A Tutorial on Microwave Photonic Filters - OSA Publishing

JOURNAL OF LIGHTWAVE TECHNOLOGY, VOL. 24, NO. 1, JANUARY 2006

201

A Tutorial on Microwave Photonic Filters José Capmany, Senior Member, IEEE, Fellow, OSA, Beatriz Ortega, Member, IEEE, and Daniel Pastor, Associate Member, IEEE

Tutorial

Abstract—Microwave photonic filters are photonic subsystems designed with the aim of carrying equivalent tasks to those of an ordinary microwave filter within a radio frequency (RF) system or link, bringing supplementary advantages inherent to photonics such as low loss, high bandwidth, immunity to electromagnetic interference (EMI), tunability, and reconfigurability. There is an increasing interest in this subject since, on one hand, emerging broadband wireless access networks and standards spanning from universal mobile telecommunications system (UMTS) to fixed access picocellular networks and including wireless local area network (WLAN), World Interoperability for Microwave Access, Inc. (WIMAX), local multipoint distribution service (LMDS), etc., require an increase in capacity by reducing the coverage area. An enabling technology to obtain this objective is based on radio-over-fiber (RoF) systems where signal processing is carried at a central office to where signals are carried from inexpensive remote antenna units (RAUs). On the other hand, microwave photonic filters can find applications in specialized fields such as radar and photonic beamsteering of phased-arrayed antennas, where dynamical reconfiguration is an added value. This paper provides a tutorial introduction of this subject to the reader not working directly in the field but interested in getting an overall introduction of the subject and also to the researcher wishing to get a comprehensive background before working on the subject.

I. I NTRODUCTION

B

Y MICROWAVE photonic filter [1]–[5], we understand a photonic subsystem designed with the aim of carrying equivalent tasks to those of an ordinary microwave filter within a radio frequency (RF) system or link, bringing supplementary advantages inherent to photonics such as low loss, high bandwidth, immunity to electromagnetic interference (EMI), tunability, and reconfigurability. The term microwave will be freely used throughout this paper to designate either RF, microwave, or millimeter-wave signals. These terms will be used interchangeably. The use and advantages of microwave photonic filters have been thoroughly described in various references in the literature. Here, we will use a simple example to illustrate this concept. Fig. 1 depicts a typical application configuration for a moving target identification (MTI) ground radar system [5]. Manuscript received July 15, 2005; revised September 9, 2005. This work was supported by TIC2002-04344-C02-01 PROFECIA, IST-2001-37435 LABELS, the networks of excellence IST-EPIX, IST-EPHOTON/ONE, and IST NEFERTITI, and the Spanish government ayudas a parques científicos. The authors are with the Institute of Telecommunications and Multimedia (ITEAM), Universidad Politecnica de Valencia, Valencia 46022, Spain (e-mail: [email protected]). Digital Object Identifier 10.1109/JLT.2005.860478

The MTI radar uses the Doppler effect to separate the targets of interest from clutter (land, sea water, rain, etc.). To do this, the radar sends a pulse sequence with pulse width τ and interpulse period PRI = 1/PRF, where PRF identifies the pulse repetition frequency. Any moving object will generate a Doppler frequency shift ∆ν of the radar central frequency fo according to its speed (dR/dt), where R(t) designates the time-varying distance from the target to the radar. The spectral signature of each object repeats in the spectrum periodically with a period given by the PRF, which obviously sets the limit on determining an unambiguous Doppler shift. Thus, focusing on a spectral region from fo to fo + PRF is enough to get all the information regarding moving targets and clutter, and what is required after signal detection is a signal processing stage to carry out the filtering of clutter and noise (the unwanted signals) from the target(s). This is usually performed as shown in the upper part of Fig. 2 by using a digital notch filter placed after frequency down-conversion to baseband and using analog to digital conversion (ADC). In order to distinguish the small echo from the target and the large echo from the fixed objects, high-performance (14to 18-bit resolution) ADCs are required, which represents a major bottleneck in the system. If the clutter can be removed before down-conversion, then the high-resolution requirements on the ADCs can be relaxed. For example, with a 30-dB clutter attenuation, the required ADC resolution is reduced by 5 bits. This operation is difficult and costly in the microwave domain but is simple if the RF signal is modulated into an optical carrier and the whole signal is processed directly in the optical domain by means of a photonic filter as shown in the lower part of Fig. 2. The former example illustrates the general concept behind microwave photonic filters [1]–[5], which is to replace the traditional approach toward RF signal processing shown in the upper part of Fig. 3, where an RF signal originating at an RF source or coming from an antenna is fed to an RF circuit that performs the signal processing tasks (usually at an intermediate frequency band after a down-conversion operation) by a novel technique. In this approach, which is shown in the lower part of Fig. 3, the RF signal that was priorly made to modulate an optical carrier is directly processed in the optical domain by a photonic filter based on fiber and integrated photonic devices and circuits. Adding extra photonic components implies increased filter complexity on one hand but brings on the other several advantages as pointed out in most of the published literature

0733-8724/$20.00 © 2006 IEEE

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Fig. 1. Example of application of a microwave photonic filter to ground MTI radar.

Fig. 2. (Above) Typical signal processing configuration in an MTI radar system. (Below) Modified version including a microwave photonic filter prior to down-conversion.

[6]–[44]: Optical delay lines have very low loss (independent of the RF signal frequency), provide very high time bandwidth products, are immune to EMI, are lightweight, and can provide very short delays that result in very-high-speed sampling frequencies (over 100 GHz in comparison with a few gigahertz with the available electronic technology). Finally, but not less important optics provides the possibility of spatial and wavelength parallelism using wavelength division multiplexing (WDM) techniques. The purpose of this paper is to provide a tutorial introduction of this subject to the reader not working directly in the field but interested in getting an overall introduction of the subject and also to the researcher wishing to get a comprehensive background before working on the subject. To this aim, we have structured the paper in five parts. Section II provides an introduction to the theory of microwave photonic filters, including some very basic concepts to understand their operation as discrete time filters and their applications, and a more detailed description of the opera-

tion of single-source microwave photonic filters (SSMPFs) and multiple-source microwave photonic filters (MSMPFs). Section III presents and discusses their potential optical and electrical-driven limitations and the basic parameters used to evaluate their performance such as link gain, noise figure, spurious free dynamic range (SFDR), etc. In Section IV, we describe some of the main proposals for the implementation of microwave photonic filters published in the literature. Obviously, there is a considerable amount of work carried by different research groups during the last years and it is impossible to describe them in detail, so we will concentrate on those that either are useful to understand the theoretical aspects, as described in Section II, or constitute a significant achievement. Finally, Section V provides a summary, conclusions, and future challenges within this field of research. A complete reference list of the subject including more than 70 bibliographical items is provided to assist the reader interested in getting more in-depth coverage of the subject.

CAPMANY et al.: TUTORIAL ON MICROWAVE PHOTONIC FILTERS

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Fig. 3. General concept behind microwave photonic filters. The upper part shows the traditional configuration. The lower part shows the replacement of the RF filter by a microwave photonic filter.

Fig. 4.

General reference layout of a microwave photonic filter showing the relevant electrical and optical signals.

II. T HEORY OF M ICROWAVE P HOTONIC F ILTERS A. General Concepts A microwave photonic filter is a photonic structure, the objective of which is to replace a standard microwave filter used in an RF system, bringing a series of advantages (tunability, reconfigurability, electromagnetic immunity, etc.) that have been outlined in the prior section [1]–[5]. Fig. 4 shows a general reference layout of a microwave photonic filter that we

will use to explain some of the basic concepts involved in its description. Referring to the upper part of Fig. 4, the RF to optical conversion is achieved by directly (or externally) modulating either a single continuous wave (CW) source or a CW source array. The input RF signal si (t) is then conveyed by the optical carrier(s) and the composite signal is fed to a photonic circuit that samples the signal in the time domain, weights the samples, and combines them using optical delay lines and other photonic

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elements. At the output(s), the resulting signal(s) is optically RF converted by means of various optical receivers producing the output RF signal so (t). The lower part of Fig. 4 shows an equivalent black-box representation of the aimed performance of the microwave photonic filter. In essence, it is expected to relate linearly the input and output RF signals by means of an impulse response h(t) in the time domain or by a frequency response H(Ω) in the frequency domain. In practice, however, this linear relationship can only be obtained under special operating conditions. Why this happens can be understood by observing Fig. 4. Here, the only i (w) and guaranteed signal linearity is that relating the input E output Eo (w) optical fields to the optical subsystem by virtue of the linearity of Maxwell’s equations. This linear relationship is established through an optical field transfer function Ho (w), and hence o (w) = E i (w)Ho (w). E

so (t) =

ar si (t − rT ) ⇒ so (t) = si (t) ∗ h(t)

r=−N

h(t) =

N

ar δ(t − rT ) =

r=−N

N

h(n)δ(t − nT ). (2)

∞

h(n)z −n

n=−∞

H(Ω) =

− c1 so (t − T ) − · · · − cN so (t − N T ) M

So (z) = H(z) = Si (z)

=

N (z) = D(z)

bM z m=0 N

1+

−m

cN z −n

n=1

M

Γz N −M N

(4)

(z − zM )

m=1

.

(5)

(z − pN )

n=1

In (5), the system function is expressed as the quotient of two polynomials N (z) and D(z) of the complex variable z, the roots of which are known as the filter zeros and poles, respectively. The location of the filter zeros and poles depends on the values of the filter coefficients bi and cj and determine the modulus and phase response of the microwave photonic filter and whether this can be considered of minimum, maximum, or linear phase. The observation of the microwave photonic transfer function given by (3) reveals that it is spectrally periodic with a period given by 2π/T in angular frequency units or 1/T in frequency unit. This period is known as the filter free spectral range (FSR). The spectrum of a microwave photonic filter is thus periodic, and Fig. 5 illustrates a typical example that we now employ to define some basic parameters related to its spectral characterization. For bandpass filters, the spectral selectivity of any of its passbands (resonances) is given by the full width half maximum (or 3-dB bandwidth) denoted as ∆ΩFWHM . The filter selectivity of a given resonance is given by its quality or Q factor

n=−N

According to the number of samples N in the impulse response sequence, the filter can be classified as either a finite impulse response (FIR) filter if N < ∞ or an infinite impulse response (IIR) filter if N < ∞. From (2), h(t) can be regarded as a discrete-time signal or sequence and thus the usual z and discrete-time Fourier (DTF) transform techniques developed for other filter technologies [45], [46] can be fully employed for its analysis. For instance, these are given by H(z) =

so (t − nT ) = bo si (t) + b1 si (t − T ) + · · · + bM si (t − M T )

(1)

The conversion process from the input RF signal to the input electric field to the optical subsystem is a nonlinear process since ei (t) ∝ si (t), and similarly, the output RF signal is nonlinearly related to the output electric field from the optical subsystem since so (t) ∝ |eo (t)|2 , where stands for the ensemble average over the possible signal fluctuations due to the coherence properties of the single or multiple optical CW sources that are employed to feed the filter. The two nonlinear operations described together with the linear relationship (1) do not yield under general circumstances an overall linear relationship between si (t) and so (t), and in Sections II-B and C we will explore the conditions under which this overall linear relationship is obtained in practice. Let us assume for the time being that this linear operation regime is possible, and therefore N

The operation of a microwave photonic filter can alternatively be described in terms of a system difference equation and its corresponding system function

∞ n=−∞

h(n)e−jnΩT .

(3)

Q=

FSR . ∆ΩFWHM

(6)

The value of the Q factor is related to the number of samples (taps) used to implement it. If the number of taps is high (> 10), the Q factor can be approximated for uniform filters by the number of taps Q ∼ = N . This relation can be slightly corrected (Q < N ) for windowed filters. Q factors as high as 237 [32] and 938 [11] have been reported for FIR and IIR microwave photonic filters, respectively. Recently, this figure has risen up to Q > 3000 [78] using a novel technique to obtain single resonance microwave filters. Finally, the filter rejection of nonadjacent channels is measured through the main to secondary sidelobe ratio (MSSR) also shown in Fig. 5.


Fig. 5.

205

Typical periodic spectrum of a microwave photonic filter showing the relevant parameters.

B. SSMPFs [6]–[15] SSMPFs are characterized, as its name indicates, by the use of only one optical √ source to feed the filter. The source output electric field Ii ej(wo t+φ(t)) (where Ii represents the optical intensity, wo the source central frequency, and φ(t) the source phase fluctuations) is modulated by the RF input signal si (t) and the different filter samples are implemented by means of delayed and windowed replicas of the RF-modulated optical carrier. In Fig. 6(a) and (b), we show two possible implementations of an FIR and an IIR SSMPF, respectively. In the first case, a transversal filter is shown where the electric field of the input RF-modulated optical signal is evenly divided into the N outputs of a 1 × N coupler. Output port j, for instance, is connected to an attenuator, providing a field attenuation √ coefficient aj−1 and an optical delay (j − 1)T , where T is the filter basic delay. Filter samples are then evenly combined by an output N × 1 coupler. At the output port of this device, the overall electric field Eo (t) is composed of the interference of all the delayed and this signal is fed to an output photodiode that converts the optical signal into the final output RF signal so (t). The overall filter structure thus relates the input and output microwave/RF signals given in volts or amperes. In the case of the IIR structure, infinite samples of the modulated electrical field are generated. Fig. 6(b) shows, in particular, a microwave photonic filter based on a single cavity recirculating delay line formed by joining together two output ports of a fiber coupler, providing a basic delay per cavity recirculation given by T . The filter behavior is similar apart from the obvious difference that in the first case, the structure produces N samples, whereas in the second, the number of samples is, in theory, infinite. The filter operation in both cases is described by the following equation that gives the output electric field, i.e.,

E0 (t) =

−1 N 1 Ii [ar si (t − rT )] 2 ej(w0 (t−rT )+φ(t−rT )) . (7) r=0

The upper number in the sum is N for the FIR case and N → ∞ for the IIR case. The output current from the photodiode is

(assuming a detector responsivity ) I0 (t) = |E0 (t)|2 = Ii

N −1

[|ar |si (t − rT )]

r=0

+ Ii

−1 N −1 N

ar a∗s si (t − rT )si (t − sT )

r=0 s=r

× Γ ((r − s)T ) .

(8)

In the above expression, represents the ensemble average over the signal fluctuations due to the stochastic process describing the source phase noise, and Γ stands for the optical source degree of coherence, and we assume as it is customary that phase fluctuations of the optical source are modeled by an ergodic process −

Γ ((r − s)T ) ∝ e

|(r−s)T | τcoh

.

(9)

τcoh = 1/π∆ν is the source coherence time, which is inversely proportional to the source linewidth ∆ν in the absence of modulation (i.e., under CW operation). A crucial aspect that is connected with the filter operation is that of the optical source coherence, as we shall now discuss. In principle, filter linearity is only guaranteed in the optical fields (due to the linearity of Maxwell equations) but not as far as optical powers are concerned. However, this last magnitude is related to the input and output currents or voltages of the RF signals since there is a linear relationship between the output optical power and the input current/voltage at the source and between the input optical power and the output electrical current/voltage at the optical receiver. As shown in (8), the general shape of the output current is composed of two terms, an incoherent term where the output current/voltage is linearly related to the input RF signal and a coherent term that depends on the source degree of coherence and destroys, in principle, power linearity.

206


Fig. 6. (a) Layout of an FIR SSMPF. (b) Layout of an IIR SSMPF.

If the optical source has a coherence time much smaller than the basic filter delay (τcoh T ), then the second term in (8) vanishes and a linear relationship between the input and output RF signals results, i.e., I0 (t) = so (t) = Ii

N −1

[|ar |si (t − rT )] .

(10)

r=0

Filters fulfilling this condition of operation are known as incoherent filters and bring in principle several advantages. For instance, the filter impulse response as seen in (10) does not depend on any optical phase. This makes these filters very stable against environmental conditions (i.e., temperature

variations, mechanical vibrations, etc.) and is the main reason why most of the implemented architectures so far are based on this paradigm. The main disadvantage is that the filter coefficients are positive since, according to (8), the coefficients are given by |ar | = |ar |2 . Thus, in principle, only filters with positive coefficients can be implemented using this approach. In the early 1980s, Goodman, Moslehi, and others showed that filters with positive coefficients are severely limited since they always implement a resonance at baseband and, most notably, the range of transfer functions that can be implemented shows poor performance in terms of filter selectivity and roll-off. This limitation, however, has been overcome and, as we will see in the next section, today it is possible to implement


207

incoherent filters with negative coefficients using a variety of techniques. On the other extreme, if the optical source has a coherence time much bigger than the basic filter delay (τcoh > T ), then the filter works under coherent operation regime and (9) can be approximated by jwo (s−r)T

Γ ((s − r)T ) = e

.

so (t) = Ii

E0 (t) =

+ Ii

ar sin (t − rT )ej(wr (t−rT )+φr (t−rT )) .

(14)

The output current from the photodiode is (assuming again a detector responsivity ) I0 (t) = |E0 (t)|2

[|ar |si (t − rT )]

r=0 −1 N −1 N

N −1 r=0

(11)

Therefore, (8) is now given by N −1

(b) show the two possible implementations of an MSMPF discussed above. The output electric field from impinging on the photodiode in this case is given by

ar a∗s si (t − rT )si (t − sT )ejwo (s−r)T .

=

[|ar |si (t − rT )]

r=0

r=0 s=r

(12)

N −1

+

−1 N −1 N

ar a∗s si (t − rT )si (t − sT )

r=0 s=r

As it can be observed, the output RF signal is composed by a set of weighted and delayed replicas of the RF-modulating signal plus an interfering term which is optical phase sensitive. Although the overall weight coefficient of a given output sample can now be negative, the filter will now be very dependent on environmental fluctuations since part of the coefficients depends on the evolution of optical phases. Coherent SSMPFs are thus potentially very difficult to stabilize and are not implemented in practice.

j(wr −ws )t j(sws −rwr )T

×e =

N −1

e

ej[φr (t−rT )−φs (t−sT )]

[|ar |si (t − rT )] .

(15)

r=0

The second term in the above expression is zero since the output phase variations from different optical sources can be assumed to be always uncorrelated. Thus, a linear relationship between the input and output RF/microwave signal is obtained.

C. MSMPFs [16]–[31]

D. Applications of Microwave Photonic Filters

In MSMPFs, the output of an array of optical CW sources is optically combined and modulated by the RF input signal si (t). The source array can be implemented either by using an array of independent lasers, the output spectrum of a lowcost Fabry–Pérot laser, or by slicing the output of a broadband source (i.e., LED or SLED) by means of a periodic optical filter. Regardless of the particular option, the electric field prior to RF modulation is given by

Apart from the application to the field of ground radars [6] outlined in Section I, there are certainly a wide range of applications where microwave photonic filters can be of interest. For instance, in the emerging broadband wireless access networks and standards spanning from universal mobile telecommunications system (UMTS) to fixed access picocellular networks and including wireless local area network (WLAN), World Interoperability for Microwave Access, Inc. (WIMAX), local multipoint distribution service (LMDS), etc., there is a need to increase the capacity by reducing the coverage area [47]. An enabling technology to obtain this objective is radio-over-fiber (RoF) systems, where radio signals are distributed from a central location to remote antenna units (RAUs) using fiber optic transmission as shown in the upper part of Fig. 8. RoF makes it possible to centralize the RF signal processing functions in one shared location (headend). By so doing, RAUs are simplified significantly as they only need to perform optoelectronic conversion and amplification functions. The centralization of RF signal processing functions enables equipment sharing, dynamic allocation of resources, and simplified system operation and maintenance. The processing at the headend involves a prior frequency down-conversion, ADC, and baseband processing using a DSP as shown in the intermediate part of Fig. 8, which illustrates a direct fiber link joining a given RAU and the headend. The down-conversion operation can be eliminated or divided into two steps, putting less stringent requirements on the ADC and DSP operations if a microwave photonic filter

ES (t) =

N −1

Ir ej(wr t+φr (t))

(13)

r=0

where Ir , wr , and φr (t) represent, respectively, the optical intensity, the source central frequency, and the phase fluctuations of the rth component of the array. Each source implements a filter sample that is selectively delayed usually by employing a dispersive (i.e., wavelength selective) delay line implemented either by a fiber coil or by a linearly chirped fiber Bragg grating (LCFBG). The dispersive delay element is chosen such that the differential group delay experienced by adjacent wavelengths of the source array is T . Sample windowing can be achieved using different techniques. If the MSMPF is based on an array of independent sources, then the simplest way is to control the output powers of the different sources. If a sliced source is employed, then the wavelength components must be wavelengthdemultiplexed, attenuated, or amplified on an individual basis and then multiplexed prior to RF modulation. Fig. 7(a) and

208


Fig. 7. (a) Layout of an FIR MSMPF using a laser array. (b) Layout of an FIR MSMPF using a sliced broadband source.

is placed prior to optical detection as shown in the lower part of Fig. 8. The microwave photonic filter can be employed either for channel rejection [48], [49] or for channel selection applications [50]–[52]. In the first case, we deal with an optical link where not only the desired signal is carried by the fiber but also unwanted interfering signals that are also picked up by the antenna. A paradigmatic example can be found in radio astronomy applications [49], where signal transmission from several stations to a central site requires removing strong manmade interfering signals from astronomy bands. The ability to reject these interfering RF signals directly in the optical domain is a unique characteristic of these photonic filters. Another application example is for noise suppression and channel interference mitigation in the front-end stage after the receiving antenna of an UMTS base station prior to a highly selective SAW filter. In the second case [50], the signal carried by the optical link is composed of a frequency plan that comprises

several disjoint parts of the RF spectrum (UMTS, HIPERLAN, LMDS, etc.). Here, a bandpass photonic filter can be employed to select a given RF band or spectral region. Furthermore, the selected band can be changed if the filter is tunable: a feature uncommon to traditional microwave filters but possible in microwave photonic filters, as we shall see in Section III. In both cases, the position of the frequency notch or the filter bandpass can be as low as a few megahertz or as high as several tens of gigahertz due to the broadband characteristics of photonic delay lines. Microwave photonic filters can also be of interest in applications where lightweight is a prime concern, for example, as analog notch filters are also needed to achieve cochannel interference suppression in digital satellite communications systems [53]. Another important application of microwave photonic filters is in the field of true time delay beamsteering of antenna arrays [54]. A photonic true time delay system for feeding an array of antennas is based on the use of broadband photonic delay lines.


209

Fig. 8. RoF access network (upper). Potential application of microwave photonic filters at the head-end on the centralized station (lower) replacing the RF filter of standard configuration (intermediate).

Fig. 9. Photonic beamsteering system based on a laser array feeding an LCFBG. The configuration is equivalent to that of a microwave photonic transversal filter (see Fig. 19).

The feeder network for an array of N antennas is essentially equivalent to an N -tap microwave photonic tunable FIR filter where the basic filter delay T can be altered, the only difference being that each filter sample is detected by a different optical receiver that is placed before each antenna unit in the array. Fig. 9 shows an example of a photonic beamsteering system that is based on using a dispersive delay line implemented by an LCFBG featuring a dispersion parameter of D ps/nm in combination with a bank of N tunable laser sources. The wavelength distance ∆λ between adjacent sources is kept constant. The RF signal to be radiated modulates the whole set of optical sources

and each wavelength is selectively delayed by the LCFBG and then directed to a particular optical receiver feeding an element of the array after being demultiplexed. The phase difference for an RF signal of frequency Ω between adjacent elements is given by ∆Φ = ΩD∆λ, so it can be easily changed by changing ∆λ. To finalize this list of potential applications, it should not be forgotten that the very high bandwidth and potentially low delays (5 s/m) that can be achieved with optical delay lines make them an ideal technology option for the implementation of signal correlators [55] for very high speed signals and incoherent optical code division multiplexing (OCDMA) applications.

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III. L IMITATIONS AND P ERFORMANCE P ARAMETERS OF M ICROWAVE P HOTONIC F ILTERS A. Optical Sources of Performance Limitation Microwave photonic filters must overcome a series of potential limitations prior to their practical realization. We classify these limitations into two groups according to whether these limitations appear mainly in the optical domain or whether they manifest in the electrical domain. Limitations arising in the optical domain include nonlinear optical effects, polarization, positive nature of the filter coefficients due to the incoherent operation, the limited range of attainable spectral periods, spectral periodicity, filter reconfigurability, and tunability. Spectral Periodicity: The spectral periodicity of microwave photonic filters limits the bandwidth of the RF signals to be processed to a fraction of the FSR in order to avoid spectral overlapping. Single resonance (i.e., nonperiodic filters) is therefore desired for certain applications. Section IV-D addresses the techniques proposed to implement this class of filters [11], [32], [33]. Positive Coefficients: Filters working under the incoherent regime are linear in optical intensity, thus the coefficients of their impulse responses are always positive. This has two important implications as derived from the theory of positive systems [4]. The first one and more important is that the range of transfer functions that can be implemented is quite limited. The second one is that regardless of its spectral period, the transfer function always has a resonance place at baseband. This is not a serious limitation since a DC blocking filter can be inserted at the optical receiver output. Nevertheless, incoherent filters with negative coefficients can be implemented by means of different recently developed techniques [34]–[44] that are further discussed in Section IV. Fiber Nonlinearities: Filter linearity can be compromised if the optical carriers used in filter implementation deliver enough power to stimulate fiber nonlinearities. The main sources of optical nonlinearities are self-phase modulation (SPM), crossphase modulation (XPM), four-wave mixing (FWM), stimulated Brillouin scattering (SBS), and Raman scattering (SRS). The requirements for each one of these are the same as those for typical communication systems and can be found elsewhere in the literature [56]. Polarization: Polarization effects are mainly important under coherent operation [2]–[4]. However, it has been outlined and experimentally demonstrated that even under incoherent operation the filter can be sensitive to signal polarization [57], [58]. The main cause for this apparent contradiction is that some signal samples experience exactly the same delay within the filter leading to a coherent interference between them even if a broadband source is employed [57], [58]. Also, when laser sources and external modulators are used, care must be taken to adjust the source polarization to that required by the modulator. The use of polarization preserving fiber pigtails at the modulator input helps to overcome this limitation. Limited Spectral Period or FSR: As discussed in Section II-A, microwave photonic filters are periodic in spectrum since they sample the input signal at a time rate given by


T . Thus, the spectral period or FSR is given by 1/T . If the filter is fed by only one optical source, then the source coherence time (which is inversely related to the source linewidth) limits the maximum (minimum) value of the attainable FSR under incoherent (coherent) operation. MSMPFs have been proposed to overcome this limitation [15]. Reconfigurability: This property refers to the possibility to dynamically change the values of ar and ck in (4). Passive structures are incapable of this feature. Several solutions have been proposed to overcome this limitation including the use of optical amplifiers (OAs) [59]–[61], modulators [62], fiber gratings, and laser arrays [15]. Some of these are addressed later in Section IV. Tunability: This property refers to the possibility to dynamically change the position of filter resonances or notches. To provide tunability, it is necessary to alter the value of the sampling period T . Solutions that include the use of switched fiber delay lines [63], high dispersion fibers [64], and FBGs [6] have been proposed. In the last two options, a tunable source is required. Some of the main reported results are also reviewed in Section IV. B. Electrical Sources of Performance Limitation Microwave photonic filters are a particular case of an analog fiber optic link and suffer from the same electrical limitation sources, including noise and intermodulation. The performance study of the complete microwave photonic filter from the point of view of a black box with an RF input port and an RF output port is therefore essential for the sake of comparison with other existing technologies and also in order to verify properly its adequate fitting inside a real applications scenario with bounded gain, noise factor, and intermodulation characteristics. An important starting point for the analysis is the knowledge of the previously mentioned features in an RoF system [65]–[69]. In fact, the more general structure of a microwave photonic (MWP) filter shown in Fig. 4 can be treated as an RoF system with direct intensity modulation (IM) or external modulation (EM), followed by an optical transmission section that in this case includes the necessary FIR or IIR tap replication scheme, and finally, the detection front-end. Nevertheless, MWP filter structures can include additionally some specific optical components not specific of RoF as multiple optical source arrays instead single-source broadband optical sources [LED, SLED, or ASE spectrum from erbium-doped fiber amplifiers (EDFAs)] or even sliced versions such as broadband sources. We now proceed to present the gain and noise factor concepts applicable to the general case of RoF and MWP systems and include the necessary specializations applicable to microwave photonic filters. 1) Gain: The total RF gain of the MWP filter can be derived from the general set up in Fig. 10. The filter can be divided into the three main blocks from input to output, namely, the electrooptical conversion module (EO), an all-optical processing part, and finally an optical to electronic conversion (OE) module. For the EO module, there are two main options, direct IM of a semiconductor source, or EM employing a CW source. Both alternatives are equivalent from the point of view of the general operation concept of MWP filters since in both


Fig. 10. General MWP filter structure including electrooptical conversion, alloptical process, and optical detection. Definition of the optical span and RF gain reference planes.

amplitude modulation of the RF signal over the optical carrier is performed. The IM alternative can result interesting for low cost and medium–low frequency range applications due to their limited modulation bandwidth (< 1 GHz). The EM approach opens the possibility for RF modulation up to tens of gigahertz with moderated cost. Electroabsortion modulators (EAMs) and electrooptical modulator (EOMs) are the two main possibilities, EOMs being the more common option because of their moderate costs up to 10 GHz (they are very mature technologically due to the strong market of digital optical networks). EAMs, nevertheless, have also been demonstrated in a considerable number of RoF systems, and they represent a promising alternative. On other hand, EMs require one additional device for CW light generation and also involve some additional optical losses at the own EM. The total RF gain or losses defined as the RF power ratio between input and output of the MWP filter (see Fig. 10) can be approximated for the EOM case as 2 πPopt Topt Z0 PRFout = (16) TRF = PRFin 2Vπ where Z0 is the effective EOM RF input impedance or resistance of the EOM electrode, Vπ is the voltage for a π-radian optical phase shift at the EOM arms that represent the voltage excursion between a minimum to a maximum of its modulation response, [A/W] is the detector responsivity, Popt is the applied CW optical power to the EOM, and Topt is the optical power transmission parameter that embraces all the optical losses and/or gain along the optical processor including the EOM insertion losses as depicted in Fig. 10 (Gopt (dBo) = 10 log10 (Topt )). The biasing point along the standard nonlinearized raised-cosine response of the EOM is supposed to be the quadrature point (QB) that ensures the maximum linearity in optical amplitude modulation and the minimum even-order distortion terms. Equation (16) supposes also that the detected photocurrent is applied to load impedance RL equal to Z0 , in other case, a factor RL /Z0 should multiply (16), i.e., GRF (dBe) = 10 log10 (TRF )

πPopt Z0 = 2 (10 log10 (Topt )) + 20 log10 2Vπ = 2Gopt (dBo) + GEO&OE (dBe). (17)

211

The total RF gain can then be divided into two separate parts as shown in (17). The first term is the contribution of the pure optical gain or losses to the RF gain, and the second term is the contribution of the EO and OE conversion. Notice that the EO–OE process can be divided also into two conversion slope efficiency parameters, the detector responsivity [A/W ] and seom = πPopt Z0 /2Vπ [W/A] for the EOM. Expressed in that way, the slope efficiency for the EOM can be directly substituted by the equivalent parameter if direct IM is employed, i.e., sIM = dP0 /dI, which represents the slope of generated optical power versus the injected current when I > Ith , and it is proportional to the known differential quantum efficiency. It is interesting to point out that sIM is independent of the mean optical power delivered by the laser (I > Ith ) and that it only depends of the slope of the P −I curve. This is in contrast with seom that depends linearly with the CW power applied to the EOM, and therefore TRF depends quadratically. This, in principle, allows the EOM-based systems to compensate for their own EOM losses or even compensate optical insertion losses of the remaining optical processor if Popt can be increased. As an example of RF gain calculus: Popt = 10 mW, EOM: Vπ = 6 V. Z0 = 50 Ω, and Gopt = −10 dBo (including EOM, passive optical circuits like optical couplers, FBGs, circulators, optical delay lines, etc.). In that case, GEO&OE (dBe) = −16 dBe, and the total gain GRF (dBe) = −36 dBe. This total negative gain can be compensated up to 0 dB by different ways: 1) by 36 dBe of electrical amplification (before, after, or at both places the MWP), 2) by pure optical gain (in that case the required gain will be half of the electrical gain, i.e., 18 dBo), or 3) a combination of electrical and optical amplification (for example, 12 dBo + 12 dBe). All these possibilities have important implications in terms of noise figure and distortion behavior of the MWP filter as it will be shown later. The total RF gain has been calculated without any reference to the particular frequency response of the MWP structure because it has to be considered as the absolute value to be added to the normalized filter response independent of the number of taps or particular optical process. In that sense, it has to be pointed out that Popt inside (16) and (17) should include the total optical power applied to the MWP structure by the set of sources when the MWP filter is of the multiple-source type as discussed in Section II-C. 2) Noise Figure: The noise figure of the microwave photonic filter can be defined as the ratio between the total noise power spectral density at the device output Nout and the noise power due to only the thermal noise spectral density applied to the input at the reference temperature and affected by the device gain. More specifically, in our case N F (dB)

= 10 log

Nout

4kT0 TRF R

NRIN + Nshot + Nsig-ASE + NPIIN + Nth 4kT T = 10 log 0 RF

R

(18)

212


Fig. 11. EOM-based general MWP filter basic structure. Optical amplification can be included after or before optical processing. Noise sources are represented. (a) Optical intensity noise. (b) Shot noise. (c) ASE noise. (d) Thermal noise.

where k is the Boltzmann’s constant, T0 is 298 K, and R is the load resistance at the RF source applied to the MWP filter. The total noise spectral density at the output of the MWP filter is composed of different sources of noise generated along the MWP filter as we can see schematically represented in Fig. 11. Relative intensity noise (RIN) produced in the optical source [case (a)] propagates along the optical processor up to the detector and is one of the dominant sources of noise when direct IM is employed. Its spectral power density is NRIN = Ip2 RIN A2 /Hz ,

Ip = Popt Topt

Nsig-ASE = 4qηnsp Ip (GOA − 1)T2 A2 /Hz

(20)

OAs are indispensable in many cases to compensate high optical losses of the passive components along the MWP filter. EDFAs or semiconductor OAs (SOAs) can be used depending if their respective gain dynamics behavior is or not a limitation or whether this dynamic is used for some purpose [cross gain modulation (XGM), for example, to negative coefficient generation]. In the case of incorporating OAs, new sources of noise produced by the amplified spontaneous emission noise (ASE) should be considered. Detailed derivation of ASE noise sources and OA noise factor can be found in [70]. We will provide here some summarized and useful expressions for the easy calculation of the more general case with dominant signal ASE beating contribution and the procedure to extend to an arbitrary chain of AO and optical losses [70].

(21)

where η is the quantum efficiency of the detector [also inside = (qη/hν)], nsp is the population inversion parameter for the amplifier that is related with the OA gain (G0A ), and the OA noise factor (F0 ) through

(19)

where Ip is the average detected photocurrent and RIN [Hz−1 ]. Notice that this noise contribution increases with the square of Popt . Also, for the case of multiple laser arrays feeding the MWP filter, the different sources can be considered in general uncorrelated and with similar RIN values, and therefore, the total intensity noise is the adding of the individual ones, being applicable (19), where Popt contains the already mentioned aggregated array power. Notice also that intensity noise spectral density depends on the RF frequency under consideration RIN(Ω)[Hz−1 ] and therefore the resultant noise figure. External modulated systems relax the constraints over the laser source and the intensity noise features can be reduced employing CW sources with low RIN parameter. In that case, the dominant noise source is the shot noise produced at the detector output, this being intrinsic to the quantum nature of lightwave with spectral density Nshot = 2qIp A2 /Hz .

According to the previous notation, the noise power spectral density due to signal to ASE beating is [7]

F0 =

(GOA − 1) 1 2nsp + . GOA GOA

(22)

Notice also that (2) includes the term T2 that embraces the optical transmission between the OA and the detector. In this way, the expression can be applied to cover any location of the OA along the optical processing chain, leaving Topt = T1 G0A T2 , where T1 is the optical transmission before the OA (just between the source output up to the OA input). To include the noise effect of more that one amplifier along the optical process, we can use the equivalent OA gain (GOA,Eq ) and OA noise factor (FO,Eq ) of a chain of {GOA1 , FO1 } + intermediate losses (TINT ) + {GOA2 , FO2 } being GOA,Eq = GOA1 TINT GOA2 FO,Eq = FO1 +

FO2 . GOA1 TINT

(23)

Equation (23) assumes that GOA,Eq , GOA1 , and GOA1 1, and therefore, (22) reduces to F0 = 2nsp . In other case, the cascading expression can be calculated also with slight modifications [7]. Note that any OAs + optical losses chain combination can be calculated by recursive iteration employing (23). Phase-induced intensity noise (PIIN) is usually the dominant noise source in single-source incoherent microwave photonic signal processors. PIIN arises since, as mentioned previously, the incoherent regime implies the use of wide linewidth sources in order to obtain a robust transfer characteristic irrespective of environmental perturbations. The price to be paid is that the laser linewidth, which arises from random phase variations of the optical output with time, is larger than the processor FSR. Inside the optical processor, the input power is tapped into different paths (samples) and recombined at the output.


213

Fig. 12. (a) SFDR schematic definition and its relation with the system requirements. (b) IMD3 and C versus input RF power. Linearly extrapolated cross point and its relation with SFDR.

The summation of multiple optical samples at the photodetector transforms the laser phase fluctuations into intensity fluctuation noise (PIIN) at the output. PIIN noise has been studied in passive structures [71] and active recirculating delay lines [72], [73]. Recently [74], an excellent and detailed consideration of its impact and the techniques to overcome the effect of PIIN has been published in the literature [75]. Among these, it is worth mentioning the use of multiple-source architectures. Finally, added to the optical-type noise sources, we also have the thermal noise propagated along the MWP filter added to that produced at the detector load resistance and the feasible electrical gain, i.e., Nth =

2 4kT0 A /Hz . (F + TRF ) R

(24)

In the simplest case of thermal noise being dominant, if the MWP filter has considerable losses TRF 1, them NF(dB) =

F (dB) + LRF (dB), with LRF (dB) = −GRF (dB). In the opposite case, if TRF 1, then NF(dB) → 0 dB, but this will be very difficult to reach in practice because high TRF 1 involves high optical power and therefore increase of RIN and shot noise or optical gain with added ASE. 3) Harmonic and Intermodulation Distortion: Harmonic and intermodulation distortion (IMD) features are the other great constraint that should be addressed for a real application of an MWP filter. The main source of signal distortion is normally the E/O conversion stage. If we consider direct IM lasers, both static distortion produced by the P −I curve and dynamic distortion produced by the laser couple rate equation dynamics are produced. EM is dominated by the static distortion and depends on the E/O device employed (EOM or EAM) and if a linearization technique was employed. Extensive compilation of all these possibilities can be found in [68] and [69]. Whatever the E/O approach is finally used, the distortion will translate into harmonic distorsion (HD) terms and IMD terms. From all

214


Fig. 13. RF notch filter based on a fiber optic Mach–Zehnder and a linearly chirped FBG [8].

the intermodulation terms, the third-order terms (IMD3) are more deleterious because they fall over the system frequency band being difficult or impossible to avoid by simple filtering. In the case of EOM modulator (without liberalizer), the risecosine static P −V curve implies distortion and traditionally the biasing point QB that ensures maximum optical amplitude modulation and minimum even-order distortion terms (IMD2, HD2). In that case, IMD3 can be reduced, decreasing the RF power and therefore the optical modulation index (m). Nevertheless, the m reduction will imply a reduction of the carrier-to-noise ratio (CNR) at the MWP filter output due to the noise floor. There are two aspects limiting the system in opposite directions, first the noise floor level and second the RF power limit at the input due to intermodulation. This balance is summarized into the known SFDR that is defined as the fundamental carrier to the two-tone third intermodulation product just when the IMD3 product power equals the total noise power on the system bandwidth. Fig. 12(a) shows schematically the SFDR definition and how a specific application could operate with RF channels with maximum power difference ∆P between the strongest and weakest signals and SFDR should be higher than ∆P + CNRmin , being CNRmin the minimum CNR for the specific application. A general procedure to compute IMD3 output power versus output carrier power (C) for an arbitrary input RF power employs the linearly extrapolated cross point IP3 [see Fig. 12(b)]. SFDR can be easily obtained from the schematic of Fig. 12 as

SFDR =

2 10 log 3

IP3 Nout R

2 dB−Hz 3

(25)

where Nout R is the power noise spectral density (watts per hertz). For the case of using EOMs without linearization [68], IP3 = 4Ip2 R, and

SFDR

4Ip2 2 2 3 dB−Hz . = 10 log 3 RINIp2 + 2qIp + Nsig−ASE + Nth (26)

IV. P RACTICAL I MPLEMENTATION OF M ICROWAVE P HOTONIC F ILTERS A. Introduction and Brief Historical Sketch The use of optical fiber as a delay medium in the context of RF signal processing applications was proposed by Wilner and van der Heuvel as early as 1976 [75]. They were the first to note that fiber delay lines are attractive due to their low loss and low dispersion. A year later, Ohlhaber and Wilner [76] reported an experimental demonstration of an optical fiber transversal filter based on three multimode fiber delay paths to generate and correlate a 4-bit 88 Mb/s coded sequence. Also, an optical fiber frequency filter was demonstrated by Chang et al. [77], who illuminated a bundle of 15 multimode fibers that provided 15 different delays spaced by 5.2 ns, yielding a filter with a transfer function having a fundamental passband at 193 MHz. Since then, different tapping elements and dispersive mechanisms have been investigated to develop advanced single-mode optical fiber delay line architectures capable of synthesizing many sophisticated time- and frequency-domain filtering operations for basic signal processing functions. The most relevant initial activity was carried by Goodman, Shaw, and others then at the University of Stanford [4], [33]. However, most of these proposals presented filters relying on the implementation of time delays by means of fiber strands. The use of novel components such as FBGs to implement a programmable delay line based on optical RF link technology [6] opened the perspectives toward the implementation of fully reconfigurable and tunable discretetime optical processing of microwave signals. In this section, different approaches for the implementation of incoherent transversal filters are reviewed, attending to the type of source(s) employed, and focusing on the main performance and limitations presented by each one. As discussed in previous sections, there are two the main options for sources employed to implement the optical taps: The first one is where only one modulated optical source is employed. The filter taps are therefore generated from delayed versions of the output signal from this source, but a limitation of the maximum attainable filter FSR is found since interference effects need to be avoided. The second one employs multiple sources, either by using multiwavelength optical sources (lasers) modulated by the same RF signal or by using a sliced broadband source. In the first alternative, provided each source implements only one tap, there is no phase correlation between different taps,


215

Fig. 14. RF photonic filter architecture based on an EDF active cavity and two linearly chirped FBGs [9]. (Inset) Tunable bandpass frequency response.

so no limitation in the minimum time delay or maximum FSR is encountered. The second one consists of a modulated broadband optical source (LED, EDFA or SOA ASE source, etc.) with very low coherence time, which is sliced to generate all the filter taps. Since each tap is implemented by a different part of the sliced spectrum, there will be no limitations in the filter FSR, provided each slice carries a portion of the optical spectrum broad enough. Finally, we have included a subsection on negative-coefficient microwave filters due to the large interest they currently attract to researchers. The main approaches proposed in the literature for implementing these types of filters, which offer higher flexibility in the transfer function, and also do not exhibit a resonance at baseband, have also been reviewed in the section. B. Implementation of SSMPFs The first continuously tunable optical transversal filter was reported in [7]. It was based on a single tunable modulated laser source and two long chirped gratings on separate ports of a coupler as tapping elements. By varying the wavelength of the source over the chirp range of the gratings, the point of reflection of the grating shifts linearly along the length of each grating, and this enables the time delay between both reflected signals (i.e., optical taps) to be controlled. Another example of an RF notch filter was proposed in [8], showing higher resolution filtering. It was based on a fiber optic Mach–Zehnder section combined with a linearly chirped fiber grating, as shown in Fig. 13. In this structure, provided the fixed delay difference is much larger than the tunable time delay, the shift of the notch frequencies can be tuned linearly and precisely while the FSR is kept nearly unchanged, offering large flexibility for real-time signal processing. Another proposal featuring high Q filters with wide and continuous tunable center frequencies was presented in [9]. The experimental configuration for the tunable filter is shown in Fig. 14. It consists of two chirped long Bragg gratings whose reflectivities are 50% and 100%, respectively, and a section of active fiber between them, which enables a large number of taps to be generated in the impulse response. The modulated light launched into the cavity is reflected successively from both

Fig. 15. (a) Cascaded passive Mach–Zehnder filters to select a desired frequency. (b) Filter frequency response of the hybrid structure based on an active fiber grating pair cavity and the passive section [10].

gratings by passing it back and forth through the active fiber. Tuning the wavelength of the optical carrier over the reflection bandwidth of the gratings causes the point of reflection to change linearly along the length of the gratings so the basic time delay between taps is different, resulting in a tunable bandpass frequency response (see inset in Fig. 14). Further work on these structures presents hybrid approaches combining both active and passive sections to obtain a significant increase in the filter’s Q factor [10], [11] The p-section passive Mach–Zehnder lattice see Fig.15(a)] is used to eliminate

216


Fig. 16. RF photonic transversal filter structure using four fiber grating arrays and doubling the number of coefficients using a Mach–Zehnder stage [13].

Fig. 18. FIR tunable RF filter architecture based on a fiber grating array [13].

Fig. 17. (a) Eight-tap filter response just after the circulator in Fig. 4. (b) Eight-tap filter response just after tap multiplexing stage in dashed box (Fig. 4). (c) Filter tunability.

the intermediate peaks and to select the multiple that corresponds to the desired filter frequency. Although this hybrid structure can only be implemented with uniform fiber gratings,

and therefore, tunability has not been demonstrated, experimental results in [10] show a filter centered at a fundamental frequency of 1.1 GHz, exhibiting a Q factor of 801, as depicted in Fig. 15(b), and increased up to 983 when a third section is included, comprising a small-FSR long delay line difference passive filter [11]. Another complex filter composed of a single tunable laser and eight fiber grating arrays was proposed in [12]. The system configuration, shown in Fig. 16, uses a 1 × 8 splitter, and each of the grating arrays is connected via an adjustable attenuator to provide the tap weighting (windowing of the impulse response) and, therefore, different bandpass spectral profiles. Each of the eight grating arrays, corresponding to eight taps of the microwave photonics signal, has four gratings. Each of these four sets of Bragg gratings, selected by changing the optical carrier wavelength, has a different spacing increment of distance, providing different tunabilities of the bandpass responses. However, the number of taps in this structure can be increased by adding a Mach–Zehnder section, as depicted in the dashed box in Fig. 16 [13]. One beam passes through directly and the other is reflected at a grating with the same wavelength, and so placed that the optical path difference between these two arms is exactly eight times that of the unit delay time, which is related to the spacing between the adjacent two taps.


217

Fig. 19. (Top) Tunable and reconfigurable RF photonic filter architecture based on a laser array and a linearly chirped FBG [16]. (Bottom) Experimental results for a five-tap filter. (Left) Reconfigurability (reduction of sidelobes level). (Right) Tunability (different bandpass central frequency).

The impulse response, before and after this section, is also shown in Fig. 16. The frequency response of the filter measured at the output of the optical circulator is shown in Fig. 17(a), whereas the response after the stage in the dashed box shows a narrower bandwidth of the passband while the FSR remains the same, confirming that the Q factor has been doubled [see Fig. 17(b)]. The bandpass profile optimization can achieve an MSSR of 30 dB by using a Hamming windowing function and filter tunability is demonstrated by tuning the optical carrier wavelength from λ1 to λ2 , as shown in Fig. 17(c). Based on the fact that the optical fiber recirculating delay line is one of the most compact configuration to implement an IIR microwave photonic filter and can provide very steep notch response, Zhang et al. proposed in 2001 [14] an optical fiber recirculating structure incorporating a fiber grating array to achieve maximum notch depth and tunable FSR. As shown in Fig. 18, this filter consists of a fiber coupler and a length of fiber to provide delayed feedback optical signal, which can be changed in this structure by tuning the optical carrier. Finally, it is worth mentioning that other approaches that are found in the literature explore properties such as the polarization synthesizing [15] in Bragg gratings to realize incoherent

optical transversal filters with large tunable FSR by using a single optical source. C. Implementation of MSMPFs 1) Filters Based on Source Arrays: As described in Section II, a class of MSMPFs is based on the use of laser arrays, aiming to provide a further step in the sense that the filters proposed are completely flexible and allow fast and independent reconfiguration and RF tunability, although the main drawback is related to the high cost of these structures. The first proposal was done in [16] and the layout of the filter is shown in the upper part of Fig. 19. It is composed of an N laser array, where the laser wavelengths and output powers can be independently adjusted. Thus, spectrally equally spaced signals representing RF signal samples can be fed to a linearly chirped fiber grating suffering different delays but keeping constant the basic incremental delay T between two adjacent wavelengths. Furthermore, T can be changed by proper tuning of the central wavelengths emitted by the laser array, providing tunable transversal RF filters. Also, since the output powers of the lasers can be adjusted independently at high speed, impulse

218


Fig. 20. (Top) Architecture for a tunable RF photonic filter based on fixed optical sources and a tunable dispersive element [17]. (Top inset) Nonuniform magnetic field inside the electrical coil. (Bottom inset) Grating time delay response when chirp is induced: spectral location of the optical taps. (Bottom) Three-tap tunable transversal filter response by using the filter architecture described in the upper part. Bandpass filter centered at (a) 6 GHz and (b) 9 GHz.

response windowing can be easily implemented, and therefore, the filter transfer function can be reconfigured at high speed. The reader at this point is invited to compare the structure in Fig. 19 with that of Fig. 9 to verify the equivalence of the structures required for microwave photonic transversal filters and for photonic beamsteering of antenna arrays. The lower left hand side part of Fig. 19 shows the response of a five-tap uniform filter where the normalized output powers from the lasers in the array are [1 1 1 1 1] together with the response of a truncated Gaussian windowed filter where the normalized output powers from the lasers in the array are given by [0.46 0.81 1 0.81 0.46], where a reduction on the MSSR down to −20 dB can be observed. The right hand side demonstrates resonance tunability, increasing the resonance position from approximately 2 up to 4 GHz. In addition, this figure shows the carrier suppression effect (CSE) suffered by the second resonance in this specific case of dispersive media and wavelength spacing. CSE effect can be eliminated by using single sideband (SSB) modulation.

Fig. 21. Multitap transversal bandpass filter implemented by spectrally slicing a broadband source with wavelength-multiplexed Bragg grating arrays equispaced in time [19].

A limitation of this technique is that since the tunability of these filters is based on the optical wavelength tuning of the multiwavelength laser, expensive sources must be employed for them. A lower cost alternative was proposed in [17] based


219

Fig. 22. (Top left) UMTS filter layout based on a broadband slice source followed by a switched dispersive delay line. (Top right) Filter prototype developed within the IST-LABELS project. (Bottom) Filter response based on a fiber grating array [22] showing the tunability of the filter.

on dispersion variable devices. Fig. 20 shows the filter setup employing the dynamic chirp of an original uniform FBG (UFBG) controlled by a nonuniform magnetic field, which is induced by an electrical coil on a magnetostrictive transducer. The dispersion slope was changed from 300 to 900 ps/nm, and therefore, by setting the optical wavelengths at fixed values, a three-tap tunable transversal filter is implemented, as shown in the lower part of Fig. 20. Other lower cost proposals for reconfigurable RF filters based on multiwavelength lasers are based on multimode Fabry–Pérot lasers [18]. In these structures, the bias injection current to the laser is modified to change the emitted optical spectra and, therefore, the optical taps. Although reconfiguration has been demonstrated, it is limited to the spectral characteristics to the modal distribution of the laser, and tunability is only achieved when used tunable dispersive elements, as described above. 2) Filters Based on Sliced Broadband Sources: The literature offers a large variety of microwave photonic filters based on sliced broadband optical sources, showing very low coherence time and low cost as their main advantages. In this section, different slicing techniques required in these structures to generate optical taps are reviewed focusing on the tunability

and reconfigurability properties of the filters. The incorporation of FBGs to microwave photonic filters has provided enhanced flexibility. A simple discretely tunable notch filter was demonstrated [19] using two Bragg gratings written in series in one of the arms of a coupler. In such a structure, FBGs are used as tapping elements and the delay between taps is fixed by the distance between the gratings. In a further step [20], a multitap (29 taps) transversal bandpass filter was demonstrated by spectrally slicing a broadband source with wavelength-multiplexed Bragg grating arrays equispaced in time (see Fig. 21), showing the possibility of shaping the tap element profile to obtain windowing for the design of the filter response. By apodizing the reflectivity of the gratings in the array according to a Kaiser window, the MSSR was lowered up to −18 dB. The accuracy of the tap weighting and time delays guaranteed by current mass production techniques contributes to high sidelobe suppression and excellent reproducibility of the grating-based filter [21]. An example of a filtering application implemented by using this approach is published in [22], where a tunable photonic filter for noise suppression and channel interference mitigation in the front-end stage of a UMTS base station prior to the highly selective SAW filter has been developed. As shown in Fig. 22,

220


Fig. 23. Architecture of the tunable stretched UFBG-based RF filter [24]. (Inset) FSR tunability dependence on the optical wavelength spacing of the optical carriers.

the slicing of the broadband optical source is performed by an array of FBGs, which also introduces a fixed time delay between the reflected slices of the signal. A 40-nm broadband SLED centered at 1550 nm is RF modulated and tapped and delayed by the N grating array. Finally, the spectral slices are fed to a reconfigurable chain of dispersive switched sections of standard fiber to vary the time delay between the slices. By varying the configuration of the switches, the time delay between the signals reflected from different gratings is changed, and thus, tunability of the filter RF response is achieved. The UMTS channel filtering application requires a high Q factor (about 400) since the required 3-dB passband of the filter should be less than 5 MHz and the operating frequency of the filter lies within 1920–1980 MHz. Furthermore, UMTS channel filtering also requires the tunability of the RF passband within the 12 channels allocated along the 60-MHz band (1920–1980 MHz). In order to achieve such a high Q factor, the FSR of the filter is an integer fraction of the UMTS operating frequency. The filter is tuned to the upper UMTS channel at 1977 MHz (18th resonance or FSR), when the dispersive module is “switched off,” the FSR of the filter has been set to 109 MHz, and the corresponding spacing between adjacent gratings has been set to 930 mm. In order to meet the 3-dB bandwidth and 40-dB rejection level required by the application at the central RF frequency, 30 Gaussian apodized taps were employed with a spectral spacing of 1 nm. The 5-MHz tuning step between UMTS channels is achieved by sections of 1.35 km of standard fiber for the 17–19th resonances of the filter response. The small MSSR is mainly due to the spacing errors between the gratings and has been subsequently optimized to over 20 dB.

More sophisticated continuously tunable systems based on FBGs have been recently presented [23], [24]. The tunable approach was previously demonstrated to provide a simple tunable notch filter where the broadband optical source was sliced by means of only two FBGs, which can be tuned by means of a strain application stage [23]. Fig. 23 shows a filter consisting of a broadband optical source, i.e., a superelectroluminescent diode, SLED, and UFBGs as filtering elements that will be stretched to tune the reflection bandwidth, initially centered at λinit . Since the central optical frequency ωN of different gratings must be equidistant [24], each grating must be stretched over a different fiber length so that the total device length is determined by the number of optical taps. The device employs identical Bragg gratings whose initial responses have been tuned by tension before gluing the gratings on the mechanical stage. Provided one of the gratings is not glued on the stage but the others are glued over different fiber lengths, the filter tunability is demonstrated as a function of the basic wavelength spacing between adjacent optical taps corresponding to reflected signals by the gratings when different elongations are applied. The inset of Fig. 23 shows the FSR tunability in the range of 1–6 GHz when three- and four-tap filters are implemented by using a fiber length of 23 km as the dispersive element. A similar configuration for a four-tap filter where the gratings are written in a parallel configuration to achieve large sidelobe suppression by weighting the taps was also demonstrated. Other solutions are based on the use of periodical spectral slicing elements such as fiber Fabry–Pérot, sampled fiber gratings, or arrayed waveguide grating (AWG) [25]–[29]. The first one is based on the use of a transmissive low spectral period


221

Fig. 24. (Left) RF photonic filter architecture using a broadband optical source sliced by an SFBG [26]. (Right) Response of the RF photonic filter implemented from different spectral SFBG responses. (a) Asymmetric double sigmoidal. (b) Voigt function. (c) Lognormal function.

optical Fabry–Pérot filter to realize subnanometer-resolved optical sampling [25]. Superstructured fiber Bragg gratings (SFBGs) have also been proposed as slicing elements in these type of structures [26], [27], as shown in Fig. 24, leading to high rejection level (> 45 dB) and with the potential of a big variety of filter transfer functions to be synthesized by designing the proper spectral response of that of the SFBG, such as asymmetric double sigmoidal, Voigt, or lognormal functions, as depicted in the left part of Fig. 24. AWG devices have also been employed to implement broadband source slicing with a high number of taps [28], [29]. In Fig. 25, a recently proposed scheme that combines source slicing via AWG devices and signal tapping using an array of spatial light modulators (SLMs) to implement a 40-tap reconfigurable microwave photonic filter is shown. This structure has great potential because the spectrum slices can be independently adjusted or switched ON or OFF by optical components

as electronically operated attenuators providing fast tunability or reconfigurability. For instance, Fig. 26 shows different transfer functions obtained when programming standard windowing functions well known in the literature. These window functions were dynamically loaded into the SLM array, thus demonstrating the possibility of adaptive filtering. Another recently reported slicing technique employs a bulk acoustooptic tunable filter (AOTF) to select certain wavelengths from the broadband source to implement the transversal filter taps with corresponding weights and separation determined by the control signals applied to the AOTF [30]. A fiber implementation of this approach is shown in Fig. 27 [31], where a fiber Bragg grating and a longitudinal acoustic wave perform the slicing of the EDFA broadband source. The acoustic wave generated by a piezoelectric transducer driven by an RF creates a periodic strain perturbation that modulates periodically the period and the refractive index of the FBG, which has been written at the neck of a symmetric tapered fiber in order to

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Fig. 25. Forty-sample reconfigurable transversal filter using a two-stage 1 × 40 AWG configuration and a 40-SLM free space array [29].

Fig. 26. Filter response for different windowing functions [29].


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Fig. 27. Transversal filter architecture based on a Bragg-grating-based acoustooptic superlattice modulator [30]. (Insets, a and b) Spectra of the optical signal generated by 0.755- and 1.444-MHz frequency, respectively. (c) and (d) Corresponding filter response.

increase the efficiency of the acoustic interaction. The inset of Fig. 27(a) and (b) shows the spectrally equispaced bands of reflection on both sides of the original Bragg grating created at 0.755 and 1.444 MHz, respectively, leading to filters with an FSR of 6.25 and 11.5 GHz (see insets c and d in Fig. 27) and an MSSR of up to 20 dB. The reconfigurability of the filter can be obtained by applying different voltages to the piezoelectric transducer since different degrees of apodization of the optical tap intensities are achieved by controlling the acoustic power. D. Single Resonance (Nonspectrally Periodic) Microwave Photonic Filters As it has been pointed out in Section III-A, the periodic nature of the spectral response of microwave photonic filters imposes a limitation over the bandwidth of the signals to be processed. In many practical implementations, particularly in those based on the use of optical fibers as delay elements, the value of T can be considerable, yielding very low FSR values, sometimes below the gigahertz or even the hundreds of megahertz range. This is a serious drawback since the spectral range where the filter can be employed is very limited. To overcome the above drawback and obtain truly bandpass transfer functions, Minasian has proposed to use incoherent structures in cascade. The main idea is that by carefully choosing two filter configurations, one (that we call filter 1) with a low FSR and very selective resonances and a second with

broader resonances and higher FSR value, the overall filter yields a transfer function given by HF1 (Ω)HF2 (Ω), which features the resonance selectivity of the first filter and the broad FSR value of the second. For instance, in [11], a filter composed of the cascade of a very low FSR active amplified recirculating delay line filter and a chain of Mach–Zehnder interferometers (MZIs) was presented featuring Q factors of 801 and 938, respectively. The former approach has two limitations. First of all, both photonic filters must be carefully designed and stabilized for perfect spectral alignment, and second and most important, it is not clear that the transfer function of the cascade of two incoherent filters is the product of the transfer functions of their individual constituents. In fact, it can be demonstrated that this is not the general case, the main reason being the nonlinear relationships between the input and output RF currents and the optical field that propagates through the optical filters. A second alternative, recently proposed [32], is based on a fiber MZI used as a sinusoidally continuous slicing stage of the broadband spectrum emitted by the optical source used to implement a tunable bandpass filter, showing a single bandpass frequency response and large tunability, as shown in Fig. 28. By using a 3-dB bandwidth of 5.4-nm optical source and 46-km fiber length as a dispersive element, the RF filter response shows a bandpass characteristic centered at a given frequency, which can be tuned varying the periodicity of the interferometer Mach–Zehnder output spectrum. The lower part of Fig. 28 shows how a periodic wavelength spacing in the

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Fig. 28. (Top) Implementation of the RF single bandpass filter based on a broadband source and an MZI [32]. (Bottom) Tunability of the filter.

interferometer output of 0.237 and 0.173 nm leads to bandpass filters at 7.9 and 12.2 GHz. A tuning range of several tens of gigahertz has been achieved with an MSSR of over 20 dB and a maximum Q factor of 40, although potential high Q values can be obtained in this setup by choosing the appropriated broadband source and compensating the degradation effect of the dispersion slope. Finally, a recent contribution proposes the implementation of single bandpass microwave photonic filter based on the use of tuned external modulators instead of broadband external modulators at the filter input, for instance, incorporating a discrete bandpass microwave filter preceding the EOM. Therefore, a single resonance on the short RF spectral modulation region of the tuned modulator will be shown by the filter transfer function, but retaining the selectivity, tunability, and reconfigurability properties of the filter [33]. E. Microwave Photonic Filters With Negative Coefficients As discussed in Section III-A, incoherent structures that are required to obtain a linear relationship between the input and output RF signals can only implement filters with positive coefficients. This severely limits the range of impulse responses

or transfer functions that can be implemented. In this section, we briefly review some of the most important proposals to overcome this limitation. The first technique, known as differential detection, was proposed in [34] and was itself a particular case of an elegant solution proposed in [35] to implement incoherent spatial filters with complex coefficients. The impulse response of an arbitrary filter can be decomposed into positive and negative taps contribution. Each part can be implemented by a different section with only positive coefficients, but the output of each section is fed to a pair of photodiodes placed in a differential configuration. Thus, signal subtraction is achieved in the final optoelectronic conversion. Although this approach was proposed in the 1980s, the experimental demonstrations of its applicability on an RF photonic filter were performed in the last decade [36], [37]. Even though the differential detection technique allows the implementation of any kind of negative coefficient filter, extra components are required because of the required structure duplication. Furthermore, filter reconfigurability is not always easy to implement. The hybrid optoelectronic alternative [38], [39] consists of the electrical implementation of the taps, just after photodetection. Light from a directly modulated injection laser is split by


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Fig. 29. Two-tap RF filter implementing a negative coefficient using the RF signal inversion in XGM–SOA-based wavelength conversion. (Inset) Spectrum of the notch filter [40].

a coupler to implement the different signal samples, which are differently delayed and converted in a photodetector. The magnitude and sign of the tap coefficients are implemented from the value and sign of the bias voltage to each photodetector [39]. Monolithic microwave integrated circuits (MMICs) [38] have also been proposed for sign and tap weighting with good performance, although the filter bandwidth is limited to that of MMICs, and the thermal noise of these filters is increased. All-optical approaches for implementing negative coefficients are the preferred option since they overcome electronic bandwidth limitations and electrical noise distortions. Coppinger et al. [40] made a first optical attempt by exploiting the π phase shift obtained in XGM and XPM wavelength conversion using SOAs in the modulating signal of the converted carrier, as depicted in Fig. 29, corresponding to the implementation of a two-sample notch filter with negative coefficients. By using this approach, the filter bandwidth is limited by the bandwidth conversion of the SOA (which can be above 40 GHz), reconfigurability and multitap filter implementation are difficult to achieve, and polarization sensitivity of SOA devices must be overcome. Negative tapping was also demonstrated by using the carrier depletion effect in a DFB laser diode [41] in a structure that also contained cascaded FBGs. Discrete and continuous tuning was demonstrated with a linear FBG and a UFBG. Other optical techniques for the implementation of negative coefficients have been recently published. Mora et al. [42] proposed the use of tunable sources amplified by an EDFA for implementing positive coefficients, whereas negative coefficients are obtained by carving the transmission spectrum of a broadband ASE source through UFBGs, as shown in Fig. 30. This technique offers phase inversion (negative coefficients) directly in the optical domain with no bandwidth limitation, and filters can be easily reconfigured by tuning the sources and the FBGs. A main drawback of this approach is a DC component always present in the filter transfer function that arises from the nonzero average optical ASE radiation level, but it can be easily suppressed at photodetection with a blocking filter. The inset

Fig. 30. RF photonic filter with negative taps based on a broadband ASE spectrum transmitted through UFBGs. (Inset) Filter response with the detail of the optical taps employed in this implementation [42].

of Fig. 30 shows the results obtained for a five-tap transversal filter with three positive and two negative taps. Other techniques recently reported [43]–[45] rely in the counter-phase modulation in Mach–Zehnder external modulator devices by means of employing the linear part of the transfer function with positive and negative slopes in the output versus input optical power sinusoidal transfer function of an EOM. As shown in the upper part of Fig. 31, two linear modulation regions with opposite slopes can be observed centered + − and VBIAS , respectively. The at different bias voltages VBIAS same RF modulation signal applied to the modulator at each of the former bias points will produce an optical-modulated output signal with the same average power but where the modulating signals are π shifted or have different signs (positive and negative taps). Although, in principle, two modulators are + − and VBIAS , required in the transmitter, each one biased at VBIAS to implement positive and negative taps, respectively, whose outputs are combined and sent to a dispersive element that implements the constant differential time delay between the filter samples, in practice, the setup can be simplified to only one modulator if this device is provided with two input ports

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Fig. 31.


RF signal inversion in a dual-input EOM for the implementation of negative coefficients [43]. (Inset) RF signal inversion principle in the EOM response.

Fig. 32. Transfer function of an eight-coefficient filter with four negative coefficients and flat-top resonance shape: Theoretical (solid line) and experimental (dotted line) results.

[44], or a WDM architecture can be implemented by using the modulator transfer function dependence with wavelength [45]. Fig. 32 shows the transfer function of an eight-coefficient filter with four negative coefficients and flat-top resonance shape. Theoretical results in solid line and experimental results in dotted line are shown for reference and comparison. As expected, the filter resonance at baseband (typical of positive coefficient filters) has been eliminated, thus confirming the feasibility of the proposed scheme for the implementation of

negative coefficients. With this technique, phase inversion in the modulation process is limited by the modulator bandwidth, which can be high enough so as to reach 40 GHz. Finally, a new all-optical technique based on a dual-output EOM connected to undergo double-pass modulation has been used to obtain a frequency response equivalent to a two-tap negative notch filter [46] under two different topologies. The first one connects the two outputs via an isolator, and the second one uses a reverse connection of the EOM together with a


grating reflector, which can be integrated on a planar circuit and extended to tunable filters when a chirped grating is employed. V. S UMMARY AND C ONCLUSION We have provided a tutorial introduction to the subject of microwave photonic filters to the reader not working directly in the field but interested in getting an overall introduction of the subject and also to the researcher wishing to get a comprehensive background before working on the subject. The tutorial has covered both basic theoretical principles and practical limitations and has also reviewed some of the principal achievements in the area of filter implementations. Microwave photonic filters are photonic subsystems designed with the aim of carrying equivalent tasks to those of an ordinary microwave filter within an RF system or link, bringing supplementary advantages inherent to photonics such as low loss, high bandwidth, immunity to EMI, tunability, and reconfigurability. There is an increasing interest in this subject since, on one hand, emerging broadband wireless access networks and standards spanning from UMTS to fixed access picocellular networks and including WLAN, WIMAX, LMDS, etc., require an increase in the capacity by reducing the coverage area. An enabling technology to obtain this objective is based on RoF systems, where signal processing is carried at a central office to where signals are carried from inexpensive RAUs. On the other hand, microwave photonic filters can find applications in specialized fields such as radar and photonic beamsteering of phased arrayed antennas, where dynamic reconfiguration is an added value. Despite the intense research activity carried during the last decades, there is still a considerable room for improvement. Some highlights of the main current technological challenges are as follows. 1) Developing methods and techniques to obtain stable filters with high Q values. This requires a) investigation in novel techniques for increasing the number of optical taps in FIR structures possibly by combining guided wave and free space architectures; b) developing techniques for tap value control in IIR structures, and c) investigating novel structures composed by a cascade of incoherent filters. 2) Developing more compact techniques to obtain negative and complex coefficient filters. This requires a) research on novel MZM and electroabsorption modulator structures and b) extending the SOA-based XGM technique to multiple taps. 3) Refining the techniques leading to filter tunability. Mainly by a) developing flexible microwave FSR control by optical means, b) achieving stronger delays in small lengths (i.e., using photonic crystal fibers), and c) developing techniques for a tighter bounding of the tolerances in delays and filter coefficients. 4) Overcoming the effects of coherence in filters with small values of T with a view of circuit integration. R EFERENCES [1] A. Seeds, “Microwave photonics,” IEEE Trans. Microw. Theory Tech., vol. 50, no. 3, pp. 877–887, Mar. 2002.

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José Capmany (S’88–M’91–SM’96) was born in Madrid, Spain, on December 15, 1962. He received the telecommunications engineering and Ph.D. degrees from the Universidad Politécnica de Madrid, in 1987 and 1991, respectively. From 1988 to 1991, he worked as a Research Assistant with the Departamento de Tecnología Fotónica, Universidad Politécnica de Madrid. In 1991, he moved to the Departamento de Comunicaciones, Universidad Politécnica de Valencia, Valencia, Spain, where he initiated activities related to optical communications and photonics, founding the Optical Communications Group (www.gco.upv.es). He was an Associate Professor from 1992 to 1996 and has been Full Professor in optical communications, systems, and networks since 1996. At the same time, he was Telecommunications Engineering Faculty Vice-Dean from 1991 to 1996 and has been deputy head of the Communications Department since 1996. In 2002, he was appointed as the Director of the Institute of Informatics, Multimedia, Communications and Computers (IMCO2) of the Universidad Politécnica de Valencia, which now has more than 100 researchers focusing on research in information technologies and applications. His research activities and interests cover a wide range of subjects related to optical communications, including optical signal processing; microwave photonics; fiber radio systems; fiber resonators; fiber gratings; radio frequency (RF) filters; subcarrier-multiplexing (SCM), wavelength-division-multiplexing (WDM), and CDMA transmission; wavelength conversion; optical bistability; and quantum information processing using photonics and slow wave devices. He has published more than 220 papers in international refereed journals and conferences, five textbooks on optical communications, and three chapters in international research books. Dr. Capmany is a Fellow of the Optical Society of America (OSA). He has been a reviewer for 25 international scientific journals in the field of optics, photonics, and optical communications. He also is or has been a member of the editorial board of Fiber and Integrated Optics, Microwave and Optical Technology Letters, Optical Fiber Technology, and the International Journal of Optoelectronics. He has been leader of more than 20 national or international research projects, and he is currently the leader of the European Union-funded IST project LABELS, dealing with the implementation of optical internetworks based on subcarrier multiplexed label swapping. He is or has been a member of the Technical Programme Committees of the European Conference on Optical Communications (ECOC), the Optical Fiber Conference (OFC), the Integrated Optics and Optical Communications Conference (IOOC), CLEO Europe, and the Optoelectronics and Communications Conference (OECC). He has also conducted activities related to professional bodies and is the Founder and current Chairman of the IEEE Lasers and Electro-Optics Society (LEOS) Spanish Chapter and a Fellow of the Optical Society of America (OSA) and the Institution of Electrical Engineers (IEE). He was the recipient of the extraordinary doctorate prize of the Universidad Politécnica de Madrid in 1992 and has been a Guest Editor for the IEEE JOURNAL ON SELECTED TOPICS IN QUANTUM ELECTRONICS.

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Beatriz Ortega (M’03) was born in Valencia, Spain, in 1972. She received the M.Sc. degree in physics from the Universidad de Valencia, in 1995 and the Ph.D. degree in telecommunications engineering from the Universidad Politécnica de Valencia, in 1999. She joined the Departamento de Comunicaciones, Universidad Politécnica de Valencia, in 1996, where she was working with the Optical Communications Group. Her research was mainly done in the field of fiber gratings. From 1997 to 1998, she was with the Optoelectronics Research Centre, University of Southampton, U.K., where she was involved in several projects developing new add-drop filters or twincore fiber-based filters. She has published more than 60 papers and conference contributions in fiber Bragg gratings, microwave photonics, and fiber filters. Currently, she is an Associate Lecturer with the Telecommunications Engineering Faculty, Universidad Politécnica de Valencia. Her main interests include fiber gratings applications, optical delay lines, and optical networks.

Daniel Pastor (S’95–A’97) was born in Elda, Spain, on November 5, 1969. He received the Ingeniero de Telecomunicacion and the Doctor Ingeniero de Telecomunicacion (Ph.D.) degrees from the Universidad Politécnica de Valencia (UPV), Valencia, Spain, in 1993 and 1996, respectively. He joined the Departamento de Comunicaciones, UPV, in 1993, where he was with the Optical Communications Group. From 1994 to 1998, he was a Lecturer with the Telecommunications Engineering Faculty and became an Associate Professor in 1999. He has coauthored more than 120 papers in journals and international conferences in the fields of optical delay line filters, fiber Bragg gratings, microwave photonics, wavelength-division-multiplexing (WDM), and subcarrier multiplexing (SCM) ligthwave systems. In his teaching activities, he has also published three textbooks and interactive CD-ROMs for the Optical Communication and Laboratory of Optical Communications subjects at the Telecommunications Faculty, UPV. He has been a leader of two national projects related to metro and access optical networks and optical-code-division multiple-access (OCDMA), respectively, and he has also been leader of particular work packages in such European Union projects as Ligthwave Architectures for the processing of Broadband Electronics Signals (LABELS) and Glass-based modulators, Routers and Switches (GLAMOROUS). His current technical interests include microwave photonics, complex fiber Bragg grating fabrication for optical signal processing applications, WDM–SCM networks, RoF systems, and OCDMA techniques.