applications. Adaptive digital beamforming antenna array has been exploited in PCS to exploit spatial ... In our adaptive antenna testbed, digital signal processing algorithms are employed ..... Fig. 1 Testbed System (Receive-Only) Architecture ...
ADAPTIVE DIGITAL BEAMFORMING ANTENNA ARRAY FOR HIGH SPEED COMMUNICATIONS Francois P.S. Chin and Michael Y.W. Chia Centre for Wireless Communications 20 Science Park Road, #02-34/37 TeleTech Park Singapore Science Park II, Singapore 117674 e-mail: {cwccps / cwccyw}@leonis.nus.sg
Abstract The rapidly increasing demand for PCS has provided the impetus to design adaptive antenna arrays to improve spectral efficiency and enhance system capacity. With increasing data rate in some PCS application like DECT( Digital European Cordless Telecommunications), higher BER would degrade the system performance further. An adaptive antenna array testbed using 12 elements was built to evaluate its performance on high data rate mobile communications in an indoor environment for DECT applications. The simultaneous data sampling rate on the elements is about 3.5 MHz. A system design of the adaptive array using digital beamforming for off-line processing is presented. An indoor field trial was conducted to demonstrate performance improvement in terms of BER and SNR using adaptive beamforming techniques like blind algorithms over switched diversity method. Spatial Division Multiple Access (SDMA) will also be discussed to demonstrate the system capacity enhancement using adaptive array for DECT. Experiments have been conducted to demonstrate multipath mitigation, interference suppression and capacity enhancement.
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1.
INTRODUCTION
Strong demand for Personal Communication System(PCS) has led to stringent requirements for mobile radio communication to maximising spectrum efficiency and optimising signal quality. Digital European Cordless Telecommunications (DECT) is one of the emerging PCS technology which is designed for providing data and voice wireless services to business, residential and public telecommunication [7]. One of the target applications of DECT is for wireless LAN which require high data rate of 1.152 Mbps for communicating with multiple fixed terminals in an indoor environment. Such wireless high speed applications would lead to increasing BER and degrading the network performance. With increasing use of mobile computing through the Internet, capacity enhancement is a pre-requisite for such PCS applications. Adaptive digital beamforming antenna array has been exploited in PCS to exploit spatial diversity to further improve spectral efficiency has recently received considerable attention [13]. Basically, an adaptive antenna array comprises a number of antenna elements combined via a beamforming network (amplitude and phase control network). The beamforming network can be implemented in either RF, IF, real-time digital signal processing hardware, or in a hybrid solution. The adaptive antenna array also enables Space Division Multiple Access SDMA which exploits the users spatial separation to enhance system capacity. The main advantage of SDMA is that it can also be integrated into existing multiple access techniques like TDMA, FDMA and CDMA. The SDMA technique allows the multiple users to communicate in the same channel using the superposition of beams. Various studies on adaptive antenna array have been conducted for GSM/DCS[8], IS-54[9], CDMA[10] and third generation systems[11]. In this paper, the system design and experimental results of using an adaptive digital beamforming array will be discussed in the context of high data rate communication for DECT fixed terminal. In our adaptive antenna testbed, digital signal processing algorithms are employed to adaptively update of the beamformer weights at the base station, so that the radiation pattern of the array can be dynamically and adaptively shaped to coherently combine the multipaths of the wanted signal to enhance the desired signal and to suppress co-channel interference. Multiple parallel beamforming weights can also be incorporated to support spatial separation of spectrally and temporally overlapping mobile users for SDMA. Therefore, the system capacity and the quality of service can be improved. Other advantages of using adaptive antenna array include lower terminal power consumption( battery operated), range extension, ISI reduction, higher data rate support, and ease of integration into the existing radio system [4]. In terms of economic benefits, though adaptive antenna systems increase the per terminal cost, the total system cost, due to the increased coverage area of each adaptive antenna, goes down dramatically without compromising the channel capacity. Thus the adaptive antenna can achieve cost-efficient solutions capable of supporting the increasing capacity demands of current and future wireless communications systems. Therefore, Centre for Wireless Communications has been actively involved in developing the adaptive digital beamforming array for mobile communication. Currently, we have built an 12 antenna array non-real time testbed on a DECT (Digital European Cordless Standard) platform which can be easily reconfigured for other platforms like PHS and DCS1800.
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2.
SYSTEM OVERVIEW
2.1 Testbed hardware The current CWC smart antenna is a non-real time with receive only smart antenna system. The testbed system is illustrated in Fig. 1. A photograph of the adaptive array system developed is shown in Fig. 2. It can be easily configure to a real time system by including the another digital subsystem to perform the signal processing at real time. The current testbed consists of hardware to record signals received over a multipath channel and software to perform off-line processing of the collected data. The main features of the system are listed below. •
A transmitter unit which comprises a single dipole antenna and a signal generator producing DECT 1.152 MBit/s PRBS (Pseudo-Random Bit Sequence).
•
Twelve receiver channels to record the signals from an array of twelve dipole antenna elements simultaneously. Each receiver channel performs RF downconversion from 1.89 GHz to 110 MHz, and IF quadrature downconversion to baseband followed by digitisation using dual 8-bit ADCs at a sample rate of 3.456 MHz, three times of the DECT data rate.
•
A store module to record captured data into DRAM store. With 8-bit I and Q data from each of 12 digitisers at sample rate 3.456MHz, the storage data rate of the store module is 82.944MHz.
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A 64 MByte DRAM store in which the acquired data is stored while the experiment is in progress. When the experiment is completed the data is transferred to the controller PC.
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A controller computer (100MHz Pentium based PC) which configures the system for data acquisition, processes the acquired data in off-line and displays the analysis results.
2.1.1 Receiver Antenna Arrays The antenna array is designed for receiving linear polarised signals using twelve elements. If the transmitted signal from the source is vertically linear polarised , the array can expect to receive arbitrary polarised after taking into account multiple reflections and diffractions from the wall, furniture,etc in the indoor environment. In our case the dipole antenna elements are oriented in alternate polarisations’ as shown in Fig. 3a to maximise the reception from the array. Alternatively, a dual linear polarised antenna element also can be used. The antenna element is a half wavelength dipole in the form of a double sided printed circuit board using RT/Duriod 5870 with a single RF output. It is designed to be broadband with an integrated balun as part of the printed circuit board as shown in Fig 3b [12]. Each dipole gives a SWR of 1.2 at 1.88 GHz with a bandwidth of 20 % and a gain about 3 dBi at boresight. These dipoles are attached to grounded metallic holder which is mounted on a perpex carrying frame which defines the shape of the array. The frame, illustrated in Fig. 3a. is a simple plate in which the twelve dipoles are mounted in a straight line at a separation of 9.1 cm (0.576λ). Each dipole can be placed in either horizontal or vertical polarisation in the frame. The linear array is appropriate if the direction of the arrival of the received signals is approximately known. The coverage of the array is determined by the radiation patterns of the dipole elements themselves and there is no capability for steering beams in the elevation plane. 2.1.2 Receiver RF Downconverter Modules The receiver downconverter modules consist of the RF and IF modules as shown in Fig. 4. The receiver is designed to operate on the channel in the middle of the DECT 20 MHz band whose centre frequency is 1.890432 GHz. Each antenna output is fed to the RF downconverter by a 2
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meters long low loss coaxial cable. Fig. 4 shows the receiver chain of each stage. Each IF receiver module performs a quadrature downconversion from 110 MHz to baseband. The baseband outputs of the IF modules are connected to the digitiser modules via coaxial cables. RF design The objective of the RF design is to filter out interference and downconvert RF to IF signal keeping a good SNR. The entire RF to IF chain give a SNR of > 12 dB. The RF receiver consist of 12 RF modules and a RF oscillator module. The RF module consists of RF Band Pass Filter(BPF), Low Noise Amplfier , mixer, IF BPF, IF amplifier. The IF BPF perform as a channel selection filter of DECT and also reject unwanted spurious signals. The RF oscillator module is designed using the phase lock loop principle. Since there are 12 RF channels, a power splitter with 1: 12 is used to divide the RF oscillator source. A cascaded Noise Figure(NF) of 12.33 dB, Third Order Intermodulation Product (IP3) of -14.4 dBm, 1 dB Power Compression of -25 dBm were achieved. IF design The quadrature downconverter consist of 12 IF modules and a IF oscillator module. The IF design need to fulfil three objectives. It should provide sufficient strong signal to the digitisers, automatic gain control and downconversion of the IF signal to the I and Q signals for the digitisers. The IF module consists of digital attenuators, amplifiers, mixer, I& Q demodulator, low pass filter as shown in Fig. 4. The IF oscillator module consists of a crystal oscillator to generate the IF frequency, IF amplifier and a IF filter to filter out the 2nd, 3rd harmonics. Since there are 12 channels, a power splitter with 1: 12 is used to divide the IF oscillator source. The IF design gives a I& Q output signal from -13.9 dBm to -19.9 dBm. In accordance with the DECT specification the receiver must be able to demodulate signals received with a power level of from -83 dBm to -33 dBm giving a dynamic range of 50 dB. However only 48 dB of dynamic range is available with the 8 bit A/D converters used in the digitisers. To extend the dynamic range, programmable attenuation will be provided at IF using two programmable digital attenuators to give an enhanced dynamic range of 54 dB . A digital gain control loop on the Store Module will update the attenuator settings once per frame (every 10ms in DECT). 2.1.3 Digitisers The analogue I and Q channels from the IF downconverter are filtered and buffered in the digitisers[13]. It is performed by a passive anti-aliasing filter which approximates a Gaussian response. The dual-channel 8-bit A/D converters on all the digitiser modules are clocked simultaneously by a master state machine on the Store Module card. Following the A/D converters are a pair of FIFO memories which act as a temporary store for samples taken during a burst. Between bursts the data is transferred from these FIFOs via a backplane daisy chain bus. The size of the FIFOs determines the maximum number of samples that can be collected during each bust. The FIFOs are necessary since it is impractical for the daisy chain bus to operate at the full sampling rate. 2.1.4 Store Module The Store Module forms the heart of the data acquisition system. It performs the following operations[13]. 1
It recovers captured data from the FIFOs on the digitiser cards via the daisy chain bus and stores the data in the DRAM store. The DRAM store is a 64 MByte VMEbus DRAM card which is mounted on the Store Module as a daughter board.
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2
The Store Module interfaces to the controller PC via VME bus to allow transfer of the data in the DRAM store to the PC for storage on hard disk.
3
The Store Module allows acquisition parameters such as burst length, time between bursts and the number of bursts to be programmed by the controller PC. State machines on the Store Module issue gated clock signals to the digitisers according to the programmed data acquisition duty cycle.
The system is designed to perform experiments in which the transmitting antenna is stationed on a table in a plan office while the received signal from each element is recorded in the digital store. The transmitter operates continuously, but the receiver records data in bursts of programmable duration at a programmable duty cycle. In the default mode of operation the burst timing is configured to mimic the TDMA structure of DECT. Though the testbed system was designed to operate using DECT frequencies and modulation, it is designed with the flexibility to support modes corresponding to the PHS and DCS1800 standards. 2.2 Testbed Software A flexible suite of off-line processing software is written using MATLAB to perform system calibration, testbed initialisation, data acquisition control, data storage/transfer, off-line signal processing and analysis, and graph plotting. In particular, for each frame of snapshot data, the off-line processing carries out, in the following order, 1) preprocessing of snapshot data to remove DC offsets in the receiver chains; 2) processing of snapshot data to blindly recover a short data sequence, of pre-defined length, for each source to adaptively ‘train’ and update the parallel weight vectors; 3) parallel filtering of snapshot data using the weight vectors derived in the last burst to separate the sources; 4) beamformer output demodulation - timing recovery and symbol detection; 4) burst BER and SINR computation using the detected symbols and known transmitted symbol sequences; and 5) graph plotting. 2.3 Array Signal Processing The blind signal recovery algorithm employed in the testbed is based on the Iterative Least Squares with Projection Constant Modulus (ILSP-CM) Algorithm [5]. Basically, treating the communication links as Finite Impulse Response (FIR) channels, the received data vector from all the array elements, in the MIMO (multiple-input-multiple-output) scenario, can be represented as X = HS + N where the k-th columns of X are the k-th array snapshot data vector, hij of H are independent channel response from the j-th source to the i-th array element, taking into account the actual channel response and the receiver chain characteristics, sjk of S is the k-th sample of the j-th source signal, and N is the receiver noise contribution to the snapshots. Here we have considered a memoryless data model which assumes multipaths with negligible delay spread. With unknown spatial signature H and no prior known of the transmitted signal samples S, the algorithm blindly estimates both variables by minimising the ML criterion min
H ,S ∈CM
X - HS
2 F
with respect to the two variables using an alternating minimisations procedure detailed in [5]. In an alternative view, the algorithm recovers the transmitted signal samples S based on the structural factorisation of the data snapshots X. To provide reasonably accurate initial
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estimates / starting points for the procedure, the ACMA (Analytic Constant Modulus Algorithm) [6], a non-iterative approach for separating multiple constant modulus (CM) signals, has been used. With this algorithm, the recovered short data sequence from each frame can subsequently be used to update the parallel MMSE spatial beamformer weight vectors to separate out individual sources. Besides requiring no array spatial response and prior knowledge of propagation environment, this method has significant advantage over that which utilises specific training sequences as the former not only achieves bandwidth savings resulting from elimination of training sequences but also provides self-start capability before the communications link is established or after it has an unexpected breakdown. 3
EXPERIMENTAL RESULTS
3.1 Single Transmitting Terminal A simple experiment was conducted in an open plan office as shown in Fig. 5. The location of the stationary transmitting terminal (signal generator operating at 1.897334 GHz), placed on a table in a cubicle in the open plan office, is shown as Tx1. Pre-uploaded GMSK data sequence, with 512-bit period, was being transmitted with various power levels and the received signals from the 12 elements were digitised and recorded for a short duration of 5 seconds. The stored data were subsequently retrieved for off-line processing to assess the performance of the abovementioned blind algorithm against switch diversity method in terms of achievable BER and gain in SNR. The former recovers the first 80 samples, corresponding to 26 symbols due to three times oversampling, for updating the spatial beamforming weight vectors. The latter, on the other hand, simply processes the signal from the antenna element with the maximum received power. For this simple trial, the data acquisition timing was identical to the TDMA structure of DECT. Specifically, data was recorded in bursts of duration 416µs (480 bits or 1 DECT slot) with a burst rate of 10ms. Though there exist non-ideal characteristics of the 12 receiver chains, such as IQ imbalance in the demodulators and unequal receiver transfer characteristics, the array system was not calibrated for these undesirable characteristics, as the focus was to recover the data symbols and the receiver mismatches may therefore be treated as part of the communications link characteristics and subsequently equalised. Fig. 6 compares the BER vs average antenna input SNR performance of switch diversity and adaptive array using various number of antenna elements. The measured background noise level is around -90 dBm. At a BER of 10-3 , the measured result shows that the required SNR for an adaptive array of four antenna elements and an antenna array using 12-element switch diversity are 5 dB and 10 dB respectively. Therefore, an adaptive array of four antenna elements can provide a 5 dB gain compared to the switch diversity method. Further gains of 1 dB an 2 dB can be achieved using 8 elements and 12 elements with the blind equalisation method. This implies a power saving factor of at least three times can be achieved using adaptive array. If the transmitting power remains, the achieved gain can be used to extend the coverage area by the base station antenna array. Taking the indoor path loss as (Range) -4, a range extension of 30 % can be easily attained in conventional one-user-in-one-time-slot TDMA system. 3.2 Two Transmitting Terminals (SDMA) A simple experiment was conducted to investigate the uplink BER performance of two transmitting users in the same DECT time slot. Two stationary transmitting terminals,
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locations of which are indicated as Tx1 and Tx2 in Fig. 5, transmitting simultaneously at the same frequency 1.987334 GHz. A total of 500 bursts of data for 5 seconds were recorded. The transmitting power levels of the two terminals are individually adjusted such that the received signal strength at the array are approximately equal, so as to avoid near-far effect. If the received power difference is too large, the signals from the two terminals cannot be separated, that is, one of the connection signal is blocked or lost. Fig. 7 shows the average BER vs normalised input SNR (average antenna input SNR from each terminal) performance for 2-user DECT SDMA using adaptive array using various number of antenna elements. The signal separation capability improves significantly as the spatial weight vector length increases. Fig. 8 shows the additional required transmission power by each terminal in 2-user SDMA DECT to attain the same BER requirement in the conventional oneuser-in-one-time-slot DECT system. For illustration, Table 1 shows how the additional required transmission powers are derived for desired BER of 10-3. As can be seen, antenna array base station employing more elements, hence more degrees of freedom in the weight vectors, needs only marginal transmission power increase in the terminals to maintain the same BER performance, possessing better signal separation capability than that with few number of elements. In the case when there is array size constraint, spatial-temporal processing using additional temporal weights can be employed to increase the degrees of freedom available for channel equalisation, though at the expense of noise enhancement. From the performance curves in Fig. 7, it can be inferred that source coding is necessary to maintain low BER at lower transmission power for SDMA DECT operation in indoor WLAN applications. Furthermore, to prevent loss of communications link due to near-far effect, all terminals could have their transmission power tuned to generate a pre-selected received power level at the adaptive array base station, according to desired uplink BER performance. 4
CONCLUSION
A 12-element smart antenna array has been developed for high data rate of 1.152 Mbps for DECT platform. A brief system design of the adaptive array using digital beamforming for offline processing is presented. An indoor field trial demonstrates performance improvement in terms of BER and SNR using adaptive beamforming techniques using blind equalisation algorithms, such as ILSP-CM algorithm, over switched diversity method in a highly multipath environment like indoor open plan office. Uplink Spatial Division Multiple Access (SDMA) for two fixed terminals is also demonstrated using the adaptive array system. Near-far effect can be avoided by pre-tuning the transmission power of each terminals according to desired BER performance. Better signal separation capability can be obtained using more degrees of freedom in the beamforming weight vectors, which in turn proportional to the number of antenna elements. This will enhance the system capacity and make the system highly suitable for indoor wireless communications applications. 5
REFERENCES
[1]
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[2]
S.C. Swales, M.A.Beach, D.J. Edwards and J.P.McGeehan, “The Performance Enhancement of Multibeam Adaptive Base Station Antennas for Cellular Land Mobile Radio Systems”, IEEE Trans. Vehicular Technology, pp. 56-67, Feb. 1990.
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[3]
G.V. Tsoulos, M.A.Beach, S.C.Swales, “Adaptive Antennas for Third Generation DSCDMA Cellular Systems”, 45th Vehicular Technology Conference, Chicago, USA, pp.615-619, July 1995.
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Michael Tangemann and Rupert Rheinschmitt, “Comparison of Upgrade Techniques for Mobile Communications Systems”, 1994.
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I. Parra, G. Xu and H. Liu, “A least Squares Projective Constant Modulus Approach”, PIMRC’96, pp. 673-676, 1995.
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A. J. van der Veen and A. Paulraj, “An Analytical Constant Modulus Algorithm”, IEEE Trans. Signal Processing, vol. 44 no. 5, pp. 1136-1155, May 1996.
[7]
ETSI, Radio Equipment and Systems (RES3); Digital European Telecommunications 9DECT) Common Interface, ETS 300 175-1 to -9, 1992.
[8]
U. Forssen, J. Karlssoon, M. Almgren, F.Lotse, F. Konestdet, “ Adaptive Antenna Arrays for GSM 900/DCS1800,” Proc. VTC ‘94, Stockholm, Sweden, June 1994, Pp. 605-609
[9]
J. H. Winters, “ Signal Acquisition and Tracking with Adaptive Arrays in the Digital Mobile Radio System IS-54 with Flat Flading, ” IEEE Trans. on Vehicular Technology, Vol. 43, No.4, Nov. 1993, Pp. 377-384.
Cordless
[10] A.F.Naguib, A. Paulraj, T. Kailath, “ Performance of CDMA Cellular Netwroks with Basesation Antenna Arrays: The Down link,” Proc. ICC94, New Orleans, USA, May 1994, pp.795-799. [11] G.V. Tsoulos, M.A. Beach, S.C. Swales,” Application of Adaptive Antenna Technology to Third Generation Mixed Cell Radio Architectures”, Proc. VTC 94, Stockholm, June 1994, pp.615-619. [12] Brain Edward and Daniel Rees,’ A Broadband Printed Dipole with Integrated Balun’, pp. 339, 344, Microwave Journal, May 87. [13] YW Chia, PS Chin, GY Wang, YPChia, ‘Smart antenna Technical report 2’, CWC Dec. 1996.
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12 Element Antenna Array
RF Receivers 1.89GHz to 110MHz IF Receivers 110MHz to baseband PRBS
Signal generator as Transmitter
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Fig. 1 Testbed System (Receive-Only) Architecture
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for BER of 10-3 4-Element 8-Element 12-Element
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