A Preamble Pattern Identification based ... - Semantic Scholar

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JOURNAL OF NETWORKS, VOL. 7, NO. 4, APRIL 2012

A Preamble Pattern Identification based Synchronization System for UWB-based Wireless Networks Zhihong Qian

College of Communication Engineering, Jilin University E-mail:[email protected]

Xue Wang, Shuang Zu

College of Communication Engineering, Jilin University E-mail: [email protected]; [email protected] Abstract —In this paper, we address a preamble pattern identification based synchronization system for UWB-based distributed wireless networks. A correlation based preamble pattern identification method is introduced. A network domain division and nodes tree setting approach according to the principle of Voronoi diagram is proposed and discussed. Therefore, synchronization concluding not only synchronization between transmitter and receiver, but also clock drift synchronization for an entire distributed wireless networks is available. Simulation results demonstrate the relationship between preamble patterns and correlation outcomes. Meanwhile, a model nodes tree is simulated for UWB-based distributed wireless networks. Index Terms—preamble pattern, correlation, Voronoi diagram, synchronization, UWB, distributed wireless networks

I.

INTRODUCTION

With the boom of wireless communication technology, various wireless communication systems come forth one after another, which introduces conflicts of the use of available frequency resources. However, demands on applications of wireless communication system are driven tightly day by day. And systems with higher data transfer rate, low cost and low power are strongly required. Moe Z. Win, a distinguished research in wireless networks, noticed novel features and advantages of impulse radio Ref. [1]. Impulse radio communicates with baseband pulses of very short duration, typically on the order of a nanosecond, thereby spreading the energy of the radio signal very thinly from near dc to a few gigahertz. When this pulse is applied to an appropriately designed antenna, the pulse propagates with distortion. Impulse radios must contend with a variety of interfering signals, and also must insure that they do not interfere with narrow-band radio systems operating in dedicated bands. These requirements necessitate the use of spread spectrum techniques. A simple means for spreading the spectrum of the ultra-wide bandwidth low duty cycle pulse trains is time hopping, with data modulation accomplished by additional pulse position modulation at the rate of many pulses per data symbol, which remains of the concept of Ultra Wide Band (UWB).

© 2012 ACADEMY PUBLISHER doi:10.4304/jnw.7.4.660-666

Nowadays, UWB technology has attracted so much attention to meet the great demand and become the focus of research and development in short range wireless communication field, which is regarded as one of key technologies of the next generation wireless communication. In accordance with terms of FCC Ref. [2], Ultra-Wide Band is not defined just to pulse transmission Ref. [3], but can be extended to a continuous transmission technology, as long as absolute signal bandwidth is greater than 500MHz. Multi-band orthogonal frequency division multiplexing (MB-OFDM) Ref. [4] based Ultra-Wideband (UWB) systems divide the allocated 7.5 GHz spectrum into 14 bands, each with a bandwidth of 528 MHz, whereby information is transmitted using OFDM modulation on each band. It fulfills the definition of UWB according to FCC. The very high data rate (480 Mbps and beyond) capability of UWB technology would provide a compelling cable-replacement wireless technology. MB-OFDM based UWB system has been proposed for the IEEE 802.15.3a Ultra Wideband standard Ref. [5], the new Wireless-USB PHY layer standard, the standard ECMA-368 Ref. [6] and ECMA-369. Synchronization is evidently a significant issue for both UWB systems and OFDM based systems. Critical multipath effect in wireless channel would lead to transmitting signal synchronization loss and subcarrier drifts Ref. [7]. Synchronization loss could cause inter carrier interferences (ICI) and inter symbol interferences (ISI), what’s worse, cause orthogonality loss of OFDM subcarriers, as a result, degrade system performance. There are a number of researches on synchronization of UWB-based wireless networks. Reference [8] proposes effective frequency offset estimation based on BLUE synchronization proposal for MB-OFDM based UWB systems. Reference [9] is a classical frequency offset estimation approach for OFDM based systems, which is referred a lot. Reference [10] proposes an integer frequency offset estimator by frequency domain spreading for UWB multiband OFDM. References [11] [12] give non-coherent methods of UWB signal acquisition based on genetic algorithm. Since the preamble structure for MB-OFDM based UWB systems has been defined in


literature [6] already, corresponding schemes are in need to improve system synchronization capability. Adaptive timing synchronization estimators are proposed in Ref. [13] [14], which are implemented by using energy ratio of received symbols. Reference [15] proposes a multi-band estimation and compensation scheme for ultra wideband communications. Reference [16] studies a synchronization design for UWB-based wireless multimedia systems. Reference [17] gives us a robust and accurate frequency and timing synchronization method using chirp signals. Reference [18] is an improved method for CFO synchronization in MB-OFDM UWB. All of the above researches on synchronization have solved a great number of issues for UWB-based systems, but there are still some critical problems to be worked out. Classical methods, e.g. Ref.[8] and [9], are of good adaptability to most preamble based systems, but could not be used to implement synchronization in MB-OFDM based UWB systems directly because of the special structure of preamble in this system. Secondly, concerning the work of synchronization of MB-OFDM based UWB systems, a majority of estimation algorithms proposed are of great performance for preamble pattern 1 ( or equivalently 2), but the performance for preamble pattern 3 (or equivalently 4) are ignored. Thirdly, most algorithms are proposed on the assumption that preamble modes are known to receivers. However, studies about how to know the exact preamble mode used is lack of research. Meanwhile, synchronization issues in UWB based distributed networks have not been worked out perfectly. Aiming to solve the problems, we address a preamble pattern identification scheme, and a synchronization system for UWB-based distributed networks based on this. The rest of the paper is organized as follows: Section II presents UWB-based systems and synchronization description. The proposed preamble identification synchronization and systems for UWB-based distributed networks are given in Section III. Section IV shows the simulation results and discussions. Conclusion and summary are provided in Section V.

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Figure 1.

B.

UWB Channel Model The IEEE 802.15 channel modeling sub-committee has adopted modified Saleh-Valenzuela (S-V) model that can distinguish clusters and rays arrival rates. The IEEE 802.15.3a UWB RF channel model described in Ref. [19] is given by L

MB-OFDM Specifications In the MB-OFDM-based UWB system, the carrier frequency is hopped with a pre-defined set of carrier frequencies according to a time-frequency code. ECMA standard specifies three types of time-frequency codes (TFCs): TFI, TFI2 and FFI. Preamble patterns are associated with different time-frequency codes. Each preamble pattern is constructed by 23 synchronization sequences and 6 channel estimation sequences (CE). Figure 1 shows the structure of preamble pattern 1 and 2 according to TFI. The first 21 sequences of synchronization sequences are PS, and the other three are FS. Preamble pattern 3 and 4, which are defined according to TFI2, are interleaved.

K

h(t ) = X ∑∑ α k ,l δ (t − Tl − τ k ,l )

(1)

l =0 k =0

where α k ,l is the channel coefficient for kth ray of lth cluster; Tl is the delay of lth cluster; τ k ,l is the delay of kth ray related to lth cluster arrival time; X is the log-normal shadowing on the amplitude. C.

Signal Model Suppose frequency offset has been estimated and compensated perfectly. The transmitted sequence in band ’k’ can be expressed as S k = {sk (0), sk (1),", sk (n − 1), sk (n), sk (n + 1),"}; n ≥ 0 (2)

The received sequence considering channel response is addressed as R k = {rk ( 0), rk (1), " , rk ( n − 1), rk ( n ), rk ( n + 1), "}; n ≥ 0 (3)

The nth sample of lth OFDM transmitted symbol in band ‘k’ is

II. SYSTEMS AND SYNCHRONIZATION DESCRIPTION A.

Preamble structure

rk (l , n) =

Lb −1

∑s

k

(l , n − i)hk (i) + wk (l , n);1 ≤ l ≤ L (4)

i =0

where s k (l , n) is the nth sample of lth symbol in band ‘k’. wk (n, l ) is the corresponding AWGN sample. The transmitted signals can be described using a complex baseband signal notation. The actual RF transmitted signal is related to the complex baseband signal as follows:

⎧⎪ N −1 ⎪⎫ rRF (t ) = Re⎨ rk (t − kTSYM ) exp( j 2πf k t )⎬ ⎪⎩ k =0 ⎪⎭

∑

(5)

where Re(⋅) represents the real part of a complex variable, rk(t) is the complex baseband signal of the kth OFDM © 2012 ACADEMY PUBLISHER

662


symbol and is nonzero over the interval from 0 to TSYM, N is the number of OFDM symbols, TSYM is the symbol interval, and fk is the center frequency for the kth band. The exact structure of the kth OFDM symbol depends on its location within the packet: ⎧r preamble, k (t ) ⎪ rk (t ) = ⎨rheader , k − N preamble (t ) ⎪r (t ) ⎩ data , k − N preamble

0 ≤ k < N preamble

t ∈ [0, TCP ]

(7)

t ∈ [TCP , TFFT + TCP ] t ∈ [T FFT + TCP , T FFT + TCP + TGI ]

The parameters f and NST are defined as the subcarrier frequency spacing and the number of total subcarriers used, respectively. The resulting waveform has duration of TFFT = 1/f. Shifting the time by TCP creates the “circular prefix” which is used in OFDM to mitigate the effects of multipath. The parameter TGI is the guard interval duration. D.

Synchronization in UWB-based systems Synchronization problems in UWB-based wireless distributed system mainly conclude carrier frequency synchronization, symbol timing synchronization, sampling synchronization and clock drift synchronization. Carrier frequency synchronization means the synchronization between the receiver and transmitter and that between the sub-carrier frequency synchronization, which will make a direct impact on the sub-carrier orthogonality, resulting in inter-carrier interference (ICI). Symbol timing synchronization refers to how to find the correct symbol start position at receivers, so as to do error-free demodulation to data. When timing errors estimated make the FFT symbol window beyond the borders, ISI and ICI will work. Sampling synchronization is to estimate and compensate the sampling frequency asynchronies between the transmitters A/D and receivers A/D. sampling synchronization error will lead to ICI among sub-carriers sampled. Clock offset and drift synchronization is to estimate clock offset in a network, and compensate it. Although wide bandwidth decreases the sensitivity to frequency offset, the demands of high transfer rate and fast frequency-hopping make it more difficult to achieve carrier frequency synchronization. The capturing speed and accuracy requirement enhance difficulties to timing synchronization. Sampling synchronization makes much less impact to the system. Clock drift synchronization is of significant value for

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III. PREAMBLE PATTERN IDENTIFICATION AND SYNCHRONIZATION SYSTEMS FOR UWB-BASED

N preamble ≤ k < N header (6) N header ≤ k < N data

All of the OFDM symbols rk(t) can be constructed using an inverse Fourier transform with a certain set of coefficient Cn, where the coefficients are defined as either data, pilots, or training symbols: ⎧ ⎪0 ⎪ ⎪ N ST / 2 rk (t ) = ⎨ ∑ C n exp( j 2πnΔ f )(t − TCP ) ⎪n = − N ST / 2 ⎪ ⎪0 ⎩

UWB-based distributed networks, which would lead to miss receiving for clock time loss. Therefore, synchronization systems for UWB-based distributed networks are seriously required, which should consider not only synchronization in physical layer, but also up layers.

WIRELESS NETWORKS

A.

Preamble patterns specification The standard PLCP preamble, which is shown in Figure , consists of three distinct portions: packet synchronization sequence, frame synchronization sequence, and the channel estimation sequence. The packet synchronization sequence shall be constructed by successively appending 21 periods, denoted as {PS0, PS1, …, PS20 }, of a time-domain sequence. Each piconet will use a distinct time-domain sequence. Each period of the timing synchronization sequence shall be constructed by pre-appending 32 “zero samples” and by appending a guard interval of 5 “zero samples” to time domain sequences. This portion of the preamble can be used for packet detection and acquisition, coarse carrier frequency estimation, and coarse symbol timing. Similarly, the frame synchronization sequence shall be constructed by successively appending 3 periods, denoted as {FS0, FS1, FS2}, of an 180 degree rotated version of the time-domain sequence specified above. Again, each period of the frame synchronization sequence shall be constructed by pre-appending 32 “zero samples” and by appending a guard interval of 5 “zero samples” to the sequences mentioned above. This portion of the preamble can be used to synchronize the receiver algorithm within the preamble. Finally, the channel estimation sequence shall be constructed by successively appending 6 periods, denoted as {CE0, CE1, …, CE5}, of the OFDM training symbol. This training symbol is generated by passing the frequency-domain sequence though the IFFT, and pre-appending the output with 32 “zero samples” and appending and a guard interval consisting of 5 “zero samples” to the resulting time-domain output. This portion of the preamble can be used to estimate the channel frequency response, for fine carrier frequency estimation, and fine symbol timing. TFCs are listed in table 1. −C96 ... −C127 −C0 −C1 ... −C127 0 0 0 0 0 C96 ... C127 C0 C1 ... C127 0 0 0 0 0

PS0

PS1

PS20

Packet Sync Sequence 21 OFDM symbols

FS0

FS1

FS2

Frame Sync Sequence 3 OFDM symbols

CE0

CE1

Channel Est Sequence 6 OFDM symbols

9.375 μs

Figure 2. Standard PLCP preamble format for a Mode 1 device

CE5


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TABLE 1 TFCS CORRESPONDING WITH PREAMBLE PATTERNS TFCs

Preamble pattern

number

Gk = e +e

Sub-bands sequences

1

TFI

1

1

2

3

1

2

3

2

TFI

2

1

3

2

1

3

2

3

TFI

3

1

1

2

2

3

3

4

TFI

4

1

1

3

3

3

3

5

FFI

5

1

1

1

1

1

1

6

FFI

6

2

2

2

2

2

2

7

FFI

7

3

3

3

3

3

3

∑ r (l, n + τ )d

*

k

C.

(n);

n =0

0 ≤ τ ≤ N SYM − 1 ,

1≤ l ≤ L

(8)

where {d } = {d1 , d 2 , "", d N } is the predefined preamble sequence. Auto correlation between consequence received symbols in frequency band ‘k’ is R k (n) =

∑ r) (l, n)r (l + d , n)

* k (l ,l + d∈L

(9)

k

where ⎧⎪3N SYM , preamble 1 & 2 (TFI ) d =⎨ ⎪⎩6 N SYM , preamble 3 & 4 (TFI 2 )

(10)

L is the total number of symbols in one band. By substituting (4) into (9), we obtain

(

)

Rk (l , n) = ∑ e j 2πε k dN SYMs / N x k* (l , n) x k (l + d , n) + G k + Wk (11)

where xk (l , n) is the channel output signal samples corresponding to the kth frequency band.

xk (l , n) =

1 N

N −1

∑ C k ( m) H k ( m )e

j 2πmn N

(12)

m =0

where H k (m) is the channel transfer function for mth frequency band.


x k (l + d ) w k (l , n)

(13) (14)

The transmitter uses different preamble patterns, and then the peak of auto correlation output would have different locations. If preamble pattern 1 is used, then the output in cases that d=NSYM, d=3NSYM, and d=6NSYM are totally different. The output in the case of d=NSYM would be of a rather small value, for there is no transmitted signal in the frequency sub-band for preamble pattern 1. The peak would be the output of the current symbol and the symbol in a d=3NSYM distance. If preamble pattern 3 is adopted, the peak would be the output of the current symbol and the symbol in a d=6NSYM distance. This feature could be used for preamble pattern identification.

Correlation based preamble pattern identification The cross correlation between the lth received OFDM symbol and preamble sequence is addressed as N −1

j 2πε k ( n + N pre + ( l + d ) N SYM ) / N

x k* (l , n) wk (l + d , n)

W k = wk* (l , n) wk (l + d , n)

B.

Rk (l ,τ ) =

− j 2πε k ( n + N pre + lN SYM ) / N

Synchronization proposals for UWB-based distributed networks For UWB-based distributed networks, synchronization is not only about synchronization between a transmitter and a receiver. Synchronization of the whole networks is in order, which refers to a large scale of synchronization concluding frequency offset estimation, timing synchronization, sampling synchronization, as well as clock offset and drift estimation and its compensation. Synchronization about frequency and timing, sampling could be operated from one node to the other node. But clock synchronization ought to take all the nodes in a distributed network, e.g. wireless sensor networks (WSN), into consideration. Therefore, if we want to get a synchronization of the whole networks, an effective approach to link all nodes is of significant importance. To do advantages to system synchronization and reduce energy consumption as much as possible, we intend to utilize Voronoi diagram to partition nodes domain, so as to get a nodes classification to build links among all the nodes. In mathematics, a Voronoi diagram is a special kind of decomposition of a metric space determined by distances to a specified discrete set of objects in the space, e.g., by a discrete set of points. Voronoi diagram has a property that the nodes in a sub-domain have a smaller distance to key node in the domain than to other key nodes. Therefore, we consider building a nodes tree by domain division according to the principle of Voronoi diagram. Nodes relationship of distance in a Voronoi diagram is shown in Figure 3. According to this feature and principle of Voronoi diagram, nodes in UWB-based distributed networks can be classified. The nodes that have a same distance to two adjacent key nodes can be acted as a special line. In Figure 3, the arrow shows the special line. The nodes on the left of the special line have a smaller distance to A than to B. Nodes on the right side of the line have a smaller distance to B than to A. Utilizing this feature, we can divide the whole networks into several sub-domains, nodes inside a certain domain have the smallest distance to the key node of the domain. Applying the feature to the

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process of node trees building, then an energy saving nodes tree could be achieved.

da = db

NP

Number of pilot subcarriers

12

NG

Number of guard subcarriers

10

NT

Total number of subcarriers used

122=(ND+NP+NG)

Df

Subcarrier frequency spacing

4.125 MHz(=fs/NFFT)

IFFT and FFT period

242.42 ns

TFFT

d a < db

B

Number of samples in zero-padded suffix Zero-padded suffix duration in time

NZPS TZPS

A

da > db

Symbol interval

312.5(=TFFT+TZPS)

FSYM

Symbol rate

3.2 MHz(=TSYM-1)

Total number of samples per symbol Number of symbols in the packet/frame synchronization sequence Duration of the packet/frame synchronization sequence

Npf

IV. SIMULATION AND DISCUSSION

Tpf

165 6 1.25 ns

800 700 600 500 Correlation value

Figure 3. Nodes distance in a Voronoi diagram

400 300 200 100 0 -100 -200

0

200

400

600 800 1000 Samples index

1200

1400

1600

1400

1600

Figure 4. Auto Correlation for TFC1 800

A.

600

400 Correlation value

Preamble pattern identification We simulate the correlation of TFC1 and TFC3 to see the correlation properties and polarities in correlation. Simulation results are shown in Figure 4 through Figure 7, from which we can get the conclusion that the preamble polarity would precipitate in correlation. Especially in the curves of cross correlation, the polarities are indicated more evidently. Therefore, we can see that preamble patterns and polarities could be achieved by the outcome of correlation, no matter auto correlation or cross correlation.

70.08 ns(=Nzps/fs)

TSYM

Ntot

We simulate our proposal in IEEE 802.15.3a Ref. [5] channel model 1 and 2 Ref. [19].The channel is invariant for the duration of preamble. We have illustrated in the previous sections that there are 24 synchronization sequences in one MB-OFDM based UWB frame, 21 packet synchronization sequences and 3 frame sequences. In the simulating process, we set Npf =6 to simulate and analyze the method for convenience, which is constructed by PS and FS sequences as [PS1, PS2, PS3, PS4, FS1, FS2] for preamble pattern 1 and 2 and [PS1, PS2, PS3, PS4, FS1, PS5] for preamble pattern 3 and 4. We adopt TFC1 and TFC3 to simulate our proposals in preamble 1 and 3, respectively. Parameters in our simulations are according to the specifications Ref. [6], which are shown in Table II. Correlation features of different preamble patterns are simulated firstly. A node tree model is simulated to show the distributed wireless networks nodes domain division and nodes tree setting up process, the structure of which saves energy consumption, and can be used to get a synchronization system.

37

200

0

-200

-400

TABLE II. PARAMETERS IN SIMULATION Parameter

Value

Description

fs

Sampling frequency

NFFT

Total number subcarriers(FFT size)

ND

Number of data subcarriers


528 MHz of

128 100

0

200

400

600 800 1000 Samples index

1200

Figure 5. Auto Correlation for TFC3


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Then a node tree base on domain division can be worked out as Figure 9. Therefore, nodes in the network are connected with a kind of prority. And syncrhonizaiton, no matter syncrhonizatoin in physical layer, or network layer, MAC layer, could be implemented with the kind of node tree. Clock offset and drift synchronization can be carried out in both sub-domain and the entire networks, which is up to the syncrhonizaiton demand. Energy consumption would decrease under this principle. When nodes within networks get increasing, the node tree could divide new domain adaptively. 50 45 40

Figure 6. Cross correlation for TFC1

35 30 25 20 15 10 5 0

0

5

10

15

20

25

30

35

40

45

50

Figure 9. Nodes tree of UWB-based distributed networks

C. Figure 7. Cross correlation for TFC3

B.

Voronoi diagram in UWB-based distributed networks To express our proposal more clearly, we simulate one condition that there are n nodes with 5 key nodes in. Then we divide the domain into 5 sub-domains with the principle of Voronoi diagram, each with one key node, the result of which is shown in Figure 8.

preamble pattern identification based synchronization analysis Aiming to analyze the features of different preamble patterns, we simulate a timing synchronization algorithm based on preamble pattern identification, synchronization probabilities of which are shown in Figure 10. It indicates the importance of preamble patterns identification, for synchronization of different preamble patterns are really different. 100

90

50 synchronization ratio (%)

45 40 35 30 25 20

80 in CM1 and TFC1 in CM1 and TFC3 in CM2 and TFC1 in CM2 and TFC3

70

60

50

15 40

10 5 0

0

5

10

15

20

25

30

35

40

45

50

0

5

10

15 SNR(dB)

20

25

Figure 10. Synchronization probability of preamble pattern identification based timing synchronization scheme

Figure 8. Domain division with Voronoi diagram principle


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V. CONCLUSION This paper addresses a preamble pattern identification based synchronization systems for UWB-based distributed networks. Correlation based preamble pattern identification and Voronoi diagram based network domain division are expressed, as well as nodes tree building up. Simulations demonstrate the features of correlation and the importance of preamble pattern identification. Meanwhile, the domain division and nodes tree setting based on Voronoi diagram provides a principle to synchronization all nodes in a distributed network with a relatively small consumption. The preamble pattern identification idea and networks nodes tree can be applied to any UWB-based distributed wireless networks. ACKNOWLEDGMENT This paper is supported by the National Natural Science Foundation of China (No.60940010, No.61071073), the Doctoral Fund of Ministry of Education of China (No. 20090061110043), and Graduate Innovation Fund of Jilin University (No. 20111059).

[13]

[14]

[15] [16]

[17]

[18]

REFERENCES [1] M. Z. Win, R. A. Scholtz, “Impulse radio: how it works,” IEEE Commun. Lett., vol. 2, no. 2, pp. 36-38, 1998. [2] Federal Communications Commission, “Revision of part 15 of the commission’s rules regarding Ultra-Wideband transmission systems: First report and order,” Technical Report FCC 02-48. [3] M. Z. Win, R. A. Scholtz, “Ultra-Wide bandwidth time-hoppingspread-spectrum impulse radio for wireless multiple-access communications,” IEEE Trans. Commun., vol. 48, no. 4, pp. 679-691, 2000. [4] Batra et al., “Multi-band OFDM physical layer proposal for IEEE 802.15 task group 3a,” IEEE P802.15-03/268r3, Orlando, FL, USA, Mar. 2004. [5] IEEE P802.15 Wireless Personal Area Networks (WPANs) Group 3a, “Multi-band OFDM physical layer proposal for IEEE 802.15 task group 3a,” Mar. 2004. [6] Standard ECMA-368, “High rate ultra wideband PHY and MAC standard. 1st Edition,” Dec. 2005. [7] H.Steendam, M.Moeneclaey, “Synchronization sensitivity of multi-carrier systems,” European Commun. ETT special issue on multi-carrier spread spectrum, vol. 52, no. 5, pp. 834-844, 2004. [8] Yinghui Li, Hlaing Minn, Jacobs T, Win M, “Frequency offset estimation for MB-OFDM-based UWB systems,” IEEE Trans. Commun. vol. 56, no. 6. pp. 968-979, 2008. [9] H. Minn, P. Tarasak, “Improved maximum likelihood frequency offset estimation based on likelihood metric design,” IEEE Trans. Signal Processing, vol. 54, no. 6, pp. 2076-2086, 2006. [10] Yang. H, Jeong. KS, Yi. JH et al. “Integer frequency offset estimator by frequency domain spreading for UWB multiband-OFDM,” IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, vol. E93A, no. 3, pp. 648-650, 2010. [11] Yang Zhihua, Zhang Qinyu, Zhang Naitong. “A non-coherent method of UWB siganl acquisition based on genetic algorithm”, Chinese Journal of Electronics, vol.38, no.7, pp.1568-1573, 2010. [12] Kreiser, D., Olonbayar, S., “Efficient synchronization method for IR-UWB 802.15.4a non-coherent energy


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detection receiver”, 2010 IEEE/ACM CPSCom, 18-20 Dec., 2010, pp.521-526. Sen. D, Chakrabarti. S, Kumar. RVR, “Some interesting results on compatible BER analysis issues related to multi-band timing and frequency synchronizers applicable for MB-OFDM based UWB communications,” Digital Signal Rrocessing, vol. 21, no. 2, pp.332-340, 2011. Sen. D, Chakrabarti. S, Kumar. RVR, “An adaptive timing synchronization scheme for multi-band orthogonal frequency division multiplexing based Ultra-Wideband communication systems,” Wireless Personal Communication, vol. 53, no. 2, pp. 281-298, 2010. Sen, D et al, “.A multi-band timing estimation and compensation scheme for Ultra-Wideband communications,” IEEE GLOBECOM 2008, pp.1-5, 2008. Ye, Z. Z, Duan, C. J et al. “A synchronization design for UWB-based Wireless Multimedia systems,” IEEE Transactions on Broadcasting, vol. 56, no.2, pp.211-225, 2010. Sandrine Boumard, Aarne Mammela. “Robust and accurate frequency and timing syncrhonization using chirp signals”, IEEE Transactions on Broadcasting, vol.55, no.1, pp.115-123, 2009. Aymen M. Karim, Masuri Othman, “Improved fine CFO syncrhonization for MB-OFDM UWB”, IEEE Communications Letters, vol.14, no.4, pp.351-353, 2010. A. F. Molisch, J. R. Foerster, M. Pendergrass, “Channel models for ultrawideband personal area networks,” IEEE Wireless Commun. Mag., Vol.10, no.6, pp.14-21, 2003.

Zhihong Qian, professor of Communication and Information System at the College of Communication Engineering, Jilin University, P.R. China. In 1982 he received the B.Sc. degree in Communication from the Xian College of Aeronautic Engineering, China. He graduated with the M.Sc. degree in Communication and Electronics Systems at Jilin University of Technology (JUT) in 1991 and the Ph.D. in Communication and Information Systems at Jilin University, China, in 2001. He worked for the Department of Electronic Engineering at Aeronautic Institute of technology from 1982 to 1996 as Teaching Assistant and Assistant Professor of Communication Engineering respectively. He joined the College of Communication Engineering at Jilin University in 1996, and worked as Associate Professor, and currently, Professor and Ph.D. Candidate Students Supervisor. He has worked as a visiting researcher at University of Massachusetts (2001), University of Texas (2005), and Virginia Tech (2006), all in USA, respectively. His research work focuses on wireless communication and networks, including ZigBee, Radio Frequency Identification (RFID), Wireless Sensor Networks (WSN),UWB ,and Internet of Things (IoT). In particular, he is currently involved in a number of projects on the application of wireless networks. He is the author of 3 monographs, has been granted 3 patents, has completed 20 research projects with his co-operators as a principal investigator or main co-operator, and authored and co-authored more than 80 research papers in national or international academic journals and conferences. Xue Wang, was born in Jilin province, China. She received the B.Sc. and M.Sc. from Jilin University in 2007 and 2009, Jilin, China. And now she is a doctorial student in Jilin University. Her research interests lie in the areas of wireless communications and networking, including synchronization scheme and ultra-wideband communications.