IEEE 2013 Tencon - Spring

Pre-FFT Tapped Delay Line Adaptive Array for STBC-OFDM Transmission in CR Network

Nordin Ramli, Wan Nadzlia Shazwanie Wan Mohd Zuferi, Anizamariah Daud and Hafizal Mohamad Wireless Communication Cluster, MIMOS Berhad, Technology Park Malaysia, 57000 Kuala Lumpur, Malaysia.

Email: nordin.ramli@mimos. my

Abstract-In this paper, a Pre-FFT tapped delay line

adaptive array (TDLAA) for space-time block coded (STBC) orthogonal frequency division multiplexing transmission over underlay cognitive radio network is proposed to improve the performance of secondary users while opportunistically utilize pre-existing primary links without harmful interference. The technique is based on the transversal filter adaptive array which performs the joint interference cancellation and channel equalization. The Pre-FFT TDLAA maximizes transmission ef­ficiency of SUs by incorporating the delayed signals to enhance the desired signal instead of excluding them as interferences. The optimum weight determination for the proposed scheme which performs joint processes under minimum mean square error criterion is developed. Simulation results demonstrate that the proposed scheme can suppress the interference ef­fectively , thus improves the performance of STBC-OFDM transmission significantly.

I. INTRODUCTION

As the nature of spectrum sharing, a cognitive radio (CR) network inevitably operates in interference intensive envi­ronments. Effective interference management is therefore essential to allow the coexistence of primary user (PU) and CR networks, as SU can reuse the PU's spectrum only under the condition that the primary services are not harmfully interrupted. In previous works, many have considered in managing the interference with PU being the subject of interest and less attention has been given to the SUo Here, we focus on the SU performance improvement that is mostly formulated as a capacity or rate maximization problem with restricted power and interference [1].

In this paper, we consider a CR network that employs Or­thogonal Frequency Division Multiplexing (OFDM) for their transmission. OFDM is a spectrally efficient modulation scheme due to its overlapped carrier spectrum which orthog­onal to each other. Thus, it gives a higher bit rate compared to the single carrier transmission [1]. The combination of space-time block coding (STBC) [2] at the transmit diversity technique in the OFDM has been considered in [3] to achieve both spatial diversity and path diversity at the same time. To improve the performance of OFDM transmission, a method that exploit a spatial diversity by utilizing multiple antenna elements. Typically, depending on whether the Fast Fourier transform (FFT) is performed before or after diversity com­bining, the structure of adaptive antenna array in OFDM receiver can be classified into two types, namely, Pre- and Post-FFT adaptive antenna array [4], [5]. In the Pre-FFT adaptive antenna array (Pre-FFT AAA), the received signals of each elements of antenna array are combined before FFT processing [6], while in the Post-FFT adaptive antenna array (Post-FFT AAA), the received signal of each array elements are first taken FFT processing and then combine each of the subcarriers [5]. Although the Post-FFT AAA performs the

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subcarrier-by subcarrier combining is optimum in terms of maximizing signal-to-interference plus noise ratio (SINR), it requires a quite long training signal, an increased number of FFT processors, and extremely large computations which increase with the number of antennas and subcarriers. On the other hand, the Pre-FFT AAA scheme proposed in which requires only one FFT processor, can drastically reduce the computational complexity by tolerating a slight performance degradation, while achieving space diversity gain. In [7], an OFDM based Post-FFT beamformer technique for CR transmission was proposed by adopting an iterative weights determination technique which less time consuming and has a smaller complexity. However, the paper was only focusing on Post-FFT AAA. Recently, we have published a study on performance comparison between Pre-FFT AAA and Post­FFT AAA that performs a joint interference suppression and equalization for STBC-OFDM transmission over underlay CR network [8]. Based on [8], we have verified that the Pre­FFT AAA performed worst under the underlay frequency selective fading channel CR network due to interference from PU transmission and the delayed signals.

In this paper, we propose a Pre-FFT tapped delay line adaptive antenna array (Pre-FFT TDLAA) that performs the joint interference cancellation and equalization for STBC­OFDM transmission over underlay CR network to improve the performance of SUs while opportunistically utilize pre­existing primary links without harmful interference. It is based on the transversal filter adaptive array which perform the joint interference cancellation and channel equaliza­tion by considering both PU and SU transmission. Pre­FFT TDLAA maximizes SU's transmission efficiency by incorporating the delayed signals to enhance the desired signal instead of excluding them as interference. The opti­mum weight determination for SU to perform joint adaptive processing to minimize the interference effect from PU under minimum mean square error (MMSE) criterion is developed. The performance of the proposed technique is simulated through intensive computer simulation and results demonstrated that the proposed scheme has improved the performance of STBC-OFDM transmission significantly.

This paper is organized as follows. In Section II, the problem formulation and propagation model are presented. Section III and IV explain about the transceiver of STBC­OFDM and determination of optimum weight is given for both approaches. Section V provides simulation results and discussion. Finally, the conclusions are drawn in Section VI.

II. PROPAGATION MODEL

Consider a CR network consists of a pair of primary transmitter and receiver and a pair of secondary transmitter

IEEE 2013 Tencon - Spring

and receiver as shown in Fig. I. We assume that both the PU and the SU systems are OFDM-based multi-carrier systems using the same bandwidth for their transmissions. As illustrated in the Fig. l, the SU receiver (SU-Rx) is not only received signals from SU transmitter (SU-Tx) but also received unwanted signal from PU transmitter (PU-Tx). Thus, an interference cancellation is required at SU-Rx to reject the interference from PU. In this work, we limit our attention to the adaptive antenna array technique at SU-Rx only. A SU-Rx applies weights on the antenna array to form a desirable reception pattern.

In this paper, we assume that both PU and SU employ STBC at their transmitter. Two different signals are transmit­ted simultaneously over Nt// and NJf,;: transmit antennas. Throughout this paper, we develop the system based on STBC transmission, thus Nt; = NJf,;: = 2. On the other hand, at the receiver, Nf{; and N�;: receive antennas are assumed to be equipped at both PU and SU, respectively. The channel transfer function at secondary systems is modeled as follows:

[ hlps PS,l

Hlss _ [ !,lss SS - "SS,l !,lss ] "SS,2

hlps hlps 'PS,11 'PS,12

hlps PS,j1 hlps PS,j2

hlps PS,N1 hlps PS,N2 hlss

SS,11 hlss SS,12

hlss SS,j1 hlss

SS,j2

I)

2)

h�S!J.N1 h�s!J,N2 where h�'s,ji and h�Ss,ji are complex number expressing the channel between j-th receive antenna and i-th transmit antenna from PU-Tx to SU-Rx and from SU-Tx to SU-Rx, respectively. H�s and H�s is the channel state information of the preceding wave for PU and SU, respectively. For Ips = {I, ... , Lps -I} is l-th delayed channel information which causes inter-symbol interference (lSI) at PU and for Is S = {I, ... , L ss -I} is l-th delayed channel information which causes lSI at SUo Here, Lps and Lss are the length of the channel for PU and SU, respectively.

Fig. I: The propagation channel model considered in this work which consists of one pair of PU and one pair of SUo

III. STBC-OFDM TRANSMITTER MODEL

Figure 2 shows the STBC-OFDM transmitter for SUo For simplicity, we assume PU also applied the same architecture

243

Fig. 2: Block diagram of STBC-OFDM transmitter model for SU (also applied to PU).

of transmitter as SUo Thus, at the transmitter, given the input discrete signals of both PU at kth subcarrier data of mth OFDM symbol as S;;U[k] and SU, S;;,U[k], are divided into two groups as S:f;;_l[k] and S:f;;[k] for PU, and Sfg_1 [k] and sfg [k] for SU, respectively. Both signals of PU and SU are sent through two transmit antennas at different symbol time. For PU, at symbol time 2m -1, first antenna transmits S:f;;_l[k] while second antenna transmits S:f;;[k]. At the

next symbol time 2m, first antenna transmits -S�;;' * [k] while second antenna transmits S�;;'*l[k]. The same process is occurred at SU-Tx. The transmit signal at first and second antenna of PU and SU are summarized as follows. Note that S�U,i [k] and S;;,U,i [k] are the coded signal after STBC operation for antenna i E 1,2, at time-symbol m and (.)* denotes the conjugate.

S�;;�\[k] = Sf::_l[k], S�;;,21 [k] = Sf::]k], Sf';;-:l[k] = Sf;;r_1 [k], Sf';;�l[k] = Sf;;r[k],

SPU,2 = sPu,* [k] 2m,k 2m-l SSU,l = _Ssu,* [k] 2m,k 2m SSU,2 - SSU,* [k] 2m,k - 2m-1 .

(3)

(4)

(5)

(6)

At the transmitter, both input signals will be converted to time domain via IFFT operation. As a result, the modulated PU and SU OFDM signals data 8;;:'U[n ] and 8�U[n ] in discrete-time OFDM symbols can be expressed as

8�u[n ] =Li.'"�olS�U[k]exp(j27Tkn/K), (7)

8�U [n ] = Li.'"�ol S;;,U [k] exp(j27Tkn/ K) (8)

where K is the total number of subcarriers, and n = {O, 1, ... , K -I} can be viewed as nth samples. The cyclic prefix (CP) is attached to the modulated data 8;;:'U [n ] and transmitted signal as S;;:,U [n ]. Thernth OFDM symbol is represented in the time domain for 'n = {I ... , ... , K S }, by

i;�u[n] = 8�u[n - Ncp] mod K (9)

where Ks = K + Ncp . The transmitted signal 8(t ) is given as 8( mKs + ii) = sm[fj,]. Then the signals are then transmitted over wireless channel. At the SU-Rx, the receive signal by j-th receive antenna at time 2m - 1 and 2m after passing through the frequency selective fading channel are given as shown in (10) and (11), respectively. Here, Z�m_1 [n ] and z�m[n ] denote the complex additive white Gaussian noise (AWGN) with zero mean and variance IJ"; in each real dimension. In (10) and (II), we assume a perfect time synchronization between PU and SU transmission, thus the error due to asynchronous timing is not taken into consideration. Denote that, the first term of (10) and (11) are the interference signals from the PU-Tx which will degrade the performance of SU transmission. The second terms of both equations are the desired signal for the SUo Thus, in order to improve the performance at SU-Rx, we present the joint interference cancellation and equalization under underlay CR network environment.

IEEE 2013 Tencon - Spring

LpS-l Lss-l SU,j [ ] _ ""' {hipS -PU,l [ I ] hips -PU,l[ I ]} ""' {hiSS -SU,l [t I ] hiss -SU,2[ I ]} j [] r2m-1 n - D PS,j182m-l n- PS + PS,j282m n- PS + D SS,j182m-l - SS + SS,j282m n- ss +Z2m-l n

(10) LpS-l Lss-l

SU,j[]_ ""' {hipS -PU,l[ I ]+h1ps -PU,2[ I ]}+ ""' {hiSS -SU,l[t I ]+hlss -SU,2[ I ]}+ j [ ] (11) r2m n - D PS,j182m n- PS PS,j282m n- PS D SS,j182m - SS SS,j282m n- SS Z2m n

IV ADAPTIVE ANTENNA ARRAY FOR PRE-FFT BASED STBC-OFDM RECEPTION

In this section, we present the receiver structure of SU to reject and mitigate the interference from PU. Recently, we have presented a study on Pre-FFT AAA for CR network [S], and verified that the performance of Pre-FFT AAA in the coexistence of both licensed and unlicensed users degraded with the increasing of PU. This is due to utilization of one­tap FFT processor which neglect the delayed signals into the adaptive processing. In this section, we shall present a technique to improve the performance Pre-FFT AAA by adopting the tapped delay line to combine the delayed signals while achieving the spatial diversity. In particular, we shall discuss the conventional technique of Pre-FFT AAA and propose the Pre-FFT TDLAA in the next subsection.

First, we attempt to rewrite the receive signal in (10) and (11) in vector form. For simplicity, we define the channel of (1) and (2) to be as:

hiss SS.l h1p8,* SS.2

(12)

(13)

Next, we define the following vectors

sPUrn ] sSU[n ]

zv[n ] r�U[n ]

[Sf,;{_l[n ] Sf,;{[nW (14) [S�;;_l S�;;[nW (15) [z�[n ],z;[n ] ... zfr::'[nW (16) [r�U,l[n ] r�U,2[n ] ... r�u,NRJ[nW(17)

where v E {2m - 1, 2m}, and the zv[n ], rv[n ] can be expressed as follows.

(IS)

(19) Note that (.f and (.)H denote the transpose and conjugate transpose respectively. By using the notation from (12) to (19), we can rewrite the receive signal at the SU in the vector form as follows:

Lps-1 SU[ ] � -I APU[ ] r n = � H pss n -l ps

1= 0 Lss-1

� -I SU + � H sss [n -l ss] + z[n ] (20) 1= 0

A. Pre-F FT AAA We now present the theoretical model for Pre-FFT AAA

[S] configuration for STBC-OFDM transmission to perform the detection for the SU desired signals. Figure 3 illustrates the receiver configuration of Pre-FFT AAA, in which the

244

""""su :·······m;r;-.:j·········:s' u

ji;";JnJ S F P ��'tkl I F I P T S

Fig. 3: Block diagram of Pre-FFT AAA for STBC-OFDM transmission.

received signals are weighted and combined in time domain. We define the weight coefficient vector as

(21)

Using the MMSE criterion, the optimal weights are decided as follows:

W�;;;'-l = argrninE[ld�;;;,_dn]- (W�;;;'_l)HrSU[nW] (22)

w�;:' = argminE[ld�;:'[n ]- (w�;:')HrSU[nW] (23)

where E[.] represents the expected value. Solving (22) and (23) , the optimal weight can be represented as below:

(24)

where, Rrr = E[rSU [n ]rSU [t]H] is the covariance matrix of the receive signals, P2�-1 = E[rSU [n ]d��"'l [n lJ and

P2� = E[rSU[n ]d��'*[n lJ, are the correlation vectors be­tween receive signal and the reference desired SU signal. Here d�;'_l [n ] and d�;, [n ] are the SU reference signal at symbol 2m - 1 and 2m, respectively. The output signals at the SU-Rx can be expressed as below.

-SU [ ] Y2m-1 n y�;:'[n ]

= (W�;:'_l)HrSU[n ] = (w�;:')HrSU[n ]

(25)

(26)

Then, the final representation for the detected desired SU signals in frequency domain is drawn after the FFT operation of (26) and (26) to yield

= L.�:01 y�;:'-l [n ] exp( -j21fkn/ K) (27)

= L.�:01 y�;:'[n ] exp( -j21fkn/ K). (2S)

IEEE 2013 Tencon - Spring

Fig. 4: Block diagram of Pre-FFT TDLAA for STBC-OFDM transmission.

� .................... �

.... (IU ........................ L

Fig. 5: A tapped delay line of FIR filter with controlling weights.

B. Pre-FFT TDLAA It is noted that the Pre-FFT AAA reduces the processing

complexity, however the performance is not optimized due to exclusion of the delayed signals in the adaptive processing. In this section, we present a technique to improve Pre­FFT AAA by adopting tapped delay line adaptive array after discarding the CP, namely as Pre-FFT TDLAA. The received signal at SU-Rx of STBC-OFDM receiver for 2 x N configuration will be similar to (20). The configuration of Pre-FFT TDLAA for STBC-OFDM transmission is shown in Fig. 4. Here, the receive signal first decomposed into 2m-1 and 2m symbols separately. Next, a complex conjugation is performed to even signal, corresponding to the complex conjugation operations performed in the transmitter. Then, the samples at each antenna is put through two tapped delay line of finite impulse responses (FIR) with length Lv for temporal equalization and estimation of the desired signal, while suppressing unwanted signal. This technique uses the spatial processing across the N f

/;f receive antennas while

the temporal processing is done across the FIR filters. In Pre-FFT TDLAA, as shown in Fig. 5 the receiver arrays has N�r; elements followed by Lr weights and Lv - 1 delay units of FIR filters. Based on (20), the received signals are then put into FIR filters such as at all taps of all 2N�r; receive antenna branches can be expressed as

rSU[n ]) = [rSU[n ]T rsu[n -l r]T rSu [n -Lr + l]T]T (29)

where rSu [n ] E C2N L, x 1 . Assume the coefficients of FIR filter as

SU su su SU T Wv,j = [wv,j [1] ... Wv,j [Iv] . . . Wv,j [Lvll (30)

where w�,� [ lr] and w�,� are the weight coefficient at lvth's taps and vector represents the weight coefficient of FIR filters at j th antenna, respectively for v E {2m - 1, 2nL} . Note that, Iv = {1, 2, ... ,Lv} is the filter tap number. By

245

considering all the receive antennas, the optimal weight for SU-Rx is w�u can be shown as follows:

[ W�X ,T w�g ,T ... W�,�,T ... (w�,r:v�, ] T

The output signal is extracted by multiplying receiver weights w�u with the dimension of 2N Lv x 1, for all the receive antennas. Using the minimum mean square error (MMSE) criterion, the optimal weights are decided for v

as follows:

-SU W2m-1 -su w2m

. E[lds U [ ] -su H -sur ] I Pl I ) arg mm 2m-l n - W2m'-1 r n �f argminE[ld��[n ]- w��,HrSU[nW] (32)

Solving (31) and (32), the optimal weight can be represented as below:

(33)

where, Rfr E[TSU [n ]Tsu [n ]H] E C2NLrx2NL,

IS the covariance matrix of the receIve signals,

Pvd E[rsu[n ]dsu,* [rI]] E C2NLrXl and 2m-l 2m-l . P'2'/:n = E[rsu[n ]d��'*[n ll E C2NLrxl, are the correlation vector between receive signal and the reference signal of desired SUo Here d�u [n ] is the reference signal at symbom v E {2m - 1, 2m} . The reference signal is extracted from the pilot signal. Note that, in order to extract a higher array signal output, we use the same covariance matrix to calculate the optimal weight for 2m - 1 and 2m. The output signal is extracted from (33) to be resulted as below.

(34)

(35)

Final representation for the detected desired SU signals in frequency domain is given as follows: and (35) to yield

-su K 1 S Y2m-l[k] = L:n==-o y2�_I[n ]exp(-j27rkn jK) (36)

Y�� [k] = L:�==-OI y��[n ] exp( -j27rkn j K). (37)

V. SIMULATION RESULTS AND DISCUSSION

In this section, performance of the proposed techniques is evaluated through extensive computer simulation with the settings shown in Table I. The schemes to be evaluated are Pre-FFT AAA and Pre-FFT TDLAA for STBC-OFDM. As for comparison, we also consider the performance of Post-FFT AAA [8]. Here, the transmitter of SUs and PUs are equipped with N!f,r; = N.j;'i = 2 transmit antennas, and uses the Alamouti's STBC to encode the QPSK data symbols. The receiver is equipped with N�r; = Nf{i =

{2, 4} antennas. The channel is assumed to be frequency selective fading channel with the maximum delay of both PU and SU is eight. We assume that the pilot signal is available in the receiver and sample matrix inversion (SMI) is used as the adaptive algorithm.

First, we run the simulation for SU's cumulative distribu­tion function (CDF) of signal to interference plus noise ratio (SINR) at different value of signal-to-noise-ratio (SNR). Here, we consider the underlay CR network with one PU is currently transmitting its signal. The interference leakage from PU to SU is measured in signal-to-interference (SIR), equal to 10dB and the value of SNR is set to lOdB. The simulation is performed for both 2 x 2 and 2 x 4 configuration.

IEEE 2013 Tencon - Spring

TABLE I" SijulatiQn Parameters Simulation Parameter Value Modulation QPSK

Number of subcarriers Nc = 64 Number of FFT 64

Cyclic Prefix Ncl4 PU and SU transmit antennas NPU NSU = 2 PU and SU receive antennas NP[JxNs'J,"= {2 4} Rx' Rx '

N umber of trials 1000 Channel Model 8-path Frequency Selective Fading

Adaptive Algorithm Sample Matrix Inversion

The simulation is repeated by changing the value of SIR = 30dB while maintaining the value of SNR at IOdB. The simulation results are presented in Fig. 6(a) and 6(b), whereby, the SINR curves for Pre-FFT TDLAA is improved as compared to Pre-FFT AAA, closer to Post-FFT AAA, for both cases in 2 x 2 and 2 x 4 configurations. The performance improvement is clearly shown at the low SIR (IOdB) as compared to higher SIR (30dB). From the figure, it is proven that the interference suppression capability of SU with Pre-FFT TDLAA over Pre-FFT AAA, especially at lower SIR, due to exploitation of time domain processing gain. In addition, it also proved that time-domain process­ing in Pre-FFT TDLAA has been utilized to improve the received signals with the lower complexity, as companson to frequency domain processing [8].

, '5 i 0.6

� 115F"""-----�_!_+--_+--i--_f___-�_I ] EllA

:5

, '5 � 0.6

(a) SNR= 10dB, SIR=lOdB

� o.;f-""'�------t'----'�-{----;'---!--+---t-] EllA

:5

(b) SNR= 10dB, SIR=30dB

Fig. 6: CDF of SINR for the proposed receiver under STBC­OFDM transmission in underlay CR network.

VI. CONCLUSIONS

In this paper, we have proposed Pre-FFT TDLAA in order to impove performance of Pre-FFT AAA for STBC­OFDM transmission over underlay CR network. It is based on the transversal filter adaptive array which perform the

246

10' r--�--�--�-�--�------'

_ Pr<,-FFT AAA, SIR=3OdB

-e- P,..,-I"FT TI)[ •. '\A.sJR.:�()dll -+-Post TIT AAA, SIR=3OdB

C·, P,..,-I"FT TIlI,.·\A,SJR.Udll

�., Post TIT AM, SIR=OdB

" SI'R[dB]

(a) 2 x 2

10-4 -e- Pr,,-FFT TDLAA,SIR=3OdB -+- P,,,t FFT AAA. SIR.:Wdll

D" Pr,,-FFT MA, Sffi=OdB

0" I"re-I<'FT TIlI.AA,SIR.Udll

�" Post TIT AAA, SIR=OdB

" SNI( f�ll

(b) 2 x 4

Fig, 7: Average BER performance of the proposed receiver under frequency selective fading channel model with differ­ent SIR values for 2 x 2 and 2 x 4 STBC-OFDM transmission.

joint interference cancellation and channel equalization. The Pre-FFT TDLAA maximized transmission efficiency of SU by incorporating its delayed signals to enhance the desired signal instead of excluding them as interferences. The opti­mum weight determination for the proposed scheme which performs joint adaptive processing under minimum mean square error (MMSE) criterion have been developed. Sim­ulation results demonstrated that the proposed scheme have suppressed the interference effectively, and improved the performance of STBC-OFDM significantly. It also showed that the proposed scheme has a better performance compared to Pre-FFT AAA, with minimal complexity.

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[4] H. Matsuoka, H.Shoki, "Comparison of pre-FFT and post-FFr pro­cessing adaptive arrays for OFDM systems in the presence of co­channel interference," Pmc. IEEE Int. Symp. on Personal & Mobile

Radio Comm, 2003. [5] YLi, N.R.Sollenberger, "Adaptive antenna arrays for OFDM systems

with co-channel interference," IEEE Trans. Comm., vo1.47, no.2, 1999. [6] M.Okada, S. Komaki, "Pre-DFT combining space diversity assisted

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[8] W.N.S. Wan Mohd Zuferi, N.Ramli, H.Mohamad, and K.Abdullah, "Pre-FFT and Post-FFT Adaptive Antenna Array for OFDM Trans­mision over Cognitive Radio Network," Pmc. 4th Int. Conj: Computer

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