A Simplified Downlink Transmission and Receiving Scheme for IDMA

Transcription

1 JOURNAL OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA, VOL. 6, NO. 3, SEPTEM 8 69 A Simplified Downlin Transmission and Receiving Scheme for IDMA Xing-Zhong Xiong and Jian-Hao Hu Abstract In this paper, we propose a downlin transmission and receiving scheme for interleavedivision multiple access (IDMA) system based on time-division duplexing (TDD) mode and time-reversal (TR) technique. The proposed scheme uses the time-reversed version of the channel impulse responses (CIR) obtained from the uplin to pre-process the transmitted signal at base station. By exploiting the wea correlations of fading channels for different user ends (UE), it is helpful to alleviate the multi-user interference (MUI) and co-channel interference (CCI). Moreover, the application of the TR technique in a multiple input-single output (MISO) configuration can reduce the delay spread of the channel impulse response, and mitigate inter-symbol interference (ISI). The UE can be simplified by canceling the iteration operation. Thus the data detection of the proposed scheme is rather simple as compared with the traditional IDMA, the complexity and computational load of UE is decreased substantially, and the proposed scheme provides a great deal of privacy and security to mobile users. Index Terms Downlin, interleave-division multiple access, multi-user detection, multiple input-single output, time-reversal technique. 1. Introduction Multiple access technique is one of the ey techniques in cellular mobile communication systems, especially in personal communication. Moreover, efficiency and adaptability are the major features for the future mobile communication systems. Other requirements for such systems include high spectral efficiency, high data rate, low power consumption and low complexity. Interleave-division multiple-access (IDMA) [1] is recently proposed to meet these requirements. As a special case of CDMA system, Manuscript received June, 8; revised July 9, 8. This wor was supported by the Nature Science Founding of China under Grant. No , and National Basic Research Program of China under Grant No. 7CB3164. The authors are with National ey Lab. of Communication, University of Electronic Science and Technology of China, Chengdu, 6154, China ( xzxiong@uestc.edu.cn, jhhu@uestc.edu.cn). X.-Z. Xiong is also with Electronic & Information Engineering Department, Sichuan University of Science & Engineering, Zigong, 643, China. IDMA can employ a very simple chip-by-chip iterative multi-user detection (MUD) strategy. The computational complexity of the MUD in uplin IDMA systems is a linear function of the number of users. The MUD algorithm in uplin IDMA systems is much simpler than that used in CDMA systems. However, the complexity of user end (UE) is also one of the ey issues for the IDMA system. According to traditional IDMA UE s architecture [1],[], UE has to detect all of the signals of other users for iterative receiving. On the other hand, it dose not satisfy the system privacy and security principle that one user nows the other users parameters. How to design the UE when we can not obtain the state of the interleavers of other users becomes a very important issue. To address above-mentioned problem, we propose a simplified downlin transmission and receiving scheme for IDMA systems based on time-division duplexing (TDD) and time-reversal (TR) technique [3]-[5]. TDD mode is employed to share the common channel information and simplify UE design. TR technique has so far only been applied in underwater acoustics [3] and ultrasound [4]. TR technique can also be applied in wireless communications [5]. TR technique is applied in the downlin of IDMA systems to alleviate the multi-user interference (MUI), inter-symbol interference (ISI) and co-channel interference (CCI), and simplify UE design. Therefore, we refer to this system as time-division duplexing and time-reversal IDMA (TDR-IDMA). The TDR-IDMA system uses the conjugate of the time-reversed version of the channel impulse responses (TR-CIR) obtained from the uplin to pre-process the transmitted signal at base station (BS). By exploiting the wea correlations of fading channels for different UEs [6], it is helpful to alleviate the MUI. The signal to interference and noise ratio (SINR) of the receiver of TDR-IDMA is higher substantially than that of the conventional IDMA. With the help of the spatial and temporal focusing of TR and multiple input-single output (MISO) technique, the UE can be simplified by canceling the iteration operation [1],[]. That is, a simple one-finger RAE is used at the receiver, Thus the desired signal can be detected when we can not obtain the state of the interleaver of other users for a given user. Moreover, TR provides a great deal of privacy and security to mobile users. It is also beneficial to simplify the UE by moving the channel estimator from the receiver of

2 7 UE to the receiver of the base station. The rest of the paper is organized as follows. Section presents the system model. Section 3 gives data transmission and detection. Numerical results and discussions are presented in Section 4. Section 5 concludes the paper.. System Model.1 System Model of Traditional Downlin We consider the downlin structure of the traditional IDMA scheme with simultaneous users in a quasi-static channel, as shown in Fig. 1. The single path channel is used in the discussion for simplification. The same conclusion can also be achieved for the fading channel. The input data sequence d of user is encoded based on a low-rate code C, generating a coded sequence c =[c (1),, c (j),, c (J)] T, where J is the frame length. Then c is permutated by an interleaver Π, producing x =[x (1),, x (j),, x (J)] T. We call the elements in x as chips. Base Station Transmitter d 11 C 1 d C d C c 1 c π 1 π x 1 x c x π { n 1( j ) h h { r 1 { r { n { r Figure 1. Downlin structure of traditional IDMA JOURNAL OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA, VOL. 6, NO. 3, SEPTEM 8 Reciever for user 1 Reciever for user {e{ e ESE (x ( x,1, 1( (j)) ) {e{ e ( x ( )) DEC (x,1, 1 (j)) j DEC 1 {e{ e ESE (x( x,, (j)) ( j)) { e ( x, ) { e ( x, ) ESE {e DEC (x, (j)) DEC {eese DEC (x, (j)) { e ( x ( )) {e, j DEC DEC (x, (j)) Reciever for user { n Fig. 1. Downlin structure of traditional IDMA. dˆ ˆd 1 dˆ d dˆ As shown in Fig. 1, each of the receivers performs an iterative interference cancellation operation. It consists of an elementary signal estimator (ESE) and a ban of single-user posteriori probability (APP) decoders (DEC). The iterative detection principle is outlined in Section 3. Without loss of generality, we only focus on the receiver for user, and the operations at other receivers are just the same. h is the CIR coefficient of user.. System Model of Downlin TDR-IDMA with SISO or MISO We consider a downlin structure of the TDR-IDMA with single input-single output (SISO) and multiple input-single output (MISO) in a quasi-static fading channel environment, as shown in Fig. (a) and Fig. (b) respectively. For MISO, there are T transmitter antennas and one receive antenna. Let h t, TR-CIR coefficient of user at the be the conjugate of the tth ˆ transmitter antenna, and d represent the data sequence of user. There is not iterative detection in this TDR-IDMA downlin. It is not necessary to obtain the state of other users interleavers. So it is convenient to simplify the UE. d 1 C c1 1 π x 1 1 d C c π x h {{ r 1 r 1 (( j) j) Reciever for user 1 { n 1 { n d c x C π h h { r (j) dˆ d ˆ Reciever for user Base Station Transmitter (a) { n Figure a. Downlin structure of TDR-IDMA with SISO dˆ ˆd 1 Reciever for user h { r dˆ dˆ 1 π DEC Base Station TR-CIR h,1 User End h, 1 d c C π x dˆ h ˆ, r d h, 1 π DEC h, T h,t (b). Figure b. Downlin structure of TDR-IDMA with MISO Fig.. Downlin structure of TDR-IDMA with (a) SISO and (b) MISO. For ease of discussion, we first consider the single path channel environment without loss of generality, as similar conclusion can be drawn for the multi-path channel environments. Certainly, there are other users in the base station, but the transmitted signal is pre-processed by different TR-CIR. The ey element of the downlin TDR-IDMA systems is the signal processing in front of the antenna. TR-CIR processing performs pre-process the transmitted signal. This processing not only can overcome the impact of fading channel, but also can alleviate the MUI, ISI and CCI. On the other hand, with the help of the spatial and temporal focusing of TR and MISO, the UE can be simplified by canceling the iteration operation when we can not obtain the state of the interleavers of other users for a given user. It is also beneficial to simplify the UE by moving the channel estimator from the receiver of UE to the receiver of the base station. 3. Data Transmission and Detection 3.1 Time-Division Duplexing and Time-Reversal TDD mode and TR technique are applied in TDR-IDMA system. TDD has many prominent advantages. First, the uplin and downlin share the same frequency, bringing convenience to estimate the CIR and use smart antenna. Second, TDD has high spectral efficiency. Finally, TDD is appropriate for asymmetric services which

3 XIONG et al.: A Simplified Downlin Transmission and Receiving Scheme for IDMA 71 introduce asymmetric traffic load between uplin and downlin. TR technique was originally employed in wideband transmission in underwater acoustics [3] and ultrasound [4]. Subsequently, it was introduced to the context of UWB communications [5] to alleviate the problem arising from the large number of multi-path components in UWB channels. In this paper, TR-CIR is not only used to alleviate multi-path components, but also is adopted to alleviate multi-user interference and co-channel interference. Generally, it is efficient to alleviate ISI with TR technique in the transmitter. From the theoretic viewpoint, the performance of TR technique is equivalent in the transmitter or the receiver. However, it is hard to simplify the UE implementation when TR technique is used in the receiver of UE. In TDR-IDMA systems, TR technique is similar to PRE-RAE operation used in CDMA for ISI alleviating. However, they are different in resolution and operation. The resolution of PRE-RAE operation is limited by the period of chips, while TR technique does not has this limitation. The performance of the perfect PRE-RAE transmitter is equivalent to that of TR transmitter. Moreover, the structure of PRE-RAE transmitter is very complex. The major feature of the proposed scheme is exploiting the wea correlation of channel information as well as the spatial and temporal focusing of TR. We use TR-CIR to pre-process the transmitted signal before transmitting to the air. The idea of TR-CIR processing is as follows. We obtain the CIR from channel estimator at base station first, and then use the CIR to obtain the conjugate of TR-CIR. Finally, the conjugate of TR-CIR is used to pre-process the transmitted signal at base station. It is convenient to reduce the ISI, MUI and CCI. This is feasible since the CIR for deferent channels is wealy correlated, and MISO can increase the diversity gain of TDR-IDMA. The UE can be simplified by canceling the iteration operation. That is, a simple one-finger RAE is used at the receiver. Thus, the desired signal can be detected when we can not obtain the state of the interleavers of other users for a given user. Moreover, TR provides a great deal of privacy and security to mobile users. Let h ( t) be the conjugate of the TR-CIR with CIR h () t and let y() t = h() t h ( t) (1) where denotes the convolution operation. When =, yt () is the autocorrelation of h () t ; otherwise, yt () is the cross-correlation of h () t and h () t for the multi-path of different users. Let ρ = Ehh h h ), where { h are the ( channel coefficients of user, and { h are the conjugates of the TR-CIR coefficients for user. ρ, when the distance between the two UEs is sufficiently large [6]. On the other hand, ρ = 1, when =. 3. Data Transmission and Detection of Traditional Downlin IDMA We assume that the channel is memoryless and has single path to simplify the analysis. The same conclusion can be drawn for the multi-path environments [1]. The received signal of the user can be expressed as r = h x + h x + n, j = 1,,, J () where { n ( j ) are the samples of an additive white Gaussian noise (AWGN) process with variance σ N = N /, and h is the channel coefficient for user. From (), we define the total interfe rence for user as = h x + n, j = 1,,, J (3) ξ The signal detection in the IDMA receiver is performed in the Turbo mode. We assume that { x, are independent, identically distributed (i.i.d.) and BPS is used in this system. From central limitation theorem, ξ can be approximated as Gaussian variable. The information updating procedure is listed as follows. Step 1: Initialization. For the first iteration, let E( x ( j )) =, Var( x ( j )) =1. Step : Information updating at the ESE. j tan h( edec ( x ( j))/ ) j E( x ( )) = (4) Var( x ) = 1 ( E( x ( ))) (5) E( ξ ) = E( r) h E( x ) (6) Var( ξ ) = Var( r) h Var( x ) (7) r E( ξ ) eese ( x) = h, = 1,,, (8) Var( ξ ) Step 3: { e ESE ( x ( j )) is sent to the APP-DEC after de-interleaving, and the { e DEC ( x ( j )) generated by the APP-DEC is sent to the ESE through the interleaving, return to Step for the next iteration. Step 4: At the final iteration, the APP-DEC produces hard decision. The signal detection in the downlin IDMA receiver is performed in the Turbo mode. The Turbo-lie detection can not be performed when we can not obtain the state of the interleavers of other users for a given user. The complexity of the user receiver is very high even if the state of the interleavers of other users can be obtained. Therefore, we propose a simplified downlin transmission and receiving scheme for IDMA systems based on time-division duplexing (TDD) and time-reversal (TR) technique to

4 7 simplify UE design. 3.3 Data Transmission and Detection of Downlin TDR-IDMA A. Algorithm Detection in Single-Path Channel with SISO Firstly, we assume that the channel is memoryless and has single path to simplify the analysis. The same conclusion can be drawn for the multi-path environments. The received signal for user can be expressed as r( j) = hhx + hh x + n (9) JOURNAL OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA, VOL. 6, NO. 3, SEPTEM 8 where { n are the samples of an AWGN process with varianceσ N. Without loss of generality, (9) can be approximated by ρ h h x h h x in ( j ) when is moderately great. For ( j ), we express the total multi-user interference r and noise as ξ We can rewrite (9) as = ρ h ( ) ( ), 1,,, h x j + n j j = J (1) ξ = h x + (11) Assume that { x, are i.i.d. random variables. Based r on the central limit theorem, ξ in (11) can be approximated by a white Gaussian random variable. We only use a simple detector to detect the desired signal, since ρ, the MUI can be alleviated substantially and the desired signal is enhanced. ρ means the fading channel of different UEs is wealy correlated, this is true when the distance between different UEs is sufficiently far [6]. Therefore, an inherent metric that can be used to quantify the capability of TR to alleviate the multi-user interference is the SINR. Higher SINR value means a better alleviating, and the desired signal can be easily detected. h SINR = (1) ρ h h + σ We have discussed the single path so far. From (1) we can see that the wea correlations of fading channels for different UEs can be used to alleviate the MUI. However, the spatial and temporal focusing of TR technique is the intrinsic feature, it is better to realize with MISO [5]. In the following, we will analyze the downlin IDMA system with TR-MISO. B. Algorithm Detection in Multi-Path Channel with MISO In the TR-MISO system, due to the temporal focusing effect, it is expected that synchronization to the received signal (at the correlation pea where it contains most of the energy) would be accomplished easier. The receiver can use a simple one-finger RAE tuned to the major signal pea, thus allowing very simple and low cost receivers. We consider a quasi-static multi-path channel with L tap coefficients, T transmitter antennas and one receiver antenna. users transmit data simultaneously. Let { 1 L t,, h, t,, h t, be the fading coefficients for us er at, the tth transmitte r antenna. Let = ( l l l l t, ), t t, t E h h h h,, and ρ ll,,,, 1,1 = 1, = L = ll, ρ ρ ρ = ρ < 1, where or =, l l, After TR preprocessing, the received signal for user can be expressed as T L 1 l h x ξ ( t, j), j = 1,,, J t= 1 l= T L 1 L 1 m n h, th, t x( j ( m n)) t= 1m= n= m n T L 1 L 1 m n + t,, t + t= 1m= n= r = + ξ = (13) h h x ( j ( m n)) n (14) where ξ is the total interference, including the ISI and MUI, the CCI is not considered in this equation, { n ( j ) are the samples of an AWGN process with varianceσ. N The ISI and MUI are alleviated simultaneously by the wea correlations of fading channels for different UEs and the wea correlations of multi-path components for one UE. The desired signal is enhanced by TR. These are so called as the spatial and temporal focusing of TR technique. Thus, the receiver can use a simple one-finger RAE tuned to the major signal pea. Certainly, TR preprocessing brings on undesired multi-path components, but these components are very wea, the undesired multi-path components can be omitted. 4. Numerical Results and Discussions We consider a simple system model similar to that in [1]. Each user s information data is encoded by a rate-1/16 repeat code. The resultant signals are interleaved by randomly generated interleavers, and transmitted over a single path channel and multi-path channels respectively, with BPS modulation. Let N info =14 be the number of information bits in a frame, be the number of simultaneous users in the system, T be the number of antennas of transmitter and ρ be the correlation for the different fading channels. The bit error rate () performance of downlin TDR-IDMA system with different ρ in single path channel is shown in Fig. 3. From the figure we can see that the performance of the TDR-IDMA for 16 wealy correlated users is close to that of the single-user system when ρ=.1. According to Fig. 3, we also learn that the MUI can be alleviated substantially and the desired signal is enhanced when ρ. Certainly, the performance of TDR-IDMA will degrade when ρ 1. In the worst case, ρ=1, TDR-IDMA reduces to IDMA. Fig. 4 shows the performance of downlin TDR-IDMA system with different ρ in multi-path channel. According to Fig. 3 and Fig. 4, we learn that the correlation of different fading

5 XIONG et al.: A Simplified Downlin Transmission and Receiving Scheme for IDMA 73 channels does affect the performance of TDR-IDMA significantly when ρ ρ=.8 p=. 8 ρ=.5 p= ρ=.3 p=.3 ρ=. p=. ρ=.1 p=.1 single single user user Eb/No (db) 5. Conclusions We have proposed a simplified downlin transmission and receiving scheme for IDMA systems based on TDD and TR technique, namely, TDR-IDMA. The TDR-IDMA system has many advantages, e.g., mitigation of the MUI, ISI and CCI. Moreover, by canceling the iterative detection with the TR and MISO technologies, the UEs can be simplified. The proposed Downlin TDR-IDMA scheme provides a great deal of privacy and security to mobile users, due to the state of other users interleavers is not necessary. Thus, it is convenient to simplify the user end. On the other hand, it is also beneficial to simplify the UE by moving the channel estimator from the receiver of UE to the receiver of the base station. References E b /N o (db) Fig. 3. Figure performance 3 comparison of of downlin TDR-IDMA TDR-IDMA with different ρ in channel, =16 with different ρ in single path channel, =16. [1] P. Li, L.-H. Liu,.-Y. Wu, and W.-. Leung, Interleave-division multiple-access, IEEE Transactions on The performance of downlin TDR-IDMA system Wireless Communication, vol. 5, no. 4, pp , 6. with different T in multi-path is shown in Fig. 5. Assume it [] P. Li, P. Wang, and X.-D. Wang, Recent progress in is a quasi-static multi-path ρ =., N info =14. From Fig. 5 we Military Communication Conference (MILCOM), Orlando, channel with L tap coefficients, interleave-division multiple-access (IDMA), in Proc. where =4, L=3, can see that TDR-IDMA can achieve better Florida, USA, pp. 1-7, Oct. 9-31, 7. performance when T is large. Moreover, the diversity gain [3] D. Rouseff, D. R. Jacson, W. L. J. Fox, C. D. Jones, J. A. of TDR-IDMA is achieved by TR technique and MISO. Ritcey, and D. R. Dowling, Underwater acoustic communication by passive-phase conjugation: Theory and 1-1 experimental results, IEEE J. Ocean. Eng., vol. 6, no. 4, pp , ρ=. p=. ρ=.3 p=.3 ρ=.5 p= Eb/No (db) E b /N o (db) Fig. 4. Figure 4 performance comparison of downlin of downlin TDR-IDMA TDR-IDMA with L=3, =4 with antennas, L=3 = T=1 T=1 T= T= T=3 T=3 T=4 T= E b /NEb/No o (db) Figure 5 performance comparison of downlin TDR-IDMA with different configure antennas, L=3, =4, ρ =. Fig. 5. performance comparison of downlin TDR-IDMA with different configure antennas, L=3, =4, ρ=. [4] M. Fin, Time reversal of ultrasonic fields-part I: Basic principles, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, vol. 39, no. 5, pp , 199. [5] R. C. Qiu, C.-M. Zhou, N. Guo, and J. Q. Zhang, Time reversal With MISO for ultrawideband communications: Experimental results, IEEE Antennas and Wireless Propagation letters, vol. 5, pp , 6. [6] B. Vucetic and J. Yua, Space-Time Coding, England: John Wiley & Sons Ltd. Publish, 3. Xing-Zhong Xiong was born in Sichuan Province, China, in He received the B.S. degree in electronic engineering from Sichuan University of Science & Engineering, Sichuan, China, in 1996 and the M.S. degree in signal and information processing from University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 6. He is currently woring towards the Ph.D. degree with UESTC. His research interests include signal processing and multiple access techniques in communication systems. Jian-Hao Hu was born in Yunnan Province, China, in He received the Ph.D. degree in communications from UESTC, Chengdu, China, in From 1999 to, he was a postdoctoral with City University of Hong ong, and researched on mobile communication systems. From to 4, he joined University of Hong ong, Hong ong, where he is currently woring on CDMA system development in the university s 3G research center. Since 5, he joined the National ey Lab. Communication of UESTC, as a professor. His research interests include wireless communication and VLSI.