1. On the Coded Complex Field Network Coding Scheme for Multiuser Cooperative Communications with Regenerative Relays Caixi 2011-09-26 Key Lab of Information Coding & Transmission Southwest Jiaotong University Chengdu, Sichuan 610031, PR of China

2. Outline Motivation System Model Iterative Multiuser Decoding Structure Simulation Conclusion Reference 2

3. Motivation The network coding technique is an effective approach that can essentially improve network throughput by increasing the bandwidth efficiency of the intermediate nodes in networks. Multiple access relay channel (MARC) can be used for the cooperative uplink from more than two mobile stations to one base station with the help of a relay, where diversity can be achieved by using network coding [1]. 3 [1] G. Kramer and A. J. van Wijngaarden, “ On the White Gaussian Multiple-Access Relay Channel, ” IEEE International Symposium on Information Theory (ISIT), June 2000.

4. Motivation Non-orthogonal MARC attracts research attention due to its higher efficiency. The joint network-channel distributed coding design problem for the non-orthogonal MARC has been addressed in [2-3]. In [2], only a simple relay network with two sources, one relay and one destination is considered. In [3], a distributed serially concatenated coding scheme for a general multi-source wireless relay network is proposed, but the BPSK modulation and one relay are considered. 4 [2] A. Hatefi, R. Visoz, and A.O. Berthet, Joint channel-network turbo coding for the non orthogonal multiple access relay channel, Proc. IEEE PIMRC10, Istanbul, Turkey, Sep. 2010. [3] R.Youssef and A.Graell i Amat, “Distributed Serially Concatenated Codes for Multi-Source Cooperative Relay Networks,” IEEE Transactions on Wireless Communications, pp. 253 – 263, Jan. 2011

5. Motivation Complex field network coding (CFNC) scheme is a promising technique to realize the high throughput by using the linear constellation precoding over complex field at every node with the help of the maximum likelihood detection of the mixing symbols [4]. 5 [4] T. Wang and G. Giannakis, “Complex field network coding for multiuser cooperative communications,” IEEE Journal on Selected Areas in Communications, vol. 26, pp.561–571, Apr. 2008

6. Motivation In the paper, a coded CFNC (C-CFNC) scheme by jointly considering the error control coding and the CFNC scheme is proposed to enhance the achieved network performance. An MAP-based multiuser decoder is utilized to enable an iterative multiuser decoding structure between the soft-decision de- multiplexing and the soft-decision error control decoding at both the relays and the destination. 6

7.  Fully-interleaved Rayleigh fading (fast fading) Link-adaptive regeneration (LAR) relay strategy is proposed in [4]. Completely-known channel state information is required at destination; The more storage and higher computational cost are required. Decode-and-forward (DF) relay strategy is assumed in [3]. The error propagation will decrease the system performance. 7 Motivation

8. In the paper, the selective decode-and-forward (SDF) strategy is employed to counteract the reliability degradation due to the inaccurate recovery at relays and to reduce decoding complexity in the destination with some increase in the communication overhead. In the SDF relay strategy, only active relays which recover successfully at least one source message will transmit the regenerated CFNC signals to the destination. 8 Motivation

9. System Model 9 Fig.1 System Model Perfect CSI at the receivers; Synchronization between the transmitted nodes; One antenna & Working in half-duplex mode SDF strategy

10. 10 System Model Fig.2 Transmitter Model at k-th Source for Coded CFNC System Binary message sequence: Coded sequence: Interleaved sequence: Modulated sequence:, Transmitted sequence:

11. 11 The received signals at m-th relay and destination during the first MAC phase is given, respectively, by System Model

12. 12 System Model Fig.3 Transmitter Model at the m-th relay for Coded CFNC System The CFNC signal at the m-th relay: is an indicator to represent whether or not the recovered message.

13. The received signal at in the second MAC phase is given 13 System Model

14. Iterative Multiuser Decoding Structure 14 Fig.4 Iterative Decoding Structure at the m-th relay for Coded CFNC System [5] X. Wang and HV Poor, “ Iterative (turbo) soft interference cancellation and decoding for coded CDMA, ” IEEE Trans.Commun., vol. 47, pp. 1046 – 1061, July 1999.

15. 15 Iterative Multiuser Decoding Structure The SISO multiuser detector delivers the a posterior log-likelihood ratio (LLR) of a transmitted “ 1 ” and a transmitted “ 0 ” for every coded bit of every user

16. 16 Iterative Multiuser Decoding Structure Fig.5 Iterative decoding structure at destination for coded CFNC system

17. Simulation The symmetric MARC model; All sources and relays use the same convolutional codes Code rate: 1/2 Generator polynomial: (7, 5) The information packet size L=128; Fully-interleaved Rayleigh fading with unit variance; Transmitted power of each node is equal to one. 17

18. 18 Simulation Fig. 6 The reliability of the coded CFNC system with different number of sources with BPSK

19. 19 Simulation Fig. 7 The reliability of the coded CFNC system with different number of relays with BPSK

20. In the paper, the error control coding is utilized in the CFNC scheme to obtain the enhanced coded CFNC scheme with the SDF strategy for multiuser cooperative communications which improves the network performance; The iterative multiuser decoder structure for the coded CFNC scheme is presented. From simulation results, the coded CFNC scheme is able to significantly improve the reliability of the multiuser message delivery in adverse cooperative communication environment; The SDF relay seems an attractive strategy when the relays are close to the source to avoid the error propagation in the DF relay strategy. 20 Conclusion

21. Reference [1] G. Kramer and A. J. van Wijngaarden, “On the White Gaussian Multiple- Access Relay Channel,” IEEE International Symposium on Information Theory (ISIT), June 2000. [2] A. Hatefi, R. Visoz, and A.O. Berthet, Joint channel-network turbo coding forthe non orthogonal multiple access relay channel, Proc. IEEE PIMRC10, Istanbul, Turkey, Sep. 2010. [3] R.Youssef and A.Graell i Amat, “Distributed Serially Concatenated Codes for Multi- Source Cooperative Relay Networks,” IEEE Transactions on Wireless Communications, pp. 253 – 263, Jan. 2011 [4] T. Wang and G. Giannakis, “Complex field network coding for multiuser cooperative communications,” IEEE Journal on Selected Areas in Communications, vol. 26, pp.561– 571, Apr. 2008 [5] X. Wang and HV Poor, “Iterative (turbo) soft interference cancellation and decoding for coded CDMA,” IEEE Trans.Commun., vol. 47, pp. 1046–1061, July 1999. 21

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