Relay Selection for Low-Complexity Coded Cooperation

This paper explores relay selection and selection diversity for coded cooperation in wireless sensor networks, with complexity constraints for the sensor nodes. In previous work, a relaying scheme based on repeat-accumulate (RA) codes was introduced, where it was assumed that the relay does not perform decoding and simply uses demodulated bits to form codewords. However, in a network setting with multiple potential relays where relays do not decode the source transmission, it is not obvious how to select the best relay. The optimal choice involves finding the best relay possibly using density evolution, but is quite complex and time-consuming. It is shown here that the mutual information of the equivalent relay channel, which is much simpler than using DE, is a good selection heuristic. With surprisingly poor performance when a naive selection scheme is used, the importance of a good relay selection scheme is emphasized.

[1]  Philip Schniter,et al.  On the achievable diversity-multiplexing tradeoff in half-duplex cooperative channels , 2005, IEEE Transactions on Information Theory.

[2]  X. Jin.  Factor graphs and the Sum-Product Algorithm , 2002 .

[3]  Jing Li,et al.  Practical Compress-Forward in User Cooperation: Wyner-Ziv Cooperation , 2006, 2006 IEEE International Symposium on Information Theory.

[4]  Matthew C. Valenti,et al.  Distributed turbo coded diversity for relay channel , 2003 .

[5]  R.S. Adve,et al.  A Practical Scheme for Relaying in Sensor Networks Using Repeat-Accumulate Codes , 2006, 2006 40th Annual Conference on Information Sciences and Systems.

[6]  Raviraj S. Adve,et al.  Low complexity and fractional coded cooperation for wireless networks , 2008, IEEE Transactions on Wireless Communications.

[7]  Robert J. McEliece,et al.  RA Codes Achieve AWGN Channel Capacity , 1999, AAECC.

[8]  Gregory W. Wornell,et al.  Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks , 2003, IEEE Trans. Inf. Theory.

[9]  Abbas El Gamal,et al.  Capacity theorems for the relay channel , 1979, IEEE Trans. Inf. Theory.

[10]  Brendan J. Frey,et al.  Factor graphs and the sum-product algorithm , 2001, IEEE Trans. Inf. Theory.

[11]  Rüdiger L. Urbanke,et al.  The capacity of low-density parity-check codes under message-passing decoding , 2001, IEEE Trans. Inf. Theory.

[12]  Aggelos Bletsas,et al.  A simple Cooperative diversity method based on network path selection , 2005, IEEE Journal on Selected Areas in Communications.

[13]  Raviraj S. Adve,et al.  Cooperative diversity using message passing in wireless sensor networks , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[14]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[15]  Gregory W. Wornell,et al.  An efficient protocol for realizing cooperative diversity in wireless networks , 2001, Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252).

[16]  Abbas El Gamal,et al.  Capacity theorems for relay channels , 1979 .

[17]  Raviraj S. Adve,et al.  Low-Complexity Cooperative Coding for Sensor Networks using Rateless and LDGM Codes , 2006, 2006 IEEE International Conference on Communications.

[18]  Elza Erkip,et al.  User cooperation diversity. Part II. Implementation aspects and performance analysis , 2003, IEEE Trans. Commun..

[19]  R. Adve,et al.  On Selection Cooperation in Distributed Networks , 2006, 2006 40th Annual Conference on Information Sciences and Systems.

[20]  Dariush Divsalar,et al.  Coding theorems for 'turbo-like' codes , 1998 .

[21]  Raviraj S. Adve,et al.  Improving amplify-and-forward relay networks: optimal power allocation versus selection , 2006, IEEE Transactions on Wireless Communications.

[22]  Elza Erkip,et al.  User cooperation diversity. Part I. System description , 2003, IEEE Trans. Commun..

[23]  Aria Nosratinia,et al.  Performance analysis of coded cooperation diversity , 2003, IEEE International Conference on Communications, 2003. ICC '03..