Joint channel decoding with feedback power control in sensor networks with correlated sources
ISWCS'09 Proceedings of the 6th international conference on Symposium on Wireless Communication Systems
An improved amplify-and-forward strategy for user cooperation channels
ISCIT'09 Proceedings of the 9th international conference on Communications and information technologies
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
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The multiple-access channel with feedback and correlated sources (MACFCS) models a sensor network in which sensors collect and transmit correlated data to a common sink. We present four achievable rate regions and a capacity outer bound for the MACFCS. For the first achievable region, we construct a decode-forward based coding strategy. The sources first exchange their data, and then cooperate to send full information to the destination. We term this strategy full decoding at sources with decode-forward (FDS-DF). For two of the other achievable regions, we first perform Slepian-Wolf coding to remove the correlation among the source data. This is followed by either (i) a compress-forward based coding strategy for the multiple-access channel with feedback, or (ii) an existing coding strategy for the multiple-access channel. We also find another achievable region using a multihop coding strategy, which only uses point-to-point coding (no cooperation). From numerical computations, we see that different strategies perform better under certain source correlation structures and network topologies. More specifically, FDS-DF approaches the capacity when (i) the inter-source distance decreases, or (ii) the correlation among the sources gets higher. Furthermore, the cooperative coding strategies considered support larger achievable rate regions than the noncooperative multihop strategy.