Myopic Coding in Multiple Relay Channels

In this paper, we investigate achievable rates for data transmission from sources to sinks through multiple relay networks. We consider myopic coding, a constrained communication strategy in which each node has only a local view of the network, meaning that nodes can only transmit to and decode from neighboring nodes. We compare this with omniscient coding, in which every node has a global view of the network and all nodes can cooperate. Using Gaussian channels as examples, we find that when the nodes transmit at low power, the rates achievable with two-hop myopic coding are as large as that under omniscient coding in a five-node multiple relay channel and close to that under omniscient coding in a six-node multiple relay channel. These results suggest that we may do local coding and cooperation without compromising much on the transmission rate. Practically, myopic coding schemes are more robust to topology changes because encoding and decoding at a node are not affected when there are changes at remote nodes. Furthermore, myopic coding mitigates the high computational complexity and large buffer/memory requirements of omniscient coding.Comment: To appear in the proceedings of the 2005 IEEE International Symposium on Information Theory, Adelaide, Australia, September 4-9, 200

Multiple Access Channels with Generalized Feedback and Confidential Messages

This paper considers the problem of secret communication over a multiple access channel with generalized feedback. Two trusted users send independent confidential messages to an intended receiver, in the presence of a passive eavesdropper. In this setting, an active cooperation between two trusted users is enabled through using channel feedback in order to improve the communication efficiency. Based on rate-splitting and decode-and-forward strategies, achievable secrecy rate regions are derived for both discrete memoryless and Gaussian channels. Results show that channel feedback improves the achievable secrecy rates.Comment: To appear in the Proceedings of the 2007 IEEE Information Theory Workshop on Frontiers in Coding Theory, Lake Tahoe, CA, September 2-6, 200