Distributed universally optimal strategies for interference channels with partial message passing
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Cross-layer optimization for wireless networks with deterministic channel models
INFOCOM'10 Proceedings of the 29th conference on Information communications
Feedback via message passing in interference channels
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Asymmetric multilevel diversity coding and asymmetric Gaussian multiple descriptions
IEEE Transactions on Information Theory
Multicommodity flows and cuts in polymatroidal networks
Proceedings of the 3rd Innovations in Theoretical Computer Science Conference
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Bounded-contention coding for wireless networks in the high SNR regime
DISC'12 Proceedings of the 26th international conference on Distributed Computing
Buffer-aware network coding for wireless networks
IEEE/ACM Transactions on Networking (TON)
Quantize-map-forward (QMF) relaying: an experimental study
Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing
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In a wireless network with a single source and a single destination and an arbitrary number of relay nodes, what is the maximum rate of information flow achievable? We make progress on this long standing problem through a two-step approach. First, we propose a deterministic channel model which captures the key wireless properties of signal strength, broadcast and superposition. We obtain an exact characterization of the capacity of a network with nodes connected by such deterministic channels. This result is a natural generalization of the celebrated max-flow min-cut theorem for wired networks. Second, we use the insights obtained from the deterministic analysis to design a new quantize-map-and-forward scheme for Gaussian networks. In this scheme, each relay quantizes the received signal at the noise level and maps it to a random Gaussian codeword for forwarding, and the final destination decodes the source's message based on the received signal. We show that, in contrast to existing schemes, this scheme can achieve the cut-set upper bound to within a gap which is independent of the channel parameters. In the case of the relay channel with a single relay as well as the two-relay Gaussian diamond network, the gap is 1 bit/s/Hz. Moreover, the scheme is universal in the sense that the relays need no knowledge of the values of the channel parameters to (approximately) achieve the rate supportable by the network. We also present extensions of the results to multicast networks, half-duplex networks, and ergodic networks.