Message passing in distributed wireless networks
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
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
Interference networks with local view: a distributed optimization approach
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Outer bounds on the capacity of Gaussian interference channels
IEEE Transactions on Information Theory
Gaussian Interference Channel Capacity to Within One Bit
IEEE Transactions on Information Theory
Wireless Network Information Flow: A Deterministic Approach
IEEE Transactions on Information Theory
Sum Capacity of Interference Channels With a Local View: Impact of Distributed Decisions
IEEE Transactions on Information Theory
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In distributed wireless networks, nodes often do not know the topology (network size, connectivity and the channel gains) of the network. Thus, they have to compute their transmission and reception parameters in a distributed fashion. In this paper, we consider the information required at the nodes to achieve globally optimal sum capacity. Our first result relates to the case when each of the transmitter know the channel gains of all the links that are at-most two-hop distant from it and the receiver knows the channel gains of all the links that are three-hop distant from it in a deterministic interference channel. With this limited information, we find that distributed decisions are sum-rate optimal only if each connected component is in a one-to-many configuration or a fully-connected configuration. In all other cases of network connectivity, the loss can be arbitrarily large. We then extend the result to see that O(K) hops of information are needed in general to achieve globally optimal solutions. To show this we consider a class of symmetric interference channel chain and find that in certain cases of channel gains, the knowledge of a particular user being odd user or even user is important thus needing O(K) hops of information at the nodes.