Distributed Universally Optimal Strategies for Interference Channels with Partial Message Passing

TL;DR

This paper develops distributed strategies for interference channels with partial message passing, achieving optimal sum capacity in certain network configurations despite limited network information.

Contribution

It introduces conditions under which distributed strategies with partial information can match centralized sum capacity in interference channels.

Findings

Distributed strategies are sum-rate optimal in one-to-many or fully-connected configurations.

In other network configurations, the capacity loss can be arbitrarily large.

Limited local information suffices for optimality in specific network topologies.

Abstract

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 that 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 a condition on the network connectivity for which there exist a distributed strategy that can be chosen by the users with partial information about the network state, which achieves the same sum capacity as that achievable by the centralized server that knows all the channel gains. Specifically, 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.