Nested Lattice Codes for Gaussian Relay Networks with Interference

TL;DR

This paper introduces a lattice coding scheme for Gaussian relay networks with interference, achieving rates close to the theoretical maximum and extending to finite-field networks with a linear coding approach.

Contribution

It presents a structured lattice coding scheme for Gaussian relay networks with interference, achieving near-capacity rates and extending the approach to finite-field networks.

Findings

Achievable rate within a constant gap of the cut-set bound.

Structured lattice coding outperforms random coding in this context.

Capacity characterization for finite-field networks with interference.

Abstract

In this paper, a class of relay networks is considered. We assume that, at a node, outgoing channels to its neighbors are orthogonal, while incoming signals from neighbors can interfere with each other. We are interested in the multicast capacity of these networks. As a subclass, we first focus on Gaussian relay networks with interference and find an achievable rate using a lattice coding scheme. It is shown that there is a constant gap between our achievable rate and the information theoretic cut-set bound. This is similar to the recent result by Avestimehr, Diggavi, and Tse, who showed such an approximate characterization of the capacity of general Gaussian relay networks. However, our achievability uses a structured code instead of a random one. Using the same idea used in the Gaussian case, we also consider linear finite-field symmetric networks with interference and characterize the capacity using a linear coding scheme.