Optimal Rate-Diverse Wireless Network Coding

TL;DR

This paper introduces a capacity-achieving wireless network coding framework for two-user broadcast channels with different link qualities, utilizing nested lattice codes and practical implementations like LDLC and BICM.

Contribution

It proposes a novel capacity-achieving framework based on nested lattice codes and a general design principle for rate-diverse wireless network coding.

Findings

Framework achieves theoretical capacity for rate-diverse channels.

Practical implementations with LDLC and BICM demonstrate performance gains.

Framework offers a new design principle for linear wireless network coding.

Abstract

This paper proposes an encoding/decoding framework for achieving the optimal channel capacities of the two-user broadcast channel where each user (receiver) has the message targeted for the other user (receiver) as side information. Since the link qualities of the channels from the base station to the two users are different, their respective single-user non-broadcast channel capacities are also different. A goal is to simultaneously achieve/approach the single-user non-broadcast channel capacities of the two users with a single broadcast transmission by applying network coding. This is referred to as the \emph{rate-diverse wireless network coding} problem. For this problem, this paper presents a capacity-achieving framework based on linear- structured nested lattice codes. The significance of the proposed framework, besides its theoretical optimality, is that it suggests a general design principle for linear rate-diverse wireless network coding going beyond the use of lattice codes. We refer to this design principle as the \emph{principle of virtual single-user channels}. Guided by this design principle, we propose two implementations of our encoding/decoding framework using practical linear codes amenable to decoding with affordable complexities: the first implementation is based on Low Density Lattice Codes (LDLC) and the second implementation is based on Bit-interleaved Coded Modulation (BICM). These two implementations demonstrate the validity and performance advantage of our framework.