Robust Successive Compute-and-Forward over Multi-User Multi-Relay Networks

TL;DR

This paper introduces two novel Compute-and-Forward schemes, extended and successive CMF, to improve multi-user multi-relay networks by addressing rank failure and enhancing performance with low complexity and robustness.

Contribution

The paper proposes two new CMF methods, extended and successive, that solve rank failure issues and improve network diversity and robustness with low complexity.

Findings

Successive CMF outperforms conventional schemes in SNR gains.

Both methods achieve full network diversity.

Successive CMF shows robustness against channel estimation errors.

Abstract

This paper develops efficient Compute-and-forward (CMF) schemes in multi-user multi-relay networks. To solve the rank failure problem in CMF setups and to achieve full diversity of the network, we introduce two novel CMF methods, namely, extended CMF and successive CMF. The former, having low complexity, is based on recovering multiple equations at relays. The latter utilizes successive interference cancellation (SIC) to enhance the system performance compared to the state-of-the-art schemes. Both methods can be utilized in a network with different number of users, relays, and relay antennas, with negligible feedback channels or signaling overhead. We derive new concise formulations and explicit framework for the successive CMF method as well as an approach to reduce its computational complexity. Our theoretical analysis and computer simulations demonstrate the superior performance of our proposed CMF methods over the conventional schemes. Furthermore, based on our simulation results, the successive CMF method yields additional signal-to-noise ratio gains and shows considerable robustness against channel estimation error, compared to the extended CMF method.