In-network Compression for Multiterminal Cascade MIMO Systems

TL;DR

This paper introduces two novel coding schemes for cascade MIMO systems that optimize receive beamforming by leveraging cascade multiterminal source coding, resulting in improved performance over standard routing methods.

Contribution

The paper develops two innovative coding schemes for cascade MIMO systems that enable efficient beamforming through source coding techniques, advancing the state-of-the-art in uplink communication.

Findings

The proposed schemes outperform standard routing in simulations.

Gradual function computation improves beamforming accuracy.

Innovation-based compression reduces data transmission costs.

Abstract

We study the problem of receive beamforming in uplink cascade multiple-input multiple-output (MIMO) systems as an instance of that of cascade multiterminal source coding for lossy function computation. Using this connection, we develop two coding schemes for the second and show that their application leads to beamforming schemes for the first. In the first coding scheme, each terminal in the cascade sends a description of the source that it observes; the decoder reconstructs all sources, lossily, and then computes an estimate of the desired function. This scheme improves upon standard routing in that every terminal only compresses the innovation of its source w.r.t. the descriptions that are sent by the previous terminals in the cascade. In the second scheme, the desired function is computed gradually in the cascade network, and each terminal sends a finer description of it. In the context of uplink cascade MIMO systems, the application of these two schemes leads to centralized receive-beamforming and distributed receive-beamforming, respectively. Numerical results illustrate the performance of the proposed methods and show that they outperform standard routing.