Cache-Aided MIMO Communications: DoF Analysis and Transmitter Optimization

TL;DR

This paper analyzes the degrees of freedom and proposes new transmitter schemes for cache-aided MIMO systems, demonstrating how to optimize spatial multiplexing and caching gains under linear processing constraints.

Contribution

It introduces a DoF analysis for cache-aided MIMO with linear processing and proposes a novel scheduling and beamforming scheme to enhance finite-SNR performance.

Findings

Achievable DoF is maximized by tuning the number of users served and streams per user.

A new class of MIMO-CC schemes leveraging multicasting improves delivery rates.

Efficient linear multicast beamformer design enhances practical system performance.

Abstract

Cache-aided MIMO communications aims to jointly exploit both coded caching~(CC) and spatial multiplexing gains to enhance communication efficiency. In this paper, we analyze both the achievable degrees of freedom~(DoF) under linear processing constraint and the finite-SNR performance of a MIMO-CC system with CC gain \(t\), where a server with \(L\) transmit antennas communicates with \(K\) users, each equipped with \(G\) receive antennas. We first demonstrate that the enhanced DoF of \(\max_{\beta, \Omega} \Omega \times \beta\) is achievable with linear processing, where the number of users \(\Omega\) served in each transmission is fine-tuned to maximize DoF, and \(\beta \le \min\big(G, \nicefrac{L \binom{\Omega-1}{t}}{\big(1 + (\Omega - t - 1)\binom{\Omega-1}{t}}\big)\big)\) represents the number of parallel streams decoded by each user. Then, we propose a new class of MIMO-CC schemes using a novel scheduling mechanism leveraging maximal multicasting opportunities to maximize delivery rates at given SNR levels while still adhering to linear processing constraints. This new class of schemes is paired with an efficient linear multicast beamformer design, resulting in a more practical, high-performance solution for integrating CC in future MIMO systems.