Weighted Sum-Throughput Maximization for Energy Harvesting Powered MIMO Multi-Access Channels

TL;DR

This paper introduces a low-complexity optimal scheduling algorithm for energy-harvesting MIMO multi-access channels, maximizing weighted sum-throughput and providing benchmarks for practical schemes.

Contribution

It develops a convex optimization-based approach and an online scheme for optimal transmission in energy-harvesting MIMO MACs, with reduced complexity and causal knowledge requirements.

Findings

The proposed algorithm achieves optimal weighted sum-throughput.

The online scheme performs close to the optimal offline policy.

Numerical results validate the effectiveness of the proposed methods.

Abstract

This paper develops a novel approach to obtaining the optimal scheduling strategy in a multi-input multi-output (MIMO) multi-access channel (MAC), where each transmitter is powered by an individual energy harvesting process. Relying on the state-of-the-art convex optimization tools, the proposed approach provides a low-complexity block coordinate ascent algorithm to obtain the optimal transmission policy that maximizes the weighted sum-throughput for MIMO MAC. The proposed approach can provide the optimal benchmarks for all practical schemes in energy-harvesting powered MIMO MAC transmissions. Based on the revealed structure of the optimal policy, we also propose an efficient online scheme, which requires only causal knowledge of energy arrival realizations. Numerical results are provided to demonstrate the merits of the proposed novel scheme.