Sum-rate Maximizing in Downlink Massive MIMO Systems with Circuit Power Consumption

TL;DR

This paper investigates the impact of circuit power consumption on sum-rate maximization in massive MIMO downlink systems, proposing an optimal RF chain activation strategy and a greedy antenna selection algorithm to improve energy efficiency.

Contribution

It introduces a circuit power consumption model and derives an analytical method to optimize RF chain activation for maximum sum-rate in massive MIMO systems.

Findings

Optimal number of RF chains maximizes sum-rate considering circuit power

Greedy algorithm approaches the optimal performance in antenna selection

Trade-off between RF power consumption and transmitted power is effectively managed

Abstract

The downlink of a single cell base station (BS) equipped with large-scale multiple-input multiple-output (MIMO) system is investigated in this paper. As the number of antennas at the base station becomes large, the power consumed at the RF chains cannot be anymore neglected. So, a circuit power consumption model is introduced in this work. It involves that the maximal sum-rate is not obtained when activating all the available RF chains. Hence, the aim of this work is to find the optimal number of activated RF chains that maximizes the sum-rate. Computing the optimal number of activated RF chains must be accompanied by an adequate antenna selection strategy. First, we derive analytically the optimal number of RF chains to be activated so that the average sum-rate is maximized under received equal power. Then, we propose an efficient greedy algorithm to select the sub-optimal set of RF chains to be activated with regards to the system sum-rate. It allows finding the balance between the power consumed at the RF chains and the transmitted power. The performance of the proposed algorithm is compared with the optimal performance given by brute force search (BFS) antenna selection. Simulations allow to compare the performance given by greedy, optimal and random antenna selection algorithms.