Spectral Efficiency in Large-Scale MIMO-OFDM Systems with Per-Antenna Power Cost

TL;DR

This paper proposes an efficient resource allocation algorithm for large-scale MIMO-OFDM systems that maximizes capacity while considering power costs of antennas and circuitry, revealing a capacity-antenna trade-off.

Contribution

It introduces a novel iterative resource allocation method that accounts for power costs and derives closed-form policies, improving system capacity in large MIMO-OFDM networks.

Findings

The algorithm achieves near-optimal performance in few iterations.

Activating all antennas may reduce overall system capacity due to power costs.

Trade-off exists between the number of active antennas and system capacity.

Abstract

In this paper, resource allocation for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) downlink networks with large numbers of base station antennas is studied. Assuming perfect channel state information at the transmitter, the resource allocation algorithm design is modeled as a non-convex optimization problem which takes into account the joint power consumption of the power amplifiers, antenna unit, and signal processing circuit unit. Subsequently, by exploiting the law of large numbers and dual decomposition, an efficient suboptimal iterative resource allocation algorithm is proposed for maximization of the system capacity (bit/s). In particular, closed-form power allocation and antenna allocation policies are derived in each iteration. Simulation results illustrate that the proposed iterative resource allocation algorithm achieves a close-to-optimal performance in a small number of iterations and unveil a trade-off between system capacity and the number of activated antennas: Activating all antennas may not be a good solution for system capacity maximization when a system with a per antenna power cost is considered.