A New Energy Efficient Beamforming Strategy for MISO Interfering Broadcast Channels based on Large Systems Analysis

TL;DR

This paper introduces a low-complexity, energy-efficient beamforming strategy for MISO interfering broadcast channels, leveraging large system analysis to optimize performance with reduced computational overhead.

Contribution

It proposes a novel beamforming design based on asymptotic analysis that simplifies computation by relying on second-order channel statistics, applicable to large systems.

Findings

Significant reduction in computational complexity.

Performance close to conventional methods in small systems.

Insights into average energy efficiency in large systems.

Abstract

In this paper, we propose a new beamforming design to maximize energy efficiency (EE) for multiple input single output interfering broadcast channels (IFBC). Under this model, the EE problem is non-convex in general due to the coupled interference and its fractional form, and thus it is difficult to solve the problem. Conventional algorithms which address this problem have adopted an iterative method for each channel realization, which requires high computational complexity. In order to reduce the computational complexity, we parameterize the beamforming vector by scalar parameters related to beam direction and power. Then, by employing asymptotic results of random matrix theory with this parametrization, we identify the optimal parameters to maximize the EE in the large system limit assuming that the number of transmit antennas and users are large with a fixed ratio. In the asymptotic regime, our solutions depend only on the second order channel statistics, which yields significantly reduced computational complexity and system overhead compared to the conventional approaches. Hence, the beamforming vector to maximize the EE performance can be determined with local channel state information and the optimized parameters. Based on the asymptotic results, the proposed scheme can provide insights on the average EE performance, and a simple yet efficient beamforming strategy is introduced for the finite system case. Numerical results confirm that the proposed scheme shows a negligible performance loss compared to the best result achieved by the conventional approaches even with small system dimensions, with much reduced system complexity.