Quantum-inspired Beamforming Optimization for Quantized Phase-only Massive MIMO Arrays

TL;DR

This paper presents a quantum-inspired optimization approach using the simulated bifurcation algorithm for beamforming in quantized phase MIMO arrays, outperforming traditional methods in convergence speed and solution quality.

Contribution

Introduces a novel quantum-inspired beamforming optimization method leveraging the SB algorithm and encoding techniques for high-bit phase quantization in MIMO arrays.

Findings

SB optimizer outperforms traditional schemes in speed and quality

Effective handling of sidelobe suppression and nulls in beamforming

Potential for advancing next-generation wireless MIMO techniques

Abstract

This paper introduces an innovative quantum-inspired method for beamforming (BF) optimization in multiple-input multiple-output (MIMO) arrays. The method leverages the simulated bifurcation (SB) algorithm to address the complex combinatorial optimization problem due to the quantized phase configuration. We propose novel encoding techniques for high-bit phase quantization, which are then mapped into Ising spins. This enables efficient construction of the Hamiltonians and subsequent optimization of BF patterns. The results clearly demonstrate that the SB optimizer surpasses traditional schemes such as digital BF, holographic algorithms and genetic algorithms, offering faster convergence and higher solution quality. The impressive capability of the SB optimizer to handle complex BF scenarios, including sidelobe suppression and multiple beams with nulls, is undoubtedly demonstrated through several application cases. These findings strongly suggest that quantum-inspired methods have great potential to advance MIMO techniques in next-generation wireless communication.