MIMO with 1-bit Pre/Post-Coding Resolution: A Quantum Annealing Approach

TL;DR

This paper introduces a quantum annealing-based iterative algorithm for designing digital pre/post-coding in MIMO systems with 1-bit resolution, achieving near-optimal performance with reduced complexity.

Contribution

It formulates the MIMO coding problem as a QUBO and proposes a QA-based solution along with a novel pre-processing technique to enhance quantum device performance.

Findings

The QA-based algorithm achieves near-optimal performance.

The pre-processing technique improves solution quality and probability.

Experimental validation on D-WAVE demonstrates efficiency.

Abstract

In this paper, we study the problem of digital pre/post-coding design in multiple-input multiple-output (MIMO) systems with 1-bit resolution per complex dimension. The optimal solution that maximizes the received signal-to-noise ratio relies on an NP-hard combinatorial problem that requires exhaustive searching with exponential complexity. By using the principles of alternating optimization and quantum annealing (QA), an iterative QA-based algorithm is proposed that achieves near-optimal performance with polynomial complexity. The algorithm is associated with a rigorous mathematical framework that casts the pre/post-coding vector design to appropriate real-valued quadratic unconstrained binary optimization (QUBO) problems. Experimental results in a state-of-the-art D-WAVE QA device validate the efficiency of the proposed algorithm. To further improve the efficiency of the D-WAVE quantum device, a new pre-processing technique which preserves the quadratic QUBO matrix from the detrimental effects of the Hamiltonian noise through non-linear companding, is proposed. The proposed pre-processing technique significantly improves the quality of the D-WAVE solutions as well as the occurrence probability of the optimal solution.