Quantum Annealing for Next-Generation MU-MIMO Detection: Evaluation and Challenges

Juan Carlos De Luna Ducoing, K. Nikitopoulos
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引用次数: 10

Abstract

Multi-user (MU), multiple-input, multiple-output (MIMO) detection has been extensively investigated, and many techniques have been proposed. However, further performance improvements may be constrained by limitations in classical computation. The motivation for this work is to test whether a machine that exploits quantum principles can offer improved performance over conventional detection approaches. This paper presents an evaluation of MIMO detection based on quantum annealing (QA) when run on an actual QA quantum processing unit (QPU) and describes the challenges and potential improvements. The evaluations show promising results in some cases, such as near-optimality in a QPSK-modulated 8×8 MIMO case, but poor results in other cases, such as for larger systems or when using 16-QAM. We show that some challenges of QA detection include dealing with integrated control errors (ICE), the limited dynamic range of QA QPUs, an exponential increase in the number of qubits to the problem size, and a high computation overhead. Solving these challenges could make QA-based detection superior to conventional approaches and bring a new generation of MU-MIMO detection methods.
下一代MU-MIMO检测的量子退火:评估和挑战
多用户(MU)、多输入、多输出(MIMO)检测已经得到了广泛的研究,并提出了许多技术。然而,进一步的性能改进可能受到经典计算的限制。这项工作的动机是测试利用量子原理的机器是否能提供比传统检测方法更好的性能。本文介绍了在实际QA量子处理单元(QPU)上运行的基于量子退火(QA)的MIMO检测的评估,并描述了挑战和潜在的改进。评估在某些情况下显示了有希望的结果,例如qpsk调制8×8 MIMO情况下的接近最优性,但在其他情况下,例如大型系统或使用16-QAM时,结果很差。我们表明,QA检测的一些挑战包括处理集成控制误差(ICE)、QA qpu的有限动态范围、问题大小的量子比特数量呈指数增长以及高计算开销。解决这些挑战可以使基于qa的检测优于传统方法,并带来新一代MU-MIMO检测方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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