Block-QAOA-Aware Detection with Parameter Transfer for Large-Scale MIMO
Shuai Zeng

TL;DR
This paper introduces a Block-QAOA-Aware MIMO detection framework that reorganizes the detection process for compatibility with limited quantum resources, utilizing parameter transfer QAOA to achieve near-optimal performance in large-scale MIMO systems.
Contribution
It proposes a novel blockwise detection method combining QAOA with parameter transfer, enabling scalable quantum-inspired detection for large MIMO systems.
Findings
Regularized blockwise detector outperforms unregularized version.
Parameter-transfer QAOA nearly matches exhaustive reference performance.
QAOA-based detector outperforms direct-training QAOA in BER from medium SNR onward.
Abstract
Large-scale MIMO detection remains challenging because exact or near-maximum-likelihood search is difficult to scale, while available quantum resources are insufficient for directly solving full-size detection instances by QAOA. This paper therefore proposes a Block-QAOA-Aware MIMO Detector (BQA-MD), whose primary purpose is to reorganize the detection chain so that it becomes compatible with limited-qubit local quantum subproblems. Specifically, BQA-MD combines block-QAOA-aware preprocessing in the QR domain, a standards-consistent blockwise 5G NR Gray-HUBO interface, an MMSE-induced dynamic regularized blockwise objective, and K-best candidate propagation. Within this framework, fixed-size block construction gives every local subproblem a uniform circuit width and parameter dimension, which in turn enables parameter-transfer QAOA as a practical realization strategy for structurally…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Optical Network Technologies
