Jul 2026· International Journal of Electronics and Telecommunications· Vol 72, pp. 1-7· 0 citations
TL;DR
This paper proposes a novel, scalable receiver scheme: the Quantization-Aware Partial MMSE (QA-P-MMSE) receiver, which significantly outperforms other scalable schemes, such as Maximum-Ratio (MR) and Partial-MMSE (P-MMSE), in terms of both average spectral efficiency and user fairness.
Abstract
Cell-free Massive MIMO systems promise unprecedented spectral efficiency by coherently serving users with a large number of distributed Access Points (APs). A key practical challenge, however, is the high capacity required for the fronthaul links connecting these APs to a central processing unit. To reduce cost and power, these links must employ low-resolution quantization, which introduces distortion that can severely degrade system performance. This paper tackles this problem by proposing a novel, scalable receiver scheme: the Quantization-Aware Partial MMSE (QA-P-MMSE) receiver. Unlike conventional methods that either ignore quantization effects or require non-scalable centralized processing, our proposed receiver explicitly incorporates the statistics of the quantization noise into its design. We demonstrate through simulations that the QA-P-MMSE receiver significantly outperforms other scalable schemes, such as Maximum-Ratio (MR) and Partial-MMSE (P-MMSE), in terms of both average spectral efficiency and user fairness. Crucially, it approaches the performance of an ideal, non-scalable MMSE receiver with unquantized fronthaul, proving its efficacy as a practical and high-performance solution for next-generation cellfree networks. Furthermore, energy efficiency analysis reveals that the proposed scheme maximizes bits-per-joule performance at 4-bit resolution, aligning with green 6G targets.
This paper proposes a novel, scalable receiver scheme: the Quantization-Aware Partial MMSE (QA-P-MMSE) receiver, which significantly outperforms other scalable schemes, such as Maximum-Ratio (MR) and Partial-MMSE (P-MMSE), in terms of both average spectral efficiency and user fairness.
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