Randomized Iterative Methods for Low-Complexity Large-Scale MIMO Detection

Wang, Zheng; Gower, Robert M.; Xia, Yili; He, Lanxin; Huang, Yongming

doi:10.1109/tsp.2022.3180552

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Fast-converging Initial Solution1

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Cited by 9 publications

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“…In addition, taking advantage of the channel hardening property of massive MIMO systems, D −1 converges asymptotically to a deterministic diagonal matrix 1 B × I [17].…”

Section: Fast-converging Initial Solutionmentioning

confidence: 99%

An Efficient Signal Detection Method Based on Enhanced Quasi-Newton Iteration for Massive MIMO Systems

Guo

Wang

Guan

et al. 2024

IEICE Trans. Fundamentals

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This letter provides an efficient massive multiple-input multiple-output (MIMO) detector based on quasi-newton methods to speed up the convergence performance under realistic scenarios, such as high user load and spatially correlated channels. The proposed method leverages the information of the Hessian matrix by merging Barzilai-Borwein method and Limited Memory-BFGS method. In addition, an efficient initial solution based on constellation mapping is proposed. The simulation results demonstrate that the proposed method diminishes performance loss to 0.7dB at the bit-error-rate of 10 −2 at 128×32 antenna configuration with low complexity, which surpasses the state-of-the-art (SOTA) algorithms.

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“…In addition, taking advantage of the channel hardening property of massive MIMO systems, D −1 converges asymptotically to a deterministic diagonal matrix 1 B × I [17].…”

Section: Fast-converging Initial Solutionmentioning

confidence: 99%