Efficient Massive MIMO Detection for M-QAM Symbols

Article Engineering, Electrical & Electronic

Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems

Salah Berra et al.

Summary: The proposed Chebyshev acceleration technique overcomes the limitations of iterative methods in a massive MIMO system, accelerating convergence rates and enhancing performance. This method utilizes a new vector combination, incorporating the spectral radius of the iteration matrix and the receiver signal, with defined optimal parameters for Chebyshev acceleration.

ELECTRONICS LETTERS (2022)

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Article Engineering, Electrical & Electronic

Improved Gauss-Seidel detector for large-scale MIMO systems

Imran A. Khoso et al.

Summary: The paper proposes an efficient iterative detection algorithm based on improved Gauss-Seidel iteration, achieving better performance with one conjugate gradient iteration. A new hybrid iteration and low-complexity initial estimation are introduced to enhance detection accuracy while reducing complexity. Additionally, a novel preconditioning technique is proposed to maintain the benefits of the proposed detector in correlated MIMO channels, showing faster convergence rate compared to conventional methods.

IET COMMUNICATIONS (2022)

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Article Engineering, Electrical & Electronic

Low-Complexity Implicit Detection for Massive MIMO Using Neumann Series

Xiaohui Zhang et al.

Summary: In this paper, a low-complexity MIMO detection method based on the Neumann series is proposed, which reduces the computational complexity of signal detection by leveraging the statistical information of the Gram matrix and transforming matrix operations.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2022)

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Article Engineering, Electrical & Electronic

Efficient Soft-Output Gauss-Seidel Data Detector for Massive MIMO Systems

Chuan Zhang et al.

Summary: This paper proposes an efficient GS-based soft-output data detector and corresponding VLSI architecture for massive MIMO systems, achieving throughput of 732 Mb/s with close-to-MMSE error-rate performance. Optimization methods are used to reduce processing latency and area on the VLSI architecture level. The proposed solution shows advantages in complexity and efficiency over existing designs, especially under challenging propagation conditions.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS (2021)

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Article Engineering, Electrical & Electronic

Configurable Quasi-Optimal Sphere Decoding for Scalable MIMO Communications

Yun Wu et al.

Summary: The paper introduces a novel configurable Sphere Decoding (SD) approach that reduces complexity while maintaining quasi-ML accuracy, resulting in lower cost accelerators with higher throughput. This new Robust Bounded Spanning with Fast Enumeration (R-BSFE) method significantly improves performance and cost efficiency for MIMO communication systems.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS (2021)

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Article Computer Science, Information Systems

Low Complexity Linear Detectors for Massive MIMO: A Comparative Study

Mahmoud A. Albreem et al.

Summary: This study examines iterative matrix inversion methods in massive MIMO systems, revealing that conjugate gradient and optimized coordinate descent methods offer the lowest complexity and acceptable performance. Additionally, the Gauss-Seidel method outperforms other detectors in complexity increment, with performance not improving with every iteration. Omega is shown to play a significant role in achieving satisfactory performance in both RI and SOR based detectors.

IEEE ACCESS (2021)

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Article Engineering, Electrical & Electronic