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In this paper, an improved and low-complexity signal detection approach for large-scale multiple-input multiple-output (MIMO) systems has been proposed. This approach utilizes the preconditioning technique to accelerate the conventional detection algorithm based on Gauss-Seidel (GS) iterative method, and achieves a detection performance close to the minimum mean square error (MMSE) detection algorithm...
In this paper, belief propagation (BP) detection in real domain for large-scale multiple-in multiple-out (MIMO) systems is proposed. The mathematical analysis of message updating rules for independent identically distributed (i.i.d.) and correlated fading MIMO channels are given in detail. The damped BP with damping on the a priori probability vector is employed to improve the performance for the...
Affected by relaxation factor ω, for large-scale MIMO uplink, successive over relaxation (SOR) detection involves low-complexity matrix inversion but unstable performance as ω changes. In this paper, a more stable and efficient SOR-based detection, which is nearly unaffected by ω, is proposed. First, the convergence of the proposed method is proved. Both analytic and numerical results have shown that,...
In this paper, a low-complexity stochastic belief propagation (BP) detector for large-scale MIMO is first proposed. Its efficient hardware architecture, with parallel pipeline, is presented in detail. Thanks to the stochastic approach, all arithmetic operations of the detector are implemented with simple logic structures. Several approaches which can potentially improve the detection performance are...
In this paper, BP detection based on belief propagation in real domain for large-scale MIMO systems is proposed. Numerical results have shown that, with quadrature phase shift keying (QPSK) modulation, this approach can show 1 dB performance improvement at the BER of 10−2, compared to conventional single-edge based BP (SE-BP) in complex domain. Based on the proposed BP detection, its symbol-based...
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