5 research outputs found

    Combined Semi-definite Relaxation and Sphere Decoding Method for Multiple Antennas Systems

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    In this paper, a new detection method which combines the semi-definite programming relaxation (SDR) with the sphere decoding (SD) is proposed for 256-QAM multiple-input multiple-output (MIMO) system. In this method, the SDR algorithms are engaged to obtain a primary result. Then, a hyper-sphere is constructed which is centered at the received signal and has its radius equals to the Euclidean distance between the primary result and the received signal. Finally, the SD searching strategy is employed to determine the final result which satisfies the principle of maximum likelihood. Simulation results show that the proposed method can offer optimum BLER performance as well as lower computational complexity than the conventional SD detectors. © 2011 IEEE.published_or_final_versio

    MIMO Detection for High-Order QAM Based on a Gaussian Tree Approximation

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    This paper proposes a new detection algorithm for MIMO communication systems employing high order QAM constellations. The factor graph that corresponds to this problem is very loopy; in fact, it is a complete graph. Hence, a straightforward application of the Belief Propagation (BP) algorithm yields very poor results. Our algorithm is based on an optimal tree approximation of the Gaussian density of the unconstrained linear system. The finite-set constraint is then applied to obtain a loop-free discrete distribution. It is shown that even though the approximation is not directly applied to the exact discrete distribution, applying the BP algorithm to the loop-free factor graph outperforms current methods in terms of both performance and complexity. The improved performance of the proposed algorithm is demonstrated on the problem of MIMO detection
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