Abstract
A neighborhood-restricted mixed Gibbs sampling (MGS)-based approach is proposed for low-complexity high-order modulation large-scale multiple-input multiple-output (LS-MIMO) detection. The proposed LS-MIMO detector applies a neighborhood limitation (NL) on the noisy solution from the MGS at a distance d — thus, named d-simplified MGS (d-sMGS) — in order to mitigate its impact, which can be harmful when a high-order modulation is considered. Numerical simulation results considering 64-QAM demonstrated that the proposed detection method can substantially improve the MGS algorithm convergence, whereas no extra computational complexity per iteration is required. The proposed d-sMGS-based detector suitable for high-order modulation LS-MIMO further exhibits improved performance × complexity tradeoff when the system loading is high, i.e., when frac {K}{N}geq 0.75. Also, with increasing the number of dimensions, i.e., increasing number of antennas and/or modulation order, a smaller restriction of 2-sMGS was shown to be a more interesting choice than 1-sMGS.
Highlights
In order to meet the demands of high transmission capacity, high reliability, and spectral and energy efficiency requirements of modern wireless communication systems, the multiple input and output (MIMO) technique has been proposed and considered an appropriate solution due to their ability to provide multiplexing and diversity gains without the need for additional spectral features
For the stopping criterion parameters, we have adopted c1 = 10, c2 = 1.0, and cmin = 10 [14]. This numerical simulation section has been divided into two main parts: in Section 6.1, the mixing ratio q and number of samples Le parameters of the Averaged mixed Gibbs sampling (MGS) (aMGS) detector are discussed, as it denotes a technique that aims at reducing the impact of the noisy solution; in Section 6.2, we present numerical results of performance and computational complexity of the proposed d-simplified MGS (d-sMGS) detector against the aMGS and MGS techniques, addressed in this work
7 Conclusions A neighborhood-limited d-sMGS detector for large-scale MIMO systems has been proposed based on the neighborhood constraint of the noisy solution at a distance of d
Summary
In order to meet the demands of high transmission capacity, high reliability, and spectral and energy efficiency requirements of modern wireless communication systems, the multiple input and output (MIMO) technique has been proposed and considered an appropriate solution due to their ability to provide multiplexing and diversity gains without the need for additional spectral features These advantages are further enhanced by large-scale use, called large-scale MIMO (LS-MIMO), which has important application in fifth-generation (5G) wireless communications. (ii) An analysis of the performance × complexity tradeoff is carried out among the proposed d-sMGS, the conventional MGS [10], and the aMGS (averaged MGS) [14], which the latter is an approach that aims to alleviate the impact caused by the random solution, the procedure is based on multiple sampling (MS) strategy, which samples the estimated symbol multiple times and performs a mean operation to obtain the result.
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