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A Novel Pilot Decontamination Method for Massive MIMO Systems Using Social Spider Optimization Algorithm

机译:基于社交蜘蛛优化算法的大规模MIMO系统导频去污新方法

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摘要

The promising capacity and data rate brought by massive MIMO communication systems lead to consider it as a very prominent fifth generation mobile technology. Pilot contamination is identified as the most significant impairment that limits the exploitation of its optimum capacity. It is caused by the re-use of the same, or at least non-orthogonal pilot sequences, among different cells that degrade the performance of channel estimation. In order to mitigate this issue, we propose a partial re-use of pilot sequences among users in the adjacent cells, which are close to the base station (BS) and also possesses minimum movement velocity. A novel multi factor social spider optimization algorithm (MSSOA), which imitates the cooperative behavior of social spiders, is used for selecting the eligible users for this pilot reuse in the neighboring cells. The algorithm tries to maximize the lowest SINR value for every user in the cell. The performance of the proposed method is evaluated through simulations and it is confirmed that the proposed method gives a better bit error rate (BER), sum-rate, and normalized mean square error (NMSE), over the conventional pilot assignment schemes.
机译:大规模MIMO通信系统带来的有希望的容量和数据速率使它被视为非常杰出的第五代移动技术。飞行员污染被认为是最严重的损害,限制了其最佳产能的利用。这是由于在不同小区之间重用相同或至少非正交的导频序列而导致信道估计性能下降。为了减轻这个问题,我们建议在邻近小区的用户中部分重用导频序列,这些小区靠近基站(BS)并且拥有最小的移动速度。一种模仿社交蜘蛛协作行为的新颖的多因素社交蜘蛛优化算法(MSSOA)用于选择合格用户,以便在相邻小区中进行该飞行员重用。该算法尝试使小区中每个用户的最低SINR值最大化。通过仿真评估了该方法的性能,并证实了该方法与常规导频分配方案相比具有更好的误码率(BER),总和率和归一化均方误差(NMSE)。

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