基于改進離散布谷鳥搜索算法的毫米波大規模MIMO系統的波束選擇
首發時間:2019-07-25
摘要:在毫米波大規模MIMO系統中采用全數字編碼需要大量的射頻鏈路,從而導致能量損耗過高。針對這一問題,本文提出一種基于離散布谷鳥搜索算法(Discrete Cuckoo Search, DCS)的波束選擇方案,用以減少所需射頻鏈路數而不會造成明顯的性能損失。首先分析毫米波大規模MIMO系統的波束選擇模型,引用DCS算法來求解模型;然后針對布谷鳥算法Levy飛行離散化結果中出現的非正常編碼,采用啟發式貪婪算法進行修復;將遺傳算法中的復制引入DCS算法中,復制全局最優的鳥巢來替換其中被發現的鳥巢,加快算法收斂速度。仿真結果表明,本文所提基于改進離散布谷鳥搜索算法的波束選擇方案相比幾種已有的方案可以獲得更優的和速率性能。
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Beam Selection for Millimeter Wave Massive MIMO Systems via Improved Discrete Cuckoo Search Algorithm
Abstract:The use of full digital coding in millimeter-wave massive MIMO systems requires a large number of radio frequency(RF) chains, resulting in excessive energy consumption.To solve this problem, this paper proposes a beam selection scheme based on Discrete Cuckoo Search (DCS) to reduce the number of required radio-frequency(RF) chains without obvious performance loss.Firstly, the beam selection model of millimeter-wave massive MIMO system is analyzed, and the DCS algorithm is used to solve the model. Owing to the the abnormal coding in the Levy flight discretization result ,the heuristic greedy algorithm is proposed to repair it. To speed up the convergence of the algorithm, the replication in the genetic algorithm is introduced into the DCS algorithm, and the global optimal nest is copied to replace the discovered nests. The simulation result shows that the proposed beam selection scheme based on the improved discrete cuckoo search algorithm can obtain better rate performance than several existing schemes.
Keywords: millimeter wave(mmWave) massive MIMO Discrete Cuckoo Search(DCS) algorithm beam selection
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基于改進離散布谷鳥搜索算法的毫米波大規模MIMO系統的波束選擇
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