本文選題：長期演進 + 下傾角優(yōu)化　； 參考：《計算機應(yīng)用》2017年01期

【摘要】：針對第三代合作伙伴項目(3GPP)中自組織網(wǎng)絡(luò)(SON)的覆蓋與容量自優(yōu)化問題,提出了一種基于粒子群優(yōu)化(PSO)算法的有源天線下傾角優(yōu)化方法。首先,確定基站(eNB)中傳輸數(shù)據(jù)的用戶設(shè)備(UE)數(shù),用戶測量上報鄰小區(qū)參考信號接收功率(RSRP)信息和位置信息;然后,確定優(yōu)化目標(biāo)預(yù)設(shè)適應(yīng)度評價函數(shù)為頻譜效率(SE);其次,將下傾角同時優(yōu)化問題看作是多維優(yōu)化問題,選擇天線下傾角為粒子集合,使用PSO算法求解得到天線下傾角的最優(yōu)值;最后,通過系統(tǒng)自主調(diào)整優(yōu)化下傾角,實現(xiàn)長期演進(LTE)網(wǎng)絡(luò)中容量及覆蓋的自優(yōu)化。通過建模及仿真結(jié)果分析,此算法在優(yōu)化目標(biāo)不同時可以取得不同的優(yōu)化效果:優(yōu)化目標(biāo)為用戶平均頻譜效率時,采用傳統(tǒng)黃金分割優(yōu)化算法頻譜效率較初始設(shè)定提升12.9%,采用PSO算法可提升22.5%;調(diào)整優(yōu)化目標(biāo)為用戶加權(quán)平均頻譜效率時,對邊緣用戶,傳統(tǒng)黃金分割優(yōu)化算法并無明顯提升,PSO算法取得了19.3%的優(yōu)化提升。實驗結(jié)果表明,該方法可提升用戶吞吐量,改善系統(tǒng)性能。
[Abstract]:Aiming at the coverage and capacity self-optimization problem of self-organizing network (SON) in the third generation partner project (3GPP), a new method based on particle swarm optimization (PSO) algorithm is proposed to optimize the dip angle of active antenna. First, determine the number of user equipment (UEE) to transmit data in the base station / eNBs, and the users measure and report the received power and position information of the reference signal in the adjacent cell; then, determine the presupposition fitness evaluation function of the optimized target as spectrum efficiency; secondly, The problem of simultaneous downdip optimization is regarded as a multi-dimensional optimization problem. The dip angle of antenna is selected as particle set, and the optimal value of dip angle is obtained by using PSO algorithm. Finally, the optimal dip angle is adjusted by the system. Self-optimization of capacity and coverage in long-term evolution LTEs is realized. Through modeling and simulation results analysis, the algorithm can achieve different optimization results at the same time when the optimization target is the average spectrum efficiency of the user. The spectral efficiency of the traditional golden section optimization algorithm is increased by 12.9 compared with the initial setting, and that of the PSO algorithm can be improved by 22.5. The traditional golden section optimization algorithm has no significant improvement and the PSO algorithm has achieved 19.3% improvement. The experimental results show that the proposed method can improve the throughput and performance of the system.
【作者單位】： 河海大學(xué)通信與信息系統(tǒng)研究所;
【基金】：中國科學(xué)院上海微系統(tǒng)與信息技術(shù)研究所無線傳感網(wǎng)與通信重點實驗室開放課題資助項目(2016001) 中央高�；究蒲袠I(yè)務(wù)費專項資金資助項目(2015B18914)~~
【分類號】：TN929.5;TP18
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本文編號：1810473