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  • 學位論文

上行正交分頻多重存取系統載波頻率偏移之估計與補償

Estimation and Compensation of Carrier Frequency Offset for Uplink OFDMA Systems

指導教授 : 譚旦旭
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摘要


正交分頻多工系統(Orthogonal Frequency Division Multiplexing, OFDM)中,載波頻率偏移(Carrier Frequency Offset, CFO)所導致之頻率不同步,會破壞子載波間之正交性而產生載波間干擾(Inter-carrier Interference, ICI),因而降低系統效能。相較於OFDM系統之單一用戶CFO,上行正交分頻多重存取系統(Orthogonal Frequency Division Multiple Access, OFDMA)因為基地台同時接收多用戶之上傳訊號,除了ICI以外尚有 CFOs成分所形成的多用戶干擾(Multiple Access Interference, MAI),因而對CFOs估計帶來更大的挑戰。粒子群演算法(Particle Swarm Optimization, PSO)是一種可用來估計CFOs的最佳化演算法,然而隨著用戶數增加,PSO會因多樣性(Diversity)不足導致最佳化效果遞減。ARPSO(Attractive and Repulsive PSO)以吸引(Attraction)與排斥(Repulsion)機制來增加Diversity,卻有收斂速度不佳的缺點。因此本論文提出結合突變(Mutation)與排斥(Repulsion)之改良型PSO演算法來改善舊有PSO之平均平方錯誤(Mean Square Error, MSE)效能及收斂速度,此演算法簡稱為MRPSO。另外,我們也應用最小平方(Least Square, LS)法補償ICI與MAI對系統造成的影響。模擬結果顯示,我們所提出的方法可以有效提升CFOs之估計與補償的效能。

並列摘要


For the orthogonal frequency division multiplexing (OFDM) system, carrier frequency offset (CFO) leads to loss of orthogonality among subcarriers; thus significantly degrading bit error performance. Moreover, in the uplink orthogonal frequency division multiple access (OFDMA) system, multiple CFOs due to multi-user result in multiple access interference (MAI), further degrading system performance. Particle Swarm Optimization (PSO) is one potential scheme for CFOs estimation, however, its performance gradually degrades with the increasing number of users due to the lack of diversity. While attractive and repulsive PSO (ARPSO) can enhance diversity using attraction and repulsion operators, its convergent speed is very slow. Therefore, this study proposes a modified PSO, which is called MRPSO for simplicity, to improve mean square error (MSE) performance and convergent speed of PSO by integrating mutation and repulsion operators. Additionally, least square (LS) is employed to mitigate the effect of ICI and MAI. Simulation result indicates that our proposed scheme is superior to LPSO_Mut and ARPSO for CFOs estimation and compensation.

參考文獻


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