基於群體最佳化的加權子空間擬合技術於載波頻率偏移估測

Weighted Subspace Fitting Technique Based on Swarm Optimization for Carrier Frequency Offset Estimation

張銘樺(Ming-Hua Zhang)

指導教授 ： 張安成

嶺東科技大學/資訊學院/資訊科技系碩士班/碩士(2019年)

摘要

本論文係於交織分頻多工存取(orthogonal frequency division multiple access, OFDMA)上行系統處理具有加權子空間擬合(weighted subspace fitting, WSF)法則之基於群體智慧最佳化演算法(swarm intelligence optimization)的盲目載波頻率偏移(carrier frequency offset, CFO)。對於CFO估測問題，眾所皆知WSF具有優越的統計特性和較佳的估測性能，無論如何，這類型的CFO估測必須於高維空間問題上透過對複雜的非線性多模態函數實施最佳化，然而需要巨大的計算負荷，導致在大參數空間中直接對非線性目標函數作最大化或最小化似乎是相當困難且不容易實現。因此，本論文使用群體智慧最佳化演算法來增進估測精準度和降低計算負荷，而主要的最佳化演算法包括粒子群最佳化(particle swarm optimization, PSO)、引力搜尋演算法(gravitational search algorithm, GSA)和混合PSO和GSA演算法(PSOGSA)以及鯨魚最佳化演算法(whale optimization algorithm, WOA)；同時，本論文亦加入模糊推論於PSO和GSA來降低所需的迭代數目。最後，提供一些模擬結果用以說明所提出的CFO估測器的有效性。

關鍵字

載波頻率偏移 ； 交織正交分頻多工存取 ； 上行 ； 加權子空間擬合 ； 群體智慧最佳化 ； 粒子群最佳化 ； 引力搜尋演算法 ； 鯨魚最佳化演算法 ； 混合PSO和GSA演算法 ； 探勘和開採 ； 模糊推論系統。

並列摘要

This thesis deals with the blind carrier frequency offset (CFO) based on the swarm intelligence (SI) optimization algorithms with the weighted subspace fitting (WSF) criterion for interleaved frequency division multiplexing access (OFDMA) uplink system. For the CFO estimation problem, it is well know that the WSF has superior statistical characteristics and better estimation performance. However, this the type of CFO estimation must pass through the high dimensional space problem. Optimizing complex nonlinear multi-modal functions requires a large computational load, which makes it seem difficult and not easy to maximize or minimize nonlinear objective functions in large parameter spaces. Therefore, this thesis uses the SI optimization algorthms to improve the estimation accuracy and reduce computational load. The main optimization algorithms include particle swarm optimization (PSO), gravitational search algorithm (GSA), the hybrid PSO and GSA (PSOGSA), and the whale optimization algorithm (WOA). Meanwhile, this thesis also adds the fuzzy inference to PSO and GSA for reducing the required number of iterations. Finally, several simulation results are provided for illustrating the effectiveness of the proposed CFO estimators.

並列關鍵字

carrier frequency offset ； interleaved orthogonal frequency division multiple access ； uplink ； weighted subspace fitting ； swarm intelligence ； particle swarm optimization ； gravitational search algorithm ； whale optimization algorithm ； hybrid PSO and GSA ； exploration and exploitation ； fuzzy inference system.

參考文獻

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