於巨量天線系統中基於加權子空間擬合的粒子群最佳化搜尋之聯合載波頻率偏移與到達方向估測

Joint CFO and DOA Estimation Based on Weighted Subspace Fitting with PSO Searching for Massive Antenna Systems

陳亭傑(Ting-Chieh Chen)

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(2021年)

摘要

本論文於含有較大的子通道數目和巨量天線陣列元件數目之OFDMA上行系統中發展具有計算效率的聯合載波頻率偏移(carrier frequency offset, CFO)和到達方向(direction of arrival, DOA)估測技術，由於具有高頻譜效率和空間多工增益，故正交分頻多工存取(orthogonal frequency division multiple access, OFDMA)架構的應用能夠有效地提升通訊系統容量。由於參數空間本質上是非線性和高維度的，而基於頻譜搜尋的加權子空間擬合估測器之計算複雜度和估測精準度係與搜尋格柵尺寸和搜尋範圍大小有很密切的關係，故頻譜搜尋相當耗時且適當格柵尺寸的決定具有不確定性。首先，本論文使用近似的訊號子空間估測方法用以降低天線陣列元件和子通道數目增加導致特徵值分解之計算複雜度增加；其次為了減輕區域最佳問題和搜尋格柵尺寸的不確定性，第二個部分引入粒子群最佳化(particle swarm optimization, PSO)演算法進行全域最佳解的搜尋，不僅可以避免搜尋格柵尺寸之不確定先驗決定的困境，亦可降低傳統窮舉式的頻譜搜尋所需要之計算複雜度；在此部分，本論文亦提出修正的PSO演算法以確保最佳解能夠在解空間中被尋獲。為了加快最佳解的搜尋速度，第三個部分首先透過離散傅立葉變換的應用分別來獲得粗略的初始CFO和DOA估測，然後PSO搜尋即可在非常小的區域內準確估測CFO和DOA。最後，藉由一些電腦模擬結果驗證這些所提出方法的有效性。

關鍵字

正交分頻多工存取 ； 載波頻率偏移 ； 到達方向 ； 聯合估測 ； 加權子空間擬合 ； 粒子群最佳化 ； 離散傅立葉轉換

並列摘要

This thesis develops computationally efficient joint carrier frequency offset (CFO) and direction of arrival (DOA) estimation techniques in OFDMA uplink system with large subchannels and massive antenna array elements. The applications of orthogonal frequency division multiple access (OFDMA) structures can promote the capacities of communication system due to the high spectrum efficiency and the spatial multiplexing gain. Due to the nonlinear high-dimensional nature of the parameter space, the complexity and estimation accuracy of the searching-based weighted subspace fitting (WSF) estimator strictly depend on the grid size used during the search. It is time consuming and the search grid is not clear. First, this thesis presents the estimate method of approximation signal subspace which can be used to reduce the computational complexity of eigenvalue decomposition that increasing with number of elements for DOA estimation and with number of subchannels for CFO estimation. Second, In order to mitigate the local optimal problem and the uncertainty of searching grid size, the thesis introduces particle swarm optimization (PSO) algorithm to search global optimal solution. It can prevent the predicament of the uncertain priori-decisions of searching grid size. Moreover, the needed computational complexity of the exhaustively spectrum scanning for peak finding can be reduced. In this part, this thesis also proposes a modified PSO algorithm which guarantees that the optimum solution can be found in the solution space. For accelerating the searching speed, the third part first obtains coarse initial CFO and DOA estimates via the application of discrete Fourier transform (DFT) and then PSO search for the accurate estimates within a very small region, respectively. Finally, several simulation results are provided for illustrating the effectiveness of the proposed methods.

並列關鍵字

orthogonal frequency division multiple access ； carrier frequency offset ； direction of arrival ； joint estimation ； weighted subspace fitting ； particle swarm optimization ； discrete Fourier transform

參考文獻

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