基於符元程序於多重輸入多重輸出 正交分頻多工系統之研究

Studies on Symbol-Based Processing for MIMO-OFDM systems

謝昀容(Yun-Jung Hsieh)

指導教授 ： 李彥文

國立暨南國際大學/科技學院/通訊工程研究所/碩士(2009年)

摘要

於本論文我們討論多重輸入多重輸出(Multiple Input and Multiple Output，MIMO)在正交分頻多工(Orthogonal Frequency Division Multiplexing，OFDM)伴隨通道編碼(Channel Coding)系統之效能，以探討空間分集(Space Diversity)、頻率分集(Frequency Diversity)和時間分集(Time Diversity)對系統之影響。我們知道基於子載波訊號處理方法雖然可以得到最佳的系統效能，但亦伴隨著很高的複雜度。因此，近代有研究提出基於符元處理之技術，即在傳送端/接收端分別只需要使用一個反離散傅立葉/傅立葉轉換，從而大幅降低複雜度。傳統基於符元處理之準則主要為最大化所有子載波之訊號雜訊比總和，此方法之缺點為子載波的訊號雜訊比常常無法平衡，造成整個系統的效能下降。在基於符元處理前提之下，我們提出使用最大-最小公平準則(Max-Min Fair Criterion)以解決此問題，並利用伴隨較低複雜度的正半定放寬(Semidefinite Relaxation，SDR)求解。在論文第一部份，我們於多重輸入多重輸出正交分頻多工系統下考慮已知通道狀態資訊(Channel State Information，CSI)之情況，並在傳送端進行傳輸波束形成。在論文第二部份，我們則考慮無通道狀態資訊之情況，在傳送端加入空時區塊編碼(Space-Time Block Code，STBC)來得到傳送分集增益。最後，我們應用多目標最佳化理論(Multiobjective Optimization)並藉由加權法(Weighted-Sum Method)計算訊號雜訊比效能之柏拉圖前緣(Pareto Front)，以進一步了解正交分頻多工系統中基於符元處理之效能。由模擬結果我們可以知道到於不同之系統參數和環境下，所使用之基於符元處理策略也會有所不同。

關鍵字

正交分頻多工 ； 多重輸入多重輸出 ； 最大-最小公平準則 ； 正半定放寬 ； 空時編碼 ； 多目標最佳化理論 ； 柏拉圖前緣 ； 加權法

並列摘要

In this thesis, we discuss the performance of multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with channel coding. The effect of space, frequency and time diversities is then studied. In this aspect, it is known that subcarrier-based signal processing techniques can provide the best performance. However, the computational complexity will be prohibitively high. Therefore, symbol-based processing techniques have been proposed recently for complexity reduction. Only one inverse discrete Fourier transform (IDFT)/DFT block is required at the transmitter/receiver. Conventional symbol-based processing is to maximize the sum of the signal-to-noise ratio (SNR) values achieved in all subcarriers. The disadvantage of it is that the SNR performance of different subcarriers is often not balanced. This will degrade the whole system performance. Here, to solve this problem, we propose to use the max-min fair criterion for symbol-based processing. Semidefinite relaxation (SDR) is used to approximate the solution with low complexity. In the first part of the thesis, we consider the scenario in which channel state information (CSI) is known at the transmitter, and then transmit beamforming is employed for the MIMO-OFDM system. In the second part of the thesis, we change to discuss the case that CSI is not known at the transmitter and space-time block-coded (STBC)-OFDM is used to obtain transmit diversity gain. Finally, to gain more understanding about the symbol-based processing in OFDM systems, we apply multiobjective optimization techniques with the weighted-sum method to calculate the Pareto Front for the SNR performance. Simulation results show that under different system and environment settings, there should be different design strategies for obtaining good performance.

並列關鍵字

OFDM ； MIMO ； Max-Min Fair Criterion ； SDR ； STBC ； Multiobjective Optimization ； Pareto Front ； Weighted-Sum Method

參考文獻

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