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  • 學位論文

多輸入多輸出通訊系統下使用晶格縮減表列偵測技 術於向量預編碼之研究

Lattice Reduction Aided Vector Precoding Techniques Using a Candidate List for MIMO Communications Systems

指導教授 : 陳喬恩
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摘要


向量預編碼(vector precoding, VP)演算法是一種在傳送端加入擾動向量來提升系統 效能的技術。因此結合多輸入輸出(MIMO)通訊系統與向量預編碼技術可以在高訊雜 比(SNR)時達到全分集增益(full diversity gain)。在本篇論文裡,我們基於MIMO通訊系 統下對向量預編碼技術從兩部份做改進。 第一部份我們將晶格縮減(lattice reduction, LR)演算法運用在最近所提出的傳收端設 計向量預編碼使用迭代能量分配上。在傳收端設計向量預編碼演算法中,使用類似全搜 索的球狀解碼(sphere decoder, SD)技術來搜尋擾動向量可得到最佳的效能,但也增加了 系統的複雜度和硬體的成本。我們所提出的演算法利用晶格縮減技術尋找次佳的擾動向 量,相較於球狀解碼演算法,此技術可以犧牲些許效能來大幅降低複雜度。 第二部份為改進晶格縮減表列偵測於向量預編碼的技術。在降低複雜度方面我們提出 兩種演算法,利用轉換矩陣的結構來減少產生的表列。在改善效能方面我們提出同時使 用向前晶格縮減(forward LLL, FRLLL)和向後晶格縮減(backward LLL, BRLLL)表列偵 測的向量預編碼方法。此演算法與使用晶格縮減表列偵測的向量預編碼相較之下,在效 能方面可獲得提升。 本篇論文透過使用晶格縮減演算法搭配各種技術應用在向量預編碼上,並在權衡複雜 度與效能後改進向量預編碼。接著我們用電腦模擬將我們所提出演算法與傳收端設計向 量預編碼演算法和晶格縮減表列偵測於向量預編碼演算法的錯誤率做比較。而從模擬結 果顯示,我們所提出的演算法在降低複雜度方面有明顯的改善。

並列摘要


Vector perturbation (VP) precoding, the precoding technique which perturbs the signal by some perturbation vector before transmission, can effectively improve the performance of a communications system. When combined with the use of multiple-input-multipleoutput (MIMO) technique, VP has been shown to achieve the full diversity gain. In this thesis, we propose several practical approaches to improve this technique. In the first part of the thesis, we introduce the lattice reduction (LR) algorithm to the recently proposed VP transceiver design with iterative power loading. Unlike the original algorithm which uses a sphere-decoder to search for the optimal perturbation vector, we propose to solve it via a number of LR-aided precoding schemes. Simulation results show that the proposed algorithms can significantly reduce the computational complexity at the expense of only marginal performance loss. In the second part of the thesis, we investigate ways of improving the vector perturbation techniques by using a candidate list. Two kinds of algorithms have been proposed. The first kind is based on the forward and backward LLL, which has been shown to provide improved error rate performance. The second kind reduces the computational complexity by exploiting the structure of the unimodular transformation matrix. The algorithms have been evaluated and compared via extensive computer simulations.

參考文獻


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