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研究生: 葉昱成
Yeh, Yu Cheng
論文名稱: 適用於空時排列調變多輸入多輸出系統之低複雜度偵測器設計及實作
Design and Implementation of Low-Complexity Detector for Space-Time Permutation Modulation MIMO Systems
指導教授: 黃元豪
Huang, Yuan Hao
口試委員: 陳喬恩
Chen, Chiao En
賴以威
Lai, I Wei
蔡佩芸
Tsai, Pei Yun
黃元豪
Huang, Yuan Hao
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年: 2016
畢業學年度: 105
語文別: 英文
論文頁數: 63
中文關鍵詞: 空時排列調變空時排列碼空間排列調變多輸入多輸出系統偵測器球面偵測器排序球面偵測器多候選選擇匹配最高比結合偵測器現場可程式化閘陣列
外文關鍵詞: Space-Time Permutation Modulation, Space-Time Permutation Code, Spatial Permutation Modulation, MIMO System, Detector, Sphere Detector, Ordered Sphere Detector, Multiple Candidate Selection Matched-MRC Detector, FPGA
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  • 近年來,行動裝置的數量越來越多,人們除了對行動裝置的功能很重視外,對傳輸的品質更是格外的要求,因此,空時排列調變多輸入多輸出(STPM-MIMO)因而被提出,它為一種新的多天線多輸出技術且擁有良好的傳輸穩定度。

    基於空時排列調變多輸入多輸出技術,本篇論文提出三種偵測器的演算法,包含球面偵測器(Sphere Detector)、排序球面偵測器(Ordered Sphere Detector)以及多候選選擇匹配最高比結合偵測器(Multiple Candidate Selection Matched-MRC Detector)。球面偵測器以及排序球面偵測器為最佳偵測器(Optimal Detector),它們的位元錯誤率與最大似然偵測器(Maximum-Likelihood Detector)相同。球面偵測器的運算複雜度在高訊雜比時,大概只有最大似然偵測器的15.6%。排序球面偵測器可以改善球面偵測器搜尋的效率,因此在高訊雜比時,排序球面偵測器的運算複雜度約只有球面偵測器複雜度的33%。雖然球面偵測器與排序球面偵測器擁有最大似然偵測器的位元錯誤率表現,但它們並不適合用於硬體實現。多候選選擇匹配最高比結合偵測器為次最佳偵測器,但其非常適合實作於硬體,它的運算複雜度在訊雜比為30dB以及0dB時僅只有排序球面偵測器複雜度的10%以及5%,但只有不到0.15dB的表現損失。

    本篇論文最後用現場可程式化閘陣列(Field-Programmable Gate Array)(xc7vx690t-3ffg1157)實作以及驗證多候選選擇匹配最高比結合偵測器,並且提出兩種版本的硬體,第一個版本擁有較高的吞吐量(539Mbps)但相對用了較多FPGA的資源;另一個版本的吞吐量(8.8Mbps)較低但使用非常少FPGA的資源。此外,硬體的時序以及FPGA資源使用率的分析也將呈現於本論文中。


    In the past few years, the number of mobile devices are more and more. Not only to the functions of the mobile devices, people attach great importance to the transmission quality as well. A new MIMO technology called Space-Time Permutation Modulation MIMO(STPM-MIMO) has additional consideration about transmission reliability.

    Based on the STPM-MIMO technology, this thesis proposes three detector algorithms, which are Sphere detector(SD), Ordered Sphere detector(OSD) and Multiple Candidate Selection Matched-MRC detector(MCSMMD) algorithms. SD and OSD algorithms are optimal detector algorithms, and their BER performances are the same as the benchmark, Maximum-Likelihood(ML) detector algorithm. The computing complexity of SD algorithm is about 15.6 percent of ML detector algorithm at high SNR. OSD algorithm can improve the efficiency of SD algorithm. The computing complexity of OSD algorithm is approximately 33 percent of SD algorithm at high SNR. Although SD and OSD algorithms have the ML performance, they are not suitable for hardware implementation. MCSMMD algorithm is sub-optimal detector algorithm; however, it is a easier and flexible hardware implementation detector algorithm. The computing complexity of MCSMMD algorithm is approximately 10 and 5 percent of OSD algorithm with very little performance loss at SNR 30 and 0 dB, respectively.

    In this thesis, two versions of hardware architecture of MCSMMD algorithm are proposed, implemented and verified by FPGA(xc7vx690t-3ffg1157). One version has higher throughput(539Mbps) but higher utilization; the other version has lower throughput(8.8Mbps) but lower utilization. The analysis of hardware timing and hardware area are also presented in the end.

    1 Introduction 1 1.1 Spatial Multiplexing MIMO System . . . . . . . . . . . . . . . . . . . . . 1 1.2 Spatial Modulation MIMO System . . . . . . . . . . . . . . . . . . . . . 2 1.3 Space-Time Permutation Modulation(STPM) MIMO System . . . . . . . 4 1.4 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.5 Organization of Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2 Space-Time Permutation Modulation MIMO system 7 2.1 An example of STPM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.3 Channel Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.4 Permutation Array . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.4.1 Hamming Distance . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.5 Spectral Efficiency of STPM . . . . . . . . . . . . . . . . . . . . . . . . . 13 3 STPM Detections 15 3.1 Optimal Detections for STPM . . . . . . . . . . . . . . . . . . . . . . . . 15 3.1.1 Maximum-Likelihood(ML) Detector . . . . . . . . . . . . . . . . . 15 3.1.2 Sphere Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.1.3 Ordered Sphere Detector . . . . . . . . . . . . . . . . . . . . . . . 22 3.1.4 Complexity and Performance Analysis . . . . . . . . . . . . . . . 29 3.2 Suboptimal Detection for STPM . . . . . . . . . . . . . . . . . . . . . . . 32 3.2.1 Multiple Candidate Selection Matched-MRC Detector . . . . . . . 32 3.2.2 Complexity and Performance Analysis . . . . . . . . . . . . . . . 40 4 Architecture 43 4.1 System Specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.2 System Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 4.3 Matched Circuit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 4.4 Maximum Ratio Combining(MRC) Circuit . . . . . . . . . . . . . . . . . 48 4.5 Higher Throughput Architecture . . . . . . . . . . . . . . . . . . . . . . . 49 4.6 Lower Throughput Architecture . . . . . . . . . . . . . . . . . . . . . . . 50 5 Chip and FPGA Implementation Results 53 5.1 Fixed-point Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 5.2 FPGA Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 5.3 FPGA Synthesis Result . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 5.3.1 Device Utilization . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 5.3.2 Timing and Throughput Analysis . . . . . . . . . . . . . . . . . . 58 5.4 TSMC90nm Synthesis Result . . . . . . . . . . . . . . . . . . . . . . . . 60 6 Conclusion 61

    [1] J. Mietzner, R. Schober, L. Lampe, W. Gerstacker, and P. Hoeher, “Multipleantenna techniques for wireless communications - a compoehensive literature survey,“ in Communications Surveys Tutorials, IEEE, vol. 1, no. 2, Second 2009, pp.87-105.

    [2] Raed Y. Mesleh, H. Haas, S. Sinaovic, C. W. Ahn, and S. Yun, “Spatial modulation,“ in IEEE Trans. Veh. Technol., vol. 57, no. 4, July 2008, pp. 2228-2241.

    [3] Marco Di Renzo, Harald Haas, Ali Ghrayeb, Shinya Sugiura and Lajos Hanzo, “Spatial Modulation for GeneralizedMIMO: Challenges, Opportunities, and Implementation,“ in Proceedings of the IEEE, vol. 102, no. 1, January 2014, pp. 56-103.

    [4] D. G. Fang, in Antenna Theory and Microstrip Antennas, 2010.

    [5] M. D. Renzo and H. Haas, “Bit error probability of sm-mimo over generalized fading channels," in IEEE Transactions on Vehicular Technology, vol. 61, no. 3, March 2012, pp. 1124-1144.

    [6] Z. D. Miaowen Wen, X. Cheng, H. V. P. Yuyang Bian, and B. Jiao, “Performance analysis of differential spatial modulation with two transmit antennas," in IEEE Communication Letters, vol. 18, no. 3, March 2014, pp. 475-478.

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