基於K最佳演算法之可擴展軟性解調輸出多輸入多輸出偵測器

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：53

、訪客IP：18.191.225.216

姓名

李銘豪(Ming-hao Lee) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

基於K最佳演算法之可擴展軟性解調輸出多輸入多輸出偵測器
(Design of Scalable Soft-output MIMO Detector based on K-Best Algorithm)

相關論文

★ 應用於2.5G/5GBASE-T乙太網路傳收機之高成本效益迴音消除器	★ 應用於IEEE 802.3bp車用乙太網路之硬決定與軟決定里德所羅門解碼器架構與電路設計
★ 適用於 10GBASE-T 及 IEEE 802.3bz 之高速低密度同位元檢查碼解碼器設計與實現	★ 基於蛙跳演算法及穩定性準則之高成本效益迴音消除器設計
★ 運用改良型混合蛙跳演算法設計之近端串音干擾消除器	★ 運用改良粒子群最佳化演算法之近端串擾消除器電路設計
★ 應用於多兆元網速乙太網路接收機類比迴音消除器之最小均方演算法電路設計	★ 光耦合隔離系統之接收端晶片電路設計與實現
★ 應用於光耦合隔離系統之發送端雜訊整形類比轉數位轉換器	★ 應用於數位視頻廣播系統之頻率合成器及3.1Ghz寬頻壓控震盪器
★ 地面數位電視廣播基頻接收器之載波同步設計	★ 適用於通訊系統之參數化數位訊號處理器核心
★ 以正交分頻多工系統之同步的高效能內插法技術	★ 正交分頻多工通訊中之盲目頻域等化器
★ 兆元位元率之平行化可適性決策回饋等化器設計與實作	★ 應用於數位視頻廣播系統中之自動增益放大器及接受端濾波器設計

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

本論文提出了一個基於K最佳演算法的可擴展性的軟性輸出之多輸入多輸出偵測器，可支援QPSK、16QAM、64QAM等三種調變，天線組態可支援2x2、4x4、8x8三種組態。由文獻可知道軟性輸出之多輸入多輸出偵測器可以簡化成候選列表產生器與軟性值產生器兩個區塊。候選列表產生器是能夠提供多組訊號路徑偵測結果，而軟性值產生器則是利用候選列表產生器所提供的資訊來產生每一個位元的軟性值。對於候選列表產生器，我們是採用DKB結合SIC演算法來實現，DKB演算法能夠減少每一層樹狀搜尋的拜訪節點數，從原本傳統K最佳演算法個拜訪點數減少為，而為了更進一步減少拜訪點數，SIC演算法取代了原本是DKB演算法的樹狀搜尋。硬體實現方面，我們採用了管線式架構的方式來實現我們的硬體。管線式架構的特色在於能夠提供比較高的資料吞吐量，但是比較難實現多天線組態的架構。為了克服這個缺點，我們設計了一個控制電路能夠對於處理單元重新組合成能夠支援多天線組態的電路。本論文利用90-nm製程的技術來實現晶片設計，晶片的核心面積為1.13 1.13 mm2，晶片的最高操作頻率為114MHz率且功率消耗為56.7 mW。除此之外為了補償因為使用SIC演算法所造成的位元錯誤率效能損失，本論文還提出了一個演算法是有效率的增加候選列表數量的演算法，概念是利用樹狀搜尋中每一層K最佳訊號的資訊來有效的產生更多組偵測訊號路徑的結果，由模擬結果與複雜度的比較下，我們所提出來的演算法相比於由傳統K最佳演算法所產生的K組訊號偵測結果來產生軟性輸出，在複雜度方面至少能夠節省22%，在位元錯誤率效能提升方面，不僅可以補償SIC所造成的損失以外，還能夠額外提供最多1.5dB的效能提升。

摘要(英)

A scalable soft output MIMO detector based on K-Best algorithm is proposed in this thesis. It can support various modulation scheme such as QPSK, 16QAM, 64QAM, and multiple antenna such as 2x2, 4x4, 8x8. The soft output MIMO detector can be simplified to two blocks. One is the candidate list generator which generates a list path of tree search. The other is the soft generator which utilizes the information of the result of candidate list generator to compute the soft values of each transmitted bits. For the candidate list generator, we combine distributed K-Best (DKB) with successive inference cancellation (SIC) algorithm in order to reduce complexity compared to conventional K-Best. The DKB algorithm can reduce the number of visited nodes at each layer of tree search from to . To further reduce number of visited nodes, successive inference cancellation (SIC) is employed in some specific layers to replace the layer of DKB detection. From the viewpoint of hardware implementation, we adopted pipelined architecture. The feature of pipelined architecture is able to provide high data throughput, but it is hard to provide multi-antenna configurations. To overcome this drawback, we design a control circuit that can reconfigure the process element (PE) to support multi-antenna configurations. Finally, this design is implemented in 90-nm CMOS technology. The core area is 1.13 1.13 mm2. With supply voltage of 1 V, the chip power is 56.7 mW and its maximum clock rate is 114 MHz. For soft decision, we proposed an algorithm that uses the information of K-Best signals in each layer of tree search to generate additional tree search paths to further enhance BER performance of the soft output MIMO detector. From the simulation results and complexity comparison, the proposed algorithm reduces computational complexity at least 22% and improves BER performance at best 1.5dB compared to conventional K-Best.

關鍵字(中)

★ 多輸入多輸出偵測器
★ 軟性解調輸出
★ K最佳演算法

關鍵字(英)

★ MIMO detector
★ Soft-output
★ K-Best Algorithm

論文目次

摘要 i
Abstract ii
致謝 iii
目錄 iv
圖目錄 vi
表目錄 ix
第一章緒論 1
1.1背景 1
1.2研究動機 2
1.3論文架構 4
第二章多輸入多輸出系統 4
2.1系統架構 5
2.2空間多工 7
2.2空間多工解碼演算法 7
2.3.1線性解碼 8
2.3.2非線性解碼 9
2.4軟性解調輸出(Soft output) 17
2.4.1比較軟性解調與硬性解調的差異 17
2.4.2 比較Hard/Soft input channel decoder的差異 20
2.4.3非線性解碼MIMO偵測器的軟性解調輸出 22
第三章軟性解調MIMO偵測器演算法 23
3.1 軟性解調輸出非線性解碼MIMO偵測器的簡化 24
3.2候選列表產生器 26
3.2.1離散K最佳演算法 26
3.2.2天線組態可配置架構 31
3.2.3複雜度與效能比較分析 35
第四章硬體架構設計 38
4.1 基本電路介紹 40
4.2 候選列表產生器 43
4.3 軟性輸出值產生器 52
4.4 控制電路的設計 55
第五章晶片實現 56
5.1 設計流程 56
5.2 定點數模擬 57
5.3 FPAG驗證 65
5.4 晶片設計結果 67
5.4.1 模擬結果驗證 67
5.4.2 晶片結論 69
5.5 硬體比較 71
第六章有效率的增加候選列表數量演算法 74
6.1 MKSE演算法 74
6.2 有效率增加候選列表數量演算法的概念 76
6.3複雜度與效能比較分析 82
第七章未來展望與結論 85
參考文獻 86

參考文獻

[1] E. Perahia, R. Stacey, “Next Generation Wireless LANs:Throughtput, Robustness, and Reliability in 802.11n” Cambridge University Press, Sep. 2008.
[2] E. Teletar. “Capacity of multi-antenna Gaussian channels,” European Transactions Telecommunications, pp. 585-595., Nov.-Dec. 1999.
[3] D. Garrett, L. Davis, S. ten Brink, and B. Hochwald, “APP processing for high performance MIMO systems,” in Proc. IEEE Custom Integrated Circuits Conf., San Jose, CA, Sep. 2003, pp. 271–274.
[4] A. Burg, N. Felber, and W. Fichtner, “A 50 mbps 4_4 maximum likelihood decoder for multiple-input multiple-output systems with QPSK modulation,” in Proc. 10th IEEE Int. Conf. Electron., Circuits, Syst.(ICECS), Dec. 2003, pp. 322–335.
[5] B. Hassibi and H. Vikalo, “On the sphere-decoding algorithm I. Expected complexity,” IEEE Trans. on Signal Processing, vol. 53, pp. 2806-2818, August 2005.
[6] Saif K. Mohammed, K. Vishnu Vardhan, A. Chockalingam, B. Sundar Rajan, ” Large MIMO Systems: A Low-Complexity Detector at High Spectral Efﬁciencies”, IEEE Int. Conf. on Commun., pp. 1104-1109, May 2008.
[7] A. Burg, M. Borgmann, M. Wenk, M. Zellweger, W. Fichtner, and H. Bolcskei, “VLSI implementation of MIMO detection using the sphere decoding algorithm,” IEEE J. Solid-State Circuit, vol. 40, pp. 1566-1577., 2005.
[8] M. Wenk, M. Zellweger, A. Burg, N. Felber, and W. Fichtner, “K-Best MIMO detection VLSI architectures achieving up to 424 Mbps,” in proc ISCAS 2006, pp. 1151-1154.
[9] 周志成,”貝式定理-量化思考的利器”, 線代啟示錄,April 29th, 2009
[10] Fred Ma and John Knight, “Convolution codes”, January 27th, 1999
[11] Bernard Sklar, “Digital communications : fundamentals and applications”, 2nd ed., Upper Saddle River, N.J. : Prentice-Hall PTR, c2001.
[12] Yong Soo Cho, Jaekwon Kim, Won Young Yang, Chung G. Kang,” MIMO-OFDM WIRELESS COMMUNICATIONS WITH MATLAB” ,2010.
[13] M. Siti and M. Fitz, “A novel soft-output layered orthogonal lattice detector for multiple antenna communications,” in IEEE International Conference on Communications, 2006. ICC’06, vol. 4, 2006
[14] M. Siti and M. P. Fitz, “Layered orthogonal lattice detector for two transmit antenna communications,” in Proc. Allerton Conference On Communication, Control, And Computing, Sep. 2005.
[15] P. Bhagawat, R. Dash, and G. Choi, “Dynamically reconfigurable soft output MIMO detector,” in ICCD, 2008, pp. 68–73.
[16] Hochwald and S. t. Brink, “Achieving near-capacity on a multipleantenna
channel,” IEEE Trans. Communications, vol. 51, no. 3, pp.389–399, 2003.
[17] HC. Studer, A. Burg, and H. B¨olcskei, “Soft-output sphere decoding:Algorithms and VLSI mplementation,” IEEE Journal on Selected Areas in Communications vol. 26, no. 2, pp. 290–300, Feb. 2008.
[18] Bhagawat, P.; Dash, R.; Gwan Choi,” Systolic Like Soft-Detection Architecture for 4x4 64-QAM MIMO System”, Design, Automation & Test in Europe Conference & Exhibition, 2009. DATE ’09.
[19] S. Chen, T. Zhang, and Y. Xin, “Relaxed K-best MIMO signal detector design and VLSI implementation,” IEEE Trans. Very Large Scale Integr.(VLSI) Syst., vol. 15, no. 3, pp. 328–337, Mar. 2007
[20] Z. Guo and P. Nilsson, “Algorithm and implementation of the K-best sphere decoding for MIMO detection,” IEEE Journal on Selected Areas in Communications, vol. 24, no. 3, pp. 491–503, 2006.
[21] M. Shabany and P. G. Gulak, “Scalable VLSI architecture for K-best lattice decoders,”in proc. ISCAS, 2008, pp. 940-943
[22] S.-K. Lin and M.-T. Shiue, “Design of Configurable K-Best MIMO Detector for 2×2, 4×4, and 8×8 Data Streams”, National Central University thesis, 2010.
[23] T.-P. Wang and T.-D. Chiueh, “Design of a New Complex Sphere Decoder for Soft-Output MIMO Detection” National Taiwan University thesis, 2007.
[24] N. Moezzi-Madani, T. Thorolfsson, and W. Davis, “A Low-Area Flexible MIMO Detector for WiFi/WiMAX Standards” , in DATE ’10:Proceedings of 2010 Design, Automation and Test Conference, mar. 2010,pp. 1633-1636
[25] S. Chen and T. Zhang, “Low power soft-output signal detector design for wireless MIMO communication systems”, in Proc. International Symp. On Low Power Electronics and Design, pp. 232-237,2007
[26] C.-H. Liao, T.-P. Wang and T.-D. Chiueh, “A 74.8mW soft-output detector IC for 8×8 spatial-multiplexing MIMO communications,” IEEE J. Solid-State Circuit, vol. 45, no. 2, pp. 411-421., 2010
[27] C. Hess, M. Wenk, A. Burg, P. Luethi, C. Studer, N. Felber, and W. Fichtner, “Reduced-complexity MIMO detector with close-to ML error rate performance,” in Proc. 17th ACM Great Lakes Symp. VLSI(GLSVLSI), 2007, pp. 200–203.
[28] 3G LTE & IMT-Advanced Service, HSN 2006, February 22-24, 2006, Dr. Hyeon Woo Lee, Global Standards & Research, SAMSUNG ELECTRONICS
[29] E. Agrell, T. Eriksson, A. Vardy, and K. Zeger, “Closet point search in lattices,” IEEE Trans. Inform. Theory, vol. 48, no. 8, pp. 2201-2214, Aug. 2002.
[30] K.-W. Wong, C.-Y. Tsui, R. S.-K Cheng and W.-H. Mow, “A VLSI architecture of a K-best lattice decoding algorithm for MIMO channels,” in Proc. ISCAS, May 2002, pp. 273-276.

指導教授

薛木添(Muh-Tian Shiue)

審核日期

2012-11-30

推文