中大機構典藏-NCU Institutional Repository-提供博碩士論文、考古題、期刊論文、研究計畫等下載:Item 987654321/58587
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 80990/80990 (100%)
Visitors : 42739686      Online Users : 2750
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/58587


    Title: 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
    Authors: 李銘豪;Lee,Ming-hao
    Contributors: 電機工程學系
    Keywords: 多輸入多輸出偵測器;軟性解調輸出;K最佳演算法;MIMO detector;Soft-output;K-Best Algorithm
    Date: 2012-11-30
    Issue Date: 2012-12-25 13:39:44 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 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。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.
    Appears in Collections:[Graduate Institute of Electrical Engineering] Electronic Thesis & Dissertation

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML681View/Open


    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明