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研究生:王致忠
研究生(外文):Chih-Chng Wang
論文名稱:利用隨機及結構化之樹狀搜尋演算法在低複雜度降低晶格之MIMO檢測下的研究
論文名稱(外文):A Low-Complexity Lattice-Reduction aided MIMO Detection Using Random and Tree-Search Algorithms.
指導教授:魏存毅
指導教授(外文):Chun-Yi Wei
口試委員:白宏達、魏存毅、王鵬華
口試委員(外文):Hung-Ta Pai、Chun-Yi Wei、Peng-Hua Wang
口試日期:2014-08-08
學位類別:碩士
校院名稱:國立臺北大學
系所名稱:通訊工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2014
畢業學年度:103
語文別:英文
論文頁數:26
中文關鍵詞:多輸入輸出系統、混合搜尋法
外文關鍵詞:MIMO、Hybrid Search
相關次數:
  • 被引用被引用:0
  • 點閱點閱:180
  • 評分評分:
  • 下載下載:10
  • 收藏至我的研究室書目清單書目收藏:0
MIMO(多數入多輸出)的訊號偵測在整個通訊架構中佔有非常重要的一環,它關係著整個通訊品質的好與壞。我們知道最大概似檢測(maximum-likelihood-detection, ML)為所有訊號檢測器中擁有最佳解的檢測器,但其計算複雜度也是最高的。如何有效降計算複雜度且保有一定的位元錯誤率(BER),在這兩者之間取得一個權衡,是我們所追求的。在本篇論文中,我們將介紹如何有效達到上述之需求,並且在文末將呈現成果。
The MIMO detector plays a very important role in the communication structure. Detection
methods will directly affect the quality of communication. In this paper we compare the
difference between tree-search algorithm and random rounding-off algorithm, and combine
their advantages into hybrid search. In this process, we add the Lattice-Reduction to help us
to get better communication quality. Finally, we will present the results in the last chapter.
1 Introduction
2 Introduction of MIMO wireless communication
3 Previous work
4 Proposed work and simulation result
5 Conclusion
[1] X. Cao, "Local Maximum Likelihood Detection Method for MIMO Systems," Commu-
nications, Circuits and Systems, 2005. Proceedings. 2005 International Conference on,
vol. 1, pp. 203-206, 2005
[2] R. S.-Yazdi and T. Kwasniewski, "Low complexity sphere decoding algorithms,"Wireless
Communication Systems. 2008. ISWCS '08. IEEE International Symposium on, pp.
438-442, 2008
[3] C.-J Huang, C.-S Sung, and T.-S. Lee, "A NEAR-ML COMPLEX K-BEST SPHERE
DECODER WITH EFFICIENT SEARCH DESIGN FOR MIMO SYSTEMS ,"Intel-
ligent Signal Processing and Communication Systems (ISPACS), 2010 International
Symposium on, pp. 1-4, 2010
[4] C. Ling, W.-H. Mow, and L. Gan, "Dual-lattice ordering and partial lattice reduction
for sic-based mimo detection," Selected Topics in Signal Processing, IEEE Journal of,
vol. 3,no. 6,pp. 975-985, 2009.
[5] Y. H. Gan and W.-H. Mov, "Complex lattice reduction algorithms for low-complexity
mimo detection," in Global Telecommunications Conference, 2005. GLOBECOM '05.
IEEE, vol. 5,pp. 5 pp.-2975, 2005.
[6] S. Liu, C. Ling, and D. Stehle, "Decoding by sampling: A randomized lattice algorithm
for bounded distance decoding," Information Theory, IEEE Transactions on, vol. 57,
no. 9 pp. 5933-5945, 2011.
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