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作者(中文):陳泓葳
作者(外文):Chen, Hong-Wei
論文名稱(中文):基於可接受錯誤率與動態訊雜比調整之低複雜度空間調變多輸入多輸出偵測器
論文名稱(外文):A Low-Complexity SNR-Adaptive Spatial Modulation Detector with Just-Acceptable Error Rate
指導教授(中文):黃元豪
指導教授(外文):Huang, Yuan-Hao
口試委員(中文):陳喬恩
黃元豪
伍紹勳
蔡佩芸
學位類別:碩士
校院名稱:國立清華大學
系所名稱:電機工程學系
學號:101061608
出版年(民國):103
畢業學年度:103
語文別:英文
論文頁數:85
中文關鍵詞:空間調變多輸入多輸出偵測器
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近年來無線通訊系統發展迅速,為了達到人們的需求,多輸出多輸入(MIMO)系統的維度(dimension)也不斷增加來提供高的吞吐量(throuput),因此低錯誤率且低複雜度的多輸出多輸入(MIMO)偵測器變成一個熱門的議題.然而隨著天線數不斷的增加,訊號處理的複雜度跟著提高,訊號之間的干擾(ICI)以及每根天線都搭載著一個RF-chain,這使得電路體積龐大且功率號損嚴重,於是就有人提出了空間調變多輸入多輸出(spatial modulation system)的系統,它為單一RF-chain的概念(single RF-chain),限制RF-chain的數目用來解決功率損號以及電路龐大的問題,還可以化簡傳送端與接收端的複雜度.空間調變多輸入多輸出(spatial modulation system)的系統利用獨特的調變方式不同於傳統的多輸出多輸入(MIMO)系統,將接收到的二位元訊號mapping到訊號星座圖上以及空間星座圖上,借此可以提高吞吐量,本論文使用空間調變多輸入多輸出(spatial modulation system)的系統.
本論文重點在於低運算複雜度的偵測器,首先我們可以設定一個可以接受的錯誤率,再根據不同接收到的訊雜比去選取最低複雜度的偵測器來使用,來提供可接受的錯誤率(JAER),傳統的ML偵測器複雜度過高不適合來實踐在硬體上,且sphere decoding 偵測器雖然可以降低複雜度但是由於偵測器無法固定運算的吞吐量所以本論文提出一個modified k-best 的演算法來做為偵測器.論文中介紹兩種偵測器分別是single k-best偵測器以及multiple k-best 偵測器,根據不同的參數有不同的複雜度,接著我們提出algorithm selection(選取演算法)的方法,來選擇低複雜度的偵測器提供可接受的錯誤率.
Abstract
1. Introduction
1.1 MIMO
1.1.1 The features of MIMO
1.2 Single-RF MIMO
1.3 Spatial modulation
1.3.1 The features of spatial modulation
2. Spatial modulation system model and generalized detection
2.1 SM modulator
2.2 Channel model
2.3 Maximum Likelihood optimal(ML) detector
2.4 Sphere decoding for spatial modulation
2.4.1 Receiver-centric sphere decoding (Rx-SD)
2.4.2 Transmit-centric sphere decoding (SM-Tx)
3. Channel preprocessing and MIMO detection
3.1 QR decomposition algorithm
3.1.1 Gram-Schmidt method
3.1.2 Householder transform method
3.1.3 Givens Rotation method
3.2 Traditional MIMO detection algorithm
3.2.1 ZF detector
3.2.2 MMSE detector
3.2.3 Maximum Likelihood MIMO detector
3.2.4 QR-SIC detector
3.2.5 Sphere decoding detector
3.2.6 Fixed complexity sphere decoding
3.2.7 K-best detector
4. Proposed detector for spatial modulation system
4.1 Single K-best detector
4.2 Multiple K-best detector
4.3 Simulation result of the proposed K-best detector
4.4 Complexity of proposed K-best
4.5 Algorithm selection
5. Hardware architecture
5.1 The architecture of the proposed K-best detector
5.1.1 The architecture of PED
5.1.2 The architecture of MIN
5.1.3 The architecture of ED
5.1.4 Fixed-point Simulation
6. Conclusion
6.1 Conclusion

Appendix
A Gray coding
B Derivation of MMSE Detector
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[37]Reduced Complexity Sphere Decoder for Spatial Modulation Detection Receivers Abdelhamid Younis∗, Raed Mesleh‡, Harald Haas∗‡, and Peter M. Grant∗∗Institute for Digital Communications, Joint Research Institute for Signal and Image Processing, The University of Edinburgh,Edinburgh EH9 3JL, UK, Email: {a.younis, h.haas & peter.grant}@ed.ac.uk‡Jacobs University Bremen, School of Engineering and Science, Campus Ring 1, Research 1, 28759 Bremen, Germany,Email: r.mesleh@jacobs-university.de 
[38]Generalised Sphere Decoding for Spatial Modulation Abdelhamid Younis, Sinan Sinanovi´c, Marco Di Renzo, Raed Mesleh, and Harald Haas
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[41]Sphere Decoding for Spatial Modulation Abdelhamid Younis(1), Marco Di Renzo(2), Raed Mesleh(3), and Harald Haas(1)(1)Institute for Digital Communications, Joint Research Institute for Signal and Image Processing The University of Edinburgh , Edinburgh EH9 3JL, UK (2)L2S, UMR 8506 CNRS – SUPELEC – Univ Paris–Sud Laboratory of Signals and Systems (L2S), French National Center for Scientific Research (CNRS) E´cole Supe´rieure d’E´ lectricite´ (SUPE´LEC), University of Paris–Sud XI (UPS) 3 rue Joliot–Curie, 91192 Gif–sur–Yvette (Paris), France(3)University of Tabuk, Electrical Engineering Department, P.O.Box: 741, 71491 Tabuk, Saudi Arabia,E–Mail: {a.younis, h.haas}@ed.ac.uk, marco.direnzo@lss.supelec.fr, raed.mesleh@ieee.org 
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