(35.175.212.130) 您好!臺灣時間:2021/05/17 22:02
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:黃家成
研究生(外文):KYAR CHAN
論文名稱:演化式演算法在多輸入多輸出無線通訊系統中結合天線選擇及訊號偵測之應用
論文名稱(外文):Joint Antenna Selection and Symbol Detection Using Evolutionary Algorithms in the MIMO Wireless Communication Systems
指導教授:方文賢
指導教授(外文):Wen-Hsien Fang
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:電子工程系
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:2008
畢業學年度:96
語文別:英文
論文頁數:65
中文關鍵詞:訊號偵測天線選擇基因演算法異質性交配廣義天線組合最小化位元錯誤率多輸入多輸出
外文關鍵詞:symbol detectiongenetic algorithmantenna selectionheterogeneous crossovermaximum likelihoodgeneralized antenna combinationparticle swarm optimizationminimum bit error rateMIMO
相關次數:
  • 被引用被引用:0
  • 點閱點閱:117
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
多輸入多輸出(multiple-input multiple-output, MIMO)無線通訊系統能大幅改善頻譜效率(spectral efficiency)且帶來更好傳輸品質,將在未來無線網路的高服務品質(quality of service, QoS)需求下扮演重要的角色。然而多天線的佈置,無可避免地導致多輸入多輸出系統包括硬體成本如射頻鏈(RF chain)增加以及干擾損害如多重串流干擾(multiple stream interference, MSI) 加劇等缺陷。

為有效地克服上述缺陷,本論文首先提出一簡單且更具效率的方法, 此一構想建立在上鏈多用戶多輸入多輸出系統中基於最大概似(maximum likelihood, ML)準則下將接收天線選擇(antenna selection)與訊號偵測(symbol detection)兩個獨立的機制結合考慮,以期能降低硬體複雜度且同時獲得更好的系統效能。為減緩計算上的負擔,吾人也利用改良版基因演算法(genetic algorithm,GA)來輔助求解所提問題。有鑒於天線選擇只挑選出部份最適合的天線,難免會導致系統效能的損失, 為彌補此一缺陷,吾人將探討一種新穎的機制稱為廣義天線組合(generalized antenna combination, GAC),而此天線組合機制並非僅單純地保留部分天線的資訊,取而代之的是用一轉換陣列對所有天線作線性組合來降低所需的射頻鏈,較之於天線選擇更能有效地保留天線資訊的完整性。再者,本論亦提出基於最小位元錯誤率(mimimum bit error rate, MBER)準則下將天線組合與訊號偵測結合設計,以期達到更好的系統效能與硬體成本的折衷。然而此結合方案也形成了非線性的問題,類似地,基因演算法或微粒群最佳化(particle swarm optimization, PSO)也被用來降低運算複雜度。

相關模擬結果顯示吾人所提之方法較之前人的方法,能獲得更好的系統效能且又大量地降低運算複雜度。

關鍵字:訊號偵測、天線選擇、基因演算法、異質性交配、廣義天線組合、最小化位元錯誤率、多輸入多輸出。
Multiple-input multiple-output (MIMO) systems, which process several merits such as spectral efficiency and better transmission quality, are one of the promising breakthroughs to meet the rapidly growing demand of quality of service (QoS) in the wireless communication systems. However, the performance gains come at the price of expensive hardware cost such as the RF chains associated with the antennas and the stronger interference impairment such as
multiple stream interference (MSI).

To alleviate the above drawbacks, we first present a simple, yet effective approach for joint receive antenna selection and symbol detection based on the maximum likelihood (ML) criterion in the uplink multiuser MIMO systems in order to simultaneously lower the hardware complexity and achieve superior performance. To mitigate the computational overhead, a variant of the conventional genetic algorithm (GA) is employed to solve the above joint problem. Since only part of the antenna is employed, the antenna selection scheme inevitably suffers performance degradation. To overcome this setback, a novel joint generalized scheme of antenna combination (GAC) and symbol detection based on the minimum bit error rate (MBER) criterion is also considered. More specifically, the new approach aims at effectively alleviating the MSI and lowering the RF chains called for by simultaneously determining the antenna combination weighting and the MBER detectors. This joint problem, however, is highly nonlinear and again the GA-based approach or
the particle swarm optimization (PSO)-based approach is employed to reduce the computational overhead.

Relevant simulation results show that both of the proposed approaches yield satisfactory performance with reduced computational complexity overhead compared with pervious works in various scenarios.
1 Introduction 1

2 Overview of MIMO Wireless Communications 6
2.1 Single User MIMO Signal Model . . . . . . . . . . . . . . . . . . . . 6
2.1.1 Capacity of Single User MIMO . . . . . . . . . . . . . . . . . . . 8
2.2 Multiuser MIMO Signal Model . . . . . . . . . . . . . . . . . . . . . 11

3 Review of Previous Works 13
3.1 Symbol Detector Architectures . . . . . . . . . . . . . . . . . . . . . 13
3.1.1 ML Detector . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.1.2 Linear Detector . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.1.3 MBER Detector . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2 Antenna Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.3 Genetic Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.3.1 Structure of Genetic Algorithm . . . . . . . . . . . . . . . . 21

4 A Genetic Approach for Joint Receive Antenna Selection and
Symbol Detection in the Multiuser MIMO Systems 26

4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.2 Review of Previous Works . . . . . . . . . . . . . . . . . . . . . . . 27
4.3 The Proposed Joint Approach . . . . . . . . . . . . . . . . . . . . . 29
4.4 Simulations and Discussions . . . . . . . . . . . . . . . . . . . . . . 35
4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

5 Joint Generalized Antenna Combination and Symbol Detection
Based on Minimum Bit Error Rate 42
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
5.2 Review of Previous Works . . . . . . . . . . . . . . . . . . . . . . . 43
5.3 The Proposed Joint Scheme . . . . . . . . . . . . . . . . . . . . . . 45
5.3.1 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . 45
5.3.2 A Genetic-Based Approach . . . . . . . . . . . . . . . . . . . 46
5.3.3 A PSO-Based Approach . . . . . . . . . . . . . . . . . . . . 49
5.4 Simulations and Discussions . . . . . . . . . . . . . . . . . . . . . . 53
5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

6 Conclusions 61
[1] G. J. Foschini and M. J. Gans, "On limits of wireless communications in a
fading environment when using multiple antennas", Wireless Personal Com-
munications, vol. 6, pp. 311-335, 1998.
[2] A. Paulraj, R. Nabar, and D. Gore, Introduction to Space-Time Wireless
Communications. Cambridge University Press, 2003.
[3] D. Tse and P. Viswanath, Fundamentals of Wireless Communication. Cam-
bridge University Press, 2005.
[4] V. Tarokh, N. Seshadri, and A. R. Calderbank, "Space-time codes for high
data rate wireless communication: Performance criterion and code construc-
tion," IEEE Trans. on Inform. Theory, vol. 44, pp. 744-765, Mar. 1999.
[5] G. J. Foschini, G. D. Golden, R. A. Valenzuela, and P.W. Wolniansky, "Sim-
plified processing for high spectral e±ciency wireless communications em-
ploying multi-element arrays," IEEE J. Select. Areas Commun., vol. 17, pp.
1841-1852, Nov. 1999.
[6] G. J. Foschini, "Layered space-time architecture for wireless communication
in a fading environment when using multiple antennas," Bell Labs Tech. J.,
vol. 1, pp. 41-59, Autumn 1996.
[7] S. Sanayei and A. Nosratinia, "Antenna selection in MIMO systems," IEEE
Commun. Mag. vol. 42, pp. 68-73, Oct. 2004.
[8] A. Gorokhov, D. A. Gore, and A. J. Paulraj, "Receive antenna selection for
MIMO spatial multiplexing: theory and algorithms," IEEE Trans. on Sig.
Proc., vol. 51, no. 11, pp. 2796-2807, Nov. 2003.
[9] A. Dua, K. Medepalli, and A. Paulraj, "Receive antenna selection in MIMO
systems using convex optimization," IEEE Trans. on Wireless Commun., vol.
5, no. 9, pp. 2353-2357, Sep. 2006.
[10] D. A. Gore, R. Heath, and A. J. Paulraj, "Statistical antenna selection for spatial multiplexing systems," in Proc. IEEE ICC, pp. 450-454, 2002.
[11] L. Dai, S. Sfar and K. B. Letaief, "Receive antenna selection for MIMO
systems in correlated channels," in Proc. IEEE ICC, pp. 2944-2948, 2004.
[12] P. D. Karamalis, N. D. Skentos, and A.G. Kanatas, "Adaptive antenna sub-
array formation for MIMO systems," IEEE Trans. on Wireless Commum.,
vol. 5, no. 11, pp. 2977-2982, Nov. 2006.
[13] S. Verdu, Multiuser Detection. Cambridge University Press, 1998.
[14] X. EWang, W. S. Lu, and A. Htoniou. "Constrained minimum-BER multiuser
detection," IEEE Trans. on Sig. Proc., vol. 48, no. 10, pp. 2903-2909, Oct.
2000.
[15] S. Chen, A. K. Samingan, B.Mulgrew, and L. Hanzo, \Adaptive minimum-
BER linear multiuser detection for DS-CDMA signals in multipath channels,"
IEEE Trans. on Sig. Proc., vol. 49, no. 6, pp. 1240-1247, Jun. 2001.
[16] M. Y. Alias, S. Chen and L. Hanzo, "Multiple-antenna-aided OFDM employ-
ing genetic-algorithm-assisted minimum bit error rate multiuser detection, "
IEEE Trans. on Vehi. Tech., vol. 54, no. 5, pp. 1713-1721, Sep. 2005.
[17] J. H. Holland, Genetic Algorithms. Sci. Am. 1992.
[18] M. Mitchell, A Introduction to Genetic Algorithms. Cambridge, MA: MIT
Press, 1996.
[19] Michalewicz, Z., Genetic Algorithm + Data Structures = Evolution Programs
(3rd ed). New York: Springer-Verlag, 1996.
[20] Mitsuo, G., and Runwei, C., Genetic Algorithms and Engineering Design.
Wiley, New York, 1997.
[21] K. Yen and L. Hanzo, "Genetic algorithm assisted joint multi-user symbol
detection and fading channel estimation for synchronous CDMA systems,"
IEEE J. Sel. Areas Commun, vol. 19, no. 6, pp. 985-998, June. 2001.
[22] C. Ergun and K. Hacioglu, Multiuser detection using a genetic algorithm in
CDMA communications system, IEEE Trans. on Wireless Commun, vol. 48,
pp. 1374-1383, Aug. 2000.
[23] Telatar, E., "Capacity of multi-antenna Gaussian channels," European Trans. on Telecom., vol. 10, no. 6, pp. 585-595, Nov/Dec 1999.
[24] G. Syswerda and J. Palmucci, "The application of genetic algorithms to re-
source scheduling," in Proc. the 4th Int. Conf. on Genetic Algorithm, pp.
502-508, 1991.
[25] D.S. Watkins, Fundamentals of Matrix Computations. Wiley, pp. 248-251,
1991.
[26] S. Haykin, Communication Systems. John Wiley and Sons, Inc., 2001.
[27] J. Kennedy and R.C. Eberhart, "Particle swarm optimization," in Proc. of
IEEE ICNN, Piscataway, USA, pp. 1942-1948, 1995.
[28] Y. H, Shi, and R. C., Eberhart, "A modi‾ed particle swarm optimizer," in
Proc. IEEE ICEC, Anchorage, Alaska, May 4-9, 1998.
[29] Jiang, M., Akhtman, J., and Hanzo, L., "Soft-information assisted near-
optimum nonlinear detection for BLAST-type space division multiplexing
OFDM systems," IEEE Trans. On Wireless Commun., vol. 6, no. 4, pp.1230-
1234 , April. 2007.
[30] Colman, G.G. W. K. and Willink, T.T. J, "Overloaded array processing using
genetic algorithms with soft-biased initialization," IEEE Trans. on Vehi Tech
: Accepted for future publication.
[31] Vincent K.N. Lau and Yu Kwong Ricky Kwok, Channel adaptive technologies
and cross layer designs for wireless systems with multiple antennas: theory
and applications. Wiley, 2006.
[32] X. Lin, N. B. Shro®, and R. Srikant, "A tutorial on cross-layer optimization in wireless networks," IEEE J. Sel. Areas Commun, vol. 24(8), pp. 1452-1463, Aug. 2006.
[33] J. L. Vicario, M. A. Lagunas, and C. A. Haro, "A cross-layer approach to
transmit antenna selection," IEEE Trans. On Wireless Commun., vol. 5, no.
8, Aug. 2006
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊