MIMO系统中的天线选择与空时编码
摘要
多输入多输出(MIMO)是下一代移动通信的重要技术之一,它不仅能使系统容量成倍提高,还能显著提高无线通信系统的频谱利用率。但过高的硬件成本限制了它的应用。天线选择是MIMO系统中一项重要技术,它能从MIMO系统的多个发射天线和多个接收天线中选择出性能最好的一个或多个天线,从而以较小的性能损失换取成本的大幅降低,极大地提高MIMO系统的性能价格比。
论文首先介绍和分析了一些经典的天线选择算法,最优算法虽然能获得最高的系统容量,但因其复杂度太高不具有实用价值。本文从香农公式出发,并结合前人的算法,通过数学推导,提出了一种新的快速天线选择算法,其所获得的系统容量与最优算法非常接近。仿真结果表明,在发射端与接收端分别有4根和8根天线并且接收端选择4根天线接收信号的情况下,新算法获得了与最优算法相近的系统容量,并且使复数加和复数乘的计算量分别减少了36.4%和40.8%。因此,新算法收敛更快。
论文采用空时分组码与新算法相结合的方法分析了新算法的误比特率。在发送端使用空时分组码编码方案,在接收端先用新算法进行天线选择,再使用空时分组码最大似然译码方案进行译码。仿真结果表明,在接收端进行天线选择,使用新算法后系统误码性能与使用最优算法时的误码性能基本一致。因此,新算法具有更好的性能。
Multi-Input and Multi-Output (MIMO) is one of the most important techniques for next generation mobile communications. MIMO can increase capacity of the communication system, and improve the spectral utilization. However, the hardware of the MIMO system is very expensive, which greatly limits its applications. As an important technique in the MIMO system, antenna selection can choose properly one or several best antennas from multiple transmitting and receiving antennas, and reduce the expense with less performance loss. Therefore, the performance-cost-ratio of the MIMO system is improved greatly.
In this thesis, the classic algorithms are introduced and analyzed first. Although the optimal algorithm can achieve the highest channel capacity, it is not of practical value because it has a very high complexity. Starting from the Shannon formula and the existing algorithms, a new antenna selection algorithm is proposed through the derivation of mathematical formulas, and its channel capacity is close to that obtained by the optimal algorithm. Simulation results indicate that in the case of 4 transmitting and 8 receiving antennas, choosing 4 antennas to receive signals, the algorithm has a channel capacity close to the capacity obtained by the optimal algorithm. Meanwhile the calculating amount for the addition and multiplication of complex numbers decreases 36.4% and 40.8% respectively. Thus the proposed algorithm converges very fast.
The proposed algorithm and Alamouti’s Space-Time Block Code (STBC) scheme are used together to analyze its Bit Error Rate (BER). In fact, Alamouti’s coding scheme is used at the transmitting end. Meanwhile, at the receiving end, the antenna selection algorithm is used first, and then Alamouti’s maximum likelihood decoding scheme is used. Simulation results show that with antenna selection at the receiving end the BER of the proposed algorithm is almost identical with that of the optimal algorithm. Therefore, the proposed algorithm has a better performance.
论文首先介绍和分析了一些经典的天线选择算法,最优算法虽然能获得最高的系统容量,但因其复杂度太高不具有实用价值。本文从香农公式出发,并结合前人的算法,通过数学推导,提出了一种新的快速天线选择算法,其所获得的系统容量与最优算法非常接近。仿真结果表明,在发射端与接收端分别有4根和8根天线并且接收端选择4根天线接收信号的情况下,新算法获得了与最优算法相近的系统容量,并且使复数加和复数乘的计算量分别减少了36.4%和40.8%。因此,新算法收敛更快。
论文采用空时分组码与新算法相结合的方法分析了新算法的误比特率。在发送端使用空时分组码编码方案,在接收端先用新算法进行天线选择,再使用空时分组码最大似然译码方案进行译码。仿真结果表明,在接收端进行天线选择,使用新算法后系统误码性能与使用最优算法时的误码性能基本一致。因此,新算法具有更好的性能。
Multi-Input and Multi-Output (MIMO) is one of the most important techniques for next generation mobile communications. MIMO can increase capacity of the communication system, and improve the spectral utilization. However, the hardware of the MIMO system is very expensive, which greatly limits its applications. As an important technique in the MIMO system, antenna selection can choose properly one or several best antennas from multiple transmitting and receiving antennas, and reduce the expense with less performance loss. Therefore, the performance-cost-ratio of the MIMO system is improved greatly.
In this thesis, the classic algorithms are introduced and analyzed first. Although the optimal algorithm can achieve the highest channel capacity, it is not of practical value because it has a very high complexity. Starting from the Shannon formula and the existing algorithms, a new antenna selection algorithm is proposed through the derivation of mathematical formulas, and its channel capacity is close to that obtained by the optimal algorithm. Simulation results indicate that in the case of 4 transmitting and 8 receiving antennas, choosing 4 antennas to receive signals, the algorithm has a channel capacity close to the capacity obtained by the optimal algorithm. Meanwhile the calculating amount for the addition and multiplication of complex numbers decreases 36.4% and 40.8% respectively. Thus the proposed algorithm converges very fast.
The proposed algorithm and Alamouti’s Space-Time Block Code (STBC) scheme are used together to analyze its Bit Error Rate (BER). In fact, Alamouti’s coding scheme is used at the transmitting end. Meanwhile, at the receiving end, the antenna selection algorithm is used first, and then Alamouti’s maximum likelihood decoding scheme is used. Simulation results show that with antenna selection at the receiving end the BER of the proposed algorithm is almost identical with that of the optimal algorithm. Therefore, the proposed algorithm has a better performance.
引文
[1] Qi Bi, G.L.Zysman. Wireless mobile communication at the start of the 21st century. IEEE Communications Magazine. 2001.1, Vol. 39, pp. 110-116.
[2] I.E.Telatar. Capacity of multi-antenna Gaussian channels. AT&T Bell Labs Internal Technical Memorandum, 1995.
[3] G..J.Foschini, M.J.Gans. On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas. Wireless Personal Communications. 1998.3, Vol. 6, No. 3, pp. 311-335.
[4] G..J.Foschini. Layered Space-Time Architecture for Wireless Communication in Fading Environment when Using Multiple Antennas. Bell Labs Technical Journal. 1996, Vol. 1, No. 2, pp. 14-59.
[5] I.E.Telatar and D.Tse. Capacity and Mutual Information of Broadband Multipath Fading Channels. IEEE International Symposium on Information Theory. 1998.8, pp.395.
[6] V.Tarokh, N.Swshadri, A.R.Calderbank. Space-Time Coding for High Data Rate Wireless Communication: Performance Analysis and Code Construction. IEEE Transactions on Information Theory. 1998.3, Vol. 44, pp. 744-765.
[7] A.F.Molish, M.Z.Win. MIMO System with Antenna Selection. IEEE Microwave Magazine. 2004.3, Vol. 5, pp. 46-56.
[8] A.Gorokhov, D.A.Gore, A.J.Paulraj. Receive Antenna Selection for MIMO Spatial Multiplexing: Theory and algorithms. IEEE Transactions on Signal Processing. 2003.11, Vol. 51, No.11, pp. 2796-2807.
[9] A.Gorokhov. Antenna Selection Algorithms for MEA Transmission Systems. IEEE International Conference on Acoustics, speech, and Signal Processing. 2002.5, Vol. 3, pp. 2857-2860.
[10]樊冰,周雪芳,孙文胜. MIMO系统中的天线选择技术.现代电子技术. 2006,Vol. 15,pp. 11-14.
[11] John.G. Proakis.数字通信(第四版).北京:电子工业出版社,2003.
[12]黄韬,袁超伟,杨睿哲. MIMO相关技术与应用(第一版).北京:机械工业出版社,2007.1.
[13]曹志刚,钱亚生.现代通信原理.北京:清华大学出版社,1991.
[14] I.E.Telatar. Capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications. 1999, Vol. 10, No. 6, pp. 585-595.
[15] Mohinder.Jankiraman. Space-Time Codes and MIMO Systems. Boston: Artech House. 2004.pp. 21-23
[16] D.Gesbert, H.Boelcskei, D.Gore. MIMO Wireless Channels: Capacity and Performance Prediction. Proc. of Globecom. 2000, pp. 1083-1088.
[17] W. C. Jakes. Microwave Mobile Communications. Piscataway: IEEE Press, 1993.
[18]罗涛,乐光新,多天线无线通信原理与应用(第一版).北京:北京邮电大学出版社,2005, pp. 20-23.
[19] S.M.Alamouti. A simple Transmitter Diversity Scheme for Wireless Communication. IEEE JSAC. 1998, Vol. 16, No. 10, pp. 1451-1458.
[20] G.D.Jerry. The Mobile Communications Handbook. Piscataway: IEEE Press. 1999.
[21] A.J.Paulraj, D.A.Gore, R.U.Nabar. An Overview of MIMO Communications - A Key to Gigabit Wireless. Proceedings of the IEEE. 2004.2, Vol. 92, Issue 2, pp. 198-218.
[22] A.F.Molish, MIMO Systems with Antenna Selection---An overview. IEEE Radio and Wireless Conference. 2003.8, pp. 167-170.
[23] A.F.Molish, M.Z.Win, J.H.Winters. Capacity of MIMO Systems With Antenna Selection. IEEE Transactions on Wireless Communications. 2005.7, vol. 4, pp. 570-574.
[24] T.Eng, Ning Kong, L.B.Milstein. Comparison of Diversity Combining Techniques for Rayleigh-Fading Channels. 1996.9, Vol. 44, No. 9, pp. 1117 - 1129.
[25]张贤达.信号处理中的线性代数.北京:科学出版社,1997,pp. 13-15.
[26]吕进文,张立军,陈常嘉. MIMO系统中改进的天线选择算法.北京交通大学学报. 2006.4,Vol. 30, No.2, pp. 29-32.
[27] V.Tarokh, N.Seshadri, A.R.Calderbank. Space-Time Codes for High Data Rate Wireless Communications: Performance Criteria in the Presence of Channel Estimation Errors, Mobility and Multiple Paths. IEEE Transactions on Information Theory. 1998, Vol. 44, pp. 744-765.
[28] B.M.Hochwald, T.L.Marzetta. Unitary Space-Time Modulation for Multiple-Antenna Communications in Rayleigh Flat Fading. IEEE Transactions on Information Theory. 2000.3, Vol. 46, pp. 543-564.
[29] V.Tarokh, H.Jafarkhani. A Differential Detection Scheme for Transmit Diversity. IEEE Journal on Selected Areas in Communications. 2000.7, Vol. 18, No. 7, pp. 1169-1174.
[30] B.L.Hughes. Differential Space-Time modulation. IEEE Transactions on Information Theory. 2000.11, Vol. 46, pp. 2567-2578.
[31] G.D.Golden, G.J.Fosehini, R.A.Valenzuela. Detection Algorithm and Initial Laboratory Results Using V-BLAST Space-Time Communication Rrchitecture. Electronics Letters. 1999, Vol. 35, pp. 6-7.
[32] V.Tarokh, N.Seshadri and A.R.Caldethank. Space-Time Codes for High Date Rate WirelessCommunication: Performance Criterion and Codes Construction. IEEE Trans IT. 1998, Vol. 44, pp. 744-765.
[33] V.Tarokh, H.Jafarkani, A.R.Calferbank. Space-Time Block Codes from Orthogonal Designs. IEEE Transactions on Information Theory. 1999.7, Vol. 45, pp. 1456-1467.
[34] V.Tarokh, H.Jafarkani, A.R.Calferbank. Space-Time Block Coding for Wireless Communication: performance results. IEEE Journal on selected areas in communications. 1999.3, Vol. 17, pp. 451-460.
[2] I.E.Telatar. Capacity of multi-antenna Gaussian channels. AT&T Bell Labs Internal Technical Memorandum, 1995.
[3] G..J.Foschini, M.J.Gans. On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas. Wireless Personal Communications. 1998.3, Vol. 6, No. 3, pp. 311-335.
[4] G..J.Foschini. Layered Space-Time Architecture for Wireless Communication in Fading Environment when Using Multiple Antennas. Bell Labs Technical Journal. 1996, Vol. 1, No. 2, pp. 14-59.
[5] I.E.Telatar and D.Tse. Capacity and Mutual Information of Broadband Multipath Fading Channels. IEEE International Symposium on Information Theory. 1998.8, pp.395.
[6] V.Tarokh, N.Swshadri, A.R.Calderbank. Space-Time Coding for High Data Rate Wireless Communication: Performance Analysis and Code Construction. IEEE Transactions on Information Theory. 1998.3, Vol. 44, pp. 744-765.
[7] A.F.Molish, M.Z.Win. MIMO System with Antenna Selection. IEEE Microwave Magazine. 2004.3, Vol. 5, pp. 46-56.
[8] A.Gorokhov, D.A.Gore, A.J.Paulraj. Receive Antenna Selection for MIMO Spatial Multiplexing: Theory and algorithms. IEEE Transactions on Signal Processing. 2003.11, Vol. 51, No.11, pp. 2796-2807.
[9] A.Gorokhov. Antenna Selection Algorithms for MEA Transmission Systems. IEEE International Conference on Acoustics, speech, and Signal Processing. 2002.5, Vol. 3, pp. 2857-2860.
[10]樊冰,周雪芳,孙文胜. MIMO系统中的天线选择技术.现代电子技术. 2006,Vol. 15,pp. 11-14.
[11] John.G. Proakis.数字通信(第四版).北京:电子工业出版社,2003.
[12]黄韬,袁超伟,杨睿哲. MIMO相关技术与应用(第一版).北京:机械工业出版社,2007.1.
[13]曹志刚,钱亚生.现代通信原理.北京:清华大学出版社,1991.
[14] I.E.Telatar. Capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications. 1999, Vol. 10, No. 6, pp. 585-595.
[15] Mohinder.Jankiraman. Space-Time Codes and MIMO Systems. Boston: Artech House. 2004.pp. 21-23
[16] D.Gesbert, H.Boelcskei, D.Gore. MIMO Wireless Channels: Capacity and Performance Prediction. Proc. of Globecom. 2000, pp. 1083-1088.
[17] W. C. Jakes. Microwave Mobile Communications. Piscataway: IEEE Press, 1993.
[18]罗涛,乐光新,多天线无线通信原理与应用(第一版).北京:北京邮电大学出版社,2005, pp. 20-23.
[19] S.M.Alamouti. A simple Transmitter Diversity Scheme for Wireless Communication. IEEE JSAC. 1998, Vol. 16, No. 10, pp. 1451-1458.
[20] G.D.Jerry. The Mobile Communications Handbook. Piscataway: IEEE Press. 1999.
[21] A.J.Paulraj, D.A.Gore, R.U.Nabar. An Overview of MIMO Communications - A Key to Gigabit Wireless. Proceedings of the IEEE. 2004.2, Vol. 92, Issue 2, pp. 198-218.
[22] A.F.Molish, MIMO Systems with Antenna Selection---An overview. IEEE Radio and Wireless Conference. 2003.8, pp. 167-170.
[23] A.F.Molish, M.Z.Win, J.H.Winters. Capacity of MIMO Systems With Antenna Selection. IEEE Transactions on Wireless Communications. 2005.7, vol. 4, pp. 570-574.
[24] T.Eng, Ning Kong, L.B.Milstein. Comparison of Diversity Combining Techniques for Rayleigh-Fading Channels. 1996.9, Vol. 44, No. 9, pp. 1117 - 1129.
[25]张贤达.信号处理中的线性代数.北京:科学出版社,1997,pp. 13-15.
[26]吕进文,张立军,陈常嘉. MIMO系统中改进的天线选择算法.北京交通大学学报. 2006.4,Vol. 30, No.2, pp. 29-32.
[27] V.Tarokh, N.Seshadri, A.R.Calderbank. Space-Time Codes for High Data Rate Wireless Communications: Performance Criteria in the Presence of Channel Estimation Errors, Mobility and Multiple Paths. IEEE Transactions on Information Theory. 1998, Vol. 44, pp. 744-765.
[28] B.M.Hochwald, T.L.Marzetta. Unitary Space-Time Modulation for Multiple-Antenna Communications in Rayleigh Flat Fading. IEEE Transactions on Information Theory. 2000.3, Vol. 46, pp. 543-564.
[29] V.Tarokh, H.Jafarkhani. A Differential Detection Scheme for Transmit Diversity. IEEE Journal on Selected Areas in Communications. 2000.7, Vol. 18, No. 7, pp. 1169-1174.
[30] B.L.Hughes. Differential Space-Time modulation. IEEE Transactions on Information Theory. 2000.11, Vol. 46, pp. 2567-2578.
[31] G.D.Golden, G.J.Fosehini, R.A.Valenzuela. Detection Algorithm and Initial Laboratory Results Using V-BLAST Space-Time Communication Rrchitecture. Electronics Letters. 1999, Vol. 35, pp. 6-7.
[32] V.Tarokh, N.Seshadri and A.R.Caldethank. Space-Time Codes for High Date Rate WirelessCommunication: Performance Criterion and Codes Construction. IEEE Trans IT. 1998, Vol. 44, pp. 744-765.
[33] V.Tarokh, H.Jafarkani, A.R.Calferbank. Space-Time Block Codes from Orthogonal Designs. IEEE Transactions on Information Theory. 1999.7, Vol. 45, pp. 1456-1467.
[34] V.Tarokh, H.Jafarkani, A.R.Calferbank. Space-Time Block Coding for Wireless Communication: performance results. IEEE Journal on selected areas in communications. 1999.3, Vol. 17, pp. 451-460.