基于混合遗传算法的波束形成技术研究
|
摘要
近年来,随着通信产业的高速发展,智能天线技术已成功应用于移动通信系统,并通过对无线数字信号的高速时空处理,不但增加了信道容量,提高了频谱效率,也扩展了覆盖范围。未来我国将进入3G,4G的高速建设发展期,智能天线技术将会迎来广阔的发展空间。
本文首先介绍了智能天线的基本结构,工作原理和信号模型,同时分析了遗传算法的基本步骤和特点。另外在研究了智能天线波达角估计算法中的MUSIC算法和波束空间MUSIC算法的原理和信号模型的基础上,提出了高分辨处理的一种波束空间中的改进MUSIC算法,仿真实验结果表明,和传统的波束空间MUSIC算法相比,改进算法的分辨信噪比门限值更低。
另外,波束形成技术源于智能天线,增强期望、抑制用户干扰是其独特的技术优势,也是空分多址(SDMA)得以实现的基础。同时本文研究了智能天线中的自适应波束形成的基本算法,包括最陡下降法,最小均方算法和最小二乘算法。目前,遗传算法在解决该类方向图优化问题上已经成为了研究热点。但是遗传算法也存在收敛速度慢、易早熟、局部搜索能力差等缺点。对于多目标多参数的方向图非线性优化问题,遗传算法在搜索速度与求解精度上往往不能两者兼顾。因此,本文提出了一种基于遗传算法和禁忌搜索算法的混合遗传算法的波束形成技术研究,该算法既具有遗传算法的全局寻优能力,又具有禁忌搜索算法的局部寻优能力,可大大提高寻优的速度和精度。本文分别进行了混合遗传算法和传统遗传算法在相同参数设置下的仿真对比分析,以及混合遗传算法在不同参数设置下的仿真对比分析,仿真实验结果表明,基于混合遗传算法的波束形成方法能在保证搜索质量的前提下极大的提高了寻优效率,提高了运算速度。
In recent years, with the development of communications, smart antenna technology has been used in the field of mobile communications successfully. By the means of space-time processing to the wireless digital signals, the efficiency of the frequency's usage is improved extremely. In the future, our country will enter the period of 3G and 4G. So we can see that the smart antenna technology would be used widely.
First, the paper introduces the basic structure, work principle and signal model of smart antenna. In the meantime it analyzes the basic step and characteristic of Genetic Algorithms (GA).Then it discusses MUSIC algorithm and MUSIC algorithm based on beamspace including principle and signal model of Direction of Arrivals (DOA) on smart antenna. Based on this, the paper proposes a modified MUSIC algorithm based on beamspace for high resolution array processing, simulation results show the threshold signal-to-noise ratio of the modified algorithm is lower than the one of basic algorithm.
Besides, Beamforming stems from smart antenna, with increasing desire signal and suppressing interference as its technical superiority, which is also the foundation for the realization of SDMA. In the meantime the paper discusses the study of adaptive algorithms on smart antenna including steepest descent algorithm, least mean square algorithm and recursive least squares. GA has become the research hot point in the optimization of antenna array pattern synthesis. But GA has some disadvantages such as slow convergence speed, easy to be premature, bad local search capability. Based on the problem of non-linear multi-objective and multi-parameter optimization, it can't meet the requirements of search speed and solution precision simultaneously. Therefore the paper proposes a beamforming technology research based on GA and Tabu Search (TS) algorithms. The hybrid genetic algorithms has both the capability of the optimization of GA in the global area and that of TS algorithms in the local area, and it greatly improves the search speed and precision. The paper simulates and analyzes the differences between the hybrid genetic algorithms and the basic genetic algorithms with the same parameters. And also simulates and analyzes the performance of the hybrid genetic algorithms with the different parameters. Simulation results show that the beamforming techniques based on the hybrid GA enormously enhance the efficiency of optimization and raise the operating rate, guarantee the quality of searching as a prerequisite.
本文首先介绍了智能天线的基本结构,工作原理和信号模型,同时分析了遗传算法的基本步骤和特点。另外在研究了智能天线波达角估计算法中的MUSIC算法和波束空间MUSIC算法的原理和信号模型的基础上,提出了高分辨处理的一种波束空间中的改进MUSIC算法,仿真实验结果表明,和传统的波束空间MUSIC算法相比,改进算法的分辨信噪比门限值更低。
另外,波束形成技术源于智能天线,增强期望、抑制用户干扰是其独特的技术优势,也是空分多址(SDMA)得以实现的基础。同时本文研究了智能天线中的自适应波束形成的基本算法,包括最陡下降法,最小均方算法和最小二乘算法。目前,遗传算法在解决该类方向图优化问题上已经成为了研究热点。但是遗传算法也存在收敛速度慢、易早熟、局部搜索能力差等缺点。对于多目标多参数的方向图非线性优化问题,遗传算法在搜索速度与求解精度上往往不能两者兼顾。因此,本文提出了一种基于遗传算法和禁忌搜索算法的混合遗传算法的波束形成技术研究,该算法既具有遗传算法的全局寻优能力,又具有禁忌搜索算法的局部寻优能力,可大大提高寻优的速度和精度。本文分别进行了混合遗传算法和传统遗传算法在相同参数设置下的仿真对比分析,以及混合遗传算法在不同参数设置下的仿真对比分析,仿真实验结果表明,基于混合遗传算法的波束形成方法能在保证搜索质量的前提下极大的提高了寻优效率,提高了运算速度。
In recent years, with the development of communications, smart antenna technology has been used in the field of mobile communications successfully. By the means of space-time processing to the wireless digital signals, the efficiency of the frequency's usage is improved extremely. In the future, our country will enter the period of 3G and 4G. So we can see that the smart antenna technology would be used widely.
First, the paper introduces the basic structure, work principle and signal model of smart antenna. In the meantime it analyzes the basic step and characteristic of Genetic Algorithms (GA).Then it discusses MUSIC algorithm and MUSIC algorithm based on beamspace including principle and signal model of Direction of Arrivals (DOA) on smart antenna. Based on this, the paper proposes a modified MUSIC algorithm based on beamspace for high resolution array processing, simulation results show the threshold signal-to-noise ratio of the modified algorithm is lower than the one of basic algorithm.
Besides, Beamforming stems from smart antenna, with increasing desire signal and suppressing interference as its technical superiority, which is also the foundation for the realization of SDMA. In the meantime the paper discusses the study of adaptive algorithms on smart antenna including steepest descent algorithm, least mean square algorithm and recursive least squares. GA has become the research hot point in the optimization of antenna array pattern synthesis. But GA has some disadvantages such as slow convergence speed, easy to be premature, bad local search capability. Based on the problem of non-linear multi-objective and multi-parameter optimization, it can't meet the requirements of search speed and solution precision simultaneously. Therefore the paper proposes a beamforming technology research based on GA and Tabu Search (TS) algorithms. The hybrid genetic algorithms has both the capability of the optimization of GA in the global area and that of TS algorithms in the local area, and it greatly improves the search speed and precision. The paper simulates and analyzes the differences between the hybrid genetic algorithms and the basic genetic algorithms with the same parameters. And also simulates and analyzes the performance of the hybrid genetic algorithms with the different parameters. Simulation results show that the beamforming techniques based on the hybrid GA enormously enhance the efficiency of optimization and raise the operating rate, guarantee the quality of searching as a prerequisite.
引文
[1]R.Compton. Adaptive antenna:corcepts and applications. Englewood Cliffs, 1998
[2]王璁.智能天线中改进最小均方算法的研究.大庆石油学院学位论文,2004
[3]郭志远,吴瑛.一种改进的SM[波束形成算法[J].信息工程大学学报,2007
[4]赵鹏飞,刘刚.一种基于特征矢量波束形成算法[J].科学技术与工程,2007
[5]宋鑫.时延、相移波束形成技术研究[J].信息技术,2005
[6]张靖,龚耀寰,黎海涛.发射自适应波束形成研究[J].电子与信息学报,2003
[7]康凤歧.智能天线系统的宽波束形成技术研究[J].电子科技,2006
[8]李克,时信华,张尔扬.一种有效的智能天线波束形成技术[J].通信技术,2002
[9]幸高翔,蔡志明.任意形状旁瓣波束形成技术研究[J].电子学报,2005
[10]王凯帅,陈航.一种精确控制旁瓣的自适应波束形成算法[J].微处理机,2006
[11]郭玉华,戴旭初.一种空时联合的自适应波束形成算法[J].数据采集与处理,2007
[12]Johnson S M,Yahya,Rahmat-Samii.Genetic algorithms in engineering electromagnetics.IEEE Antenna and Propagation Magzine.1997,39(4):7-18
[13]李晋文,毛钧杰,柴舜连等.遗传算法在天线阵自适应算法中的应用.电子与信息学报.2000,22(2)
[14]Mori N,Kita H.Genetic algorithms for adaptation to dynamic environments-a survey.Proceedings of IEEE Conference on Industrial Electronics Socitey.2000,4
[15]Marcano D,Duran F.Synthesis of antenna arrays using genetic algorithms. IEEE Antennas and Propagation Magazine.2000,42(3):12-20
[16]Tennant A,Dawoud M M,Anderson A P.Array pattern nulling by element
position perturbations using a genetic algorithm. Electronics letter.1994,30(3):174-176
[17]Liao Wen-Pin,Chu Fu-Lai.Array pattern nulling by phase and position perturbations with the use of the genetic algorithm.Microwave and Optical Technology Letters.1997,15(4)
[18]Haupt,Randy L,Ellen Sue.Phase-only adaptive nulling with a genetic algorithm.Proceedings of IEEE Aerospace Conference,1997,3:151-160
[19]Lee Yee Hui,Andrew M C,Porter S J.Genetic algorithm using real parameters for array antenna design optimization.Proceedings of IEEE High Frequency Postgraduate Student Colloquium,1999:8-13
[20]Winter J H.Smart antennas for wireless systems.IEEE Personal Communicati-ons Magazine,1998,5(1):23-27
[21]Cuppini Monica a genetic algorithm for channel assignment problems.Europe-an Transactions on Telecommunications and Related Technologies,1994,5(2):285
-294
[22]Ren Q S,Ye Z X.Genetic searching algorithm for optimal runlength-limited codes with error control[J].Jourmal of China Institute of Communications,1997,19 (3):54-59
[23]Ozcan E,Mohan C K.Partial shape matching using genetic algorithms[J].Patte-rn Recoginition letters,1997,18(10):987-992
[24]任庆生,叶中行,曾进.对常用选择算子的分析[J].上海交通大学学报,2000,4
[25]李小文,李贵勇等.TD-SCDMA第三代移动通信系统、信令及实现.北京：人民邮电出版社,2003
[26]金荣洪,耿军平,范瑜.无线通信中的智能天线.北京邮电大学出版社,2006
[27]Kim M,Ichige K,Arai H.Implementation of FPGA based Fast DOA Estimator using Unitary MUSIC algorithm.Proceedings of IEEE Vehicular Technology Conference,2003,1:213-217
[28]Sun C,Hirata A,Shimizu T,et al.Sectorized calibration of an ESPAR antenna for CUBA-MUSIC direction of arrival estimation.Proceedings of IEEE International Symposium on Antennas and Propagation Society.2005,4:14-17
[29]J van de Laar.TIME-MUSIC DOA estimation based on the exploitation of an arbitrary-order temporal structure in the data.Proceedings of Sensor Array and Multichannel Signal Processing Workshop.2004:308-312
[30]王永良,陈辉,彭应宁,万群.空间谱估计理论与算法[M].北京：清华大学出版社,2004
[31]Oh S.K., Un C.K. Improved MUSIC algorithm for high-resolution array processing. Electronic Letters,1989, vol.25, no.22,1523-1525.
[32]Vasylyshyn V.I. High-resolution phased array signal processing via DFT Beamspace TLSESPRIT with structure weighting. Proc. of 2003 IEEE Phased Array Systems and Technology Symposium, Boston, Massachusetts,2003, 605-610
[33]Wax M., Kailath T. Detection of signals by information theoretic criteria. IEEE Trans. ASSP,1985, vol.33,387-392.
[34]黄辉宁.信号检测与估计[M].北京：北京理工大学出版社.1997,3：115-150
[35]何振亚.自适应信号处理[M].北京：科学出版社.2003,5：21-66
[36]赵春辉,张朝柱,李刚.自适应信号处理[M].哈尔滨：哈尔滨工程大学出版社.2006,3：191-197
[37]S.Haykin.Adaptive Filter Theory[J].Prentice Hall New Jersey.1991
[38]S.Salhi Defining tabu list size and aspiration criterion within tabu search methods Computers & Operations Research 29 (2002):67-86
[39]Liang Yanchun,Wang Zaishen,Zhou chunguang.A study on convergence of canonial genetic algorithms with natural selections.Chinese Journal of Electronics, 1997,6(3):71-75
[40]GLOVER F,KELLY J,LAGUNA M.Genetic algorithms and tabu search: hybrids for optimization[J].Comput & OpsRes,1995,22(1):111-134
[41]ANDRZEJ Jaszkiewicz.Genetic local search for mult-objective combinatorial optimization[J].European Journal of Operational Research,2002,137(1):50-71
[42]王竹芳,潘德惠.用遗传-禁忌搜索混合算法求解组合投资问题.东北大学学报.2006
[2]王璁.智能天线中改进最小均方算法的研究.大庆石油学院学位论文,2004
[3]郭志远,吴瑛.一种改进的SM[波束形成算法[J].信息工程大学学报,2007
[4]赵鹏飞,刘刚.一种基于特征矢量波束形成算法[J].科学技术与工程,2007
[5]宋鑫.时延、相移波束形成技术研究[J].信息技术,2005
[6]张靖,龚耀寰,黎海涛.发射自适应波束形成研究[J].电子与信息学报,2003
[7]康凤歧.智能天线系统的宽波束形成技术研究[J].电子科技,2006
[8]李克,时信华,张尔扬.一种有效的智能天线波束形成技术[J].通信技术,2002
[9]幸高翔,蔡志明.任意形状旁瓣波束形成技术研究[J].电子学报,2005
[10]王凯帅,陈航.一种精确控制旁瓣的自适应波束形成算法[J].微处理机,2006
[11]郭玉华,戴旭初.一种空时联合的自适应波束形成算法[J].数据采集与处理,2007
[12]Johnson S M,Yahya,Rahmat-Samii.Genetic algorithms in engineering electromagnetics.IEEE Antenna and Propagation Magzine.1997,39(4):7-18
[13]李晋文,毛钧杰,柴舜连等.遗传算法在天线阵自适应算法中的应用.电子与信息学报.2000,22(2)
[14]Mori N,Kita H.Genetic algorithms for adaptation to dynamic environments-a survey.Proceedings of IEEE Conference on Industrial Electronics Socitey.2000,4
[15]Marcano D,Duran F.Synthesis of antenna arrays using genetic algorithms. IEEE Antennas and Propagation Magazine.2000,42(3):12-20
[16]Tennant A,Dawoud M M,Anderson A P.Array pattern nulling by element
position perturbations using a genetic algorithm. Electronics letter.1994,30(3):174-176
[17]Liao Wen-Pin,Chu Fu-Lai.Array pattern nulling by phase and position perturbations with the use of the genetic algorithm.Microwave and Optical Technology Letters.1997,15(4)
[18]Haupt,Randy L,Ellen Sue.Phase-only adaptive nulling with a genetic algorithm.Proceedings of IEEE Aerospace Conference,1997,3:151-160
[19]Lee Yee Hui,Andrew M C,Porter S J.Genetic algorithm using real parameters for array antenna design optimization.Proceedings of IEEE High Frequency Postgraduate Student Colloquium,1999:8-13
[20]Winter J H.Smart antennas for wireless systems.IEEE Personal Communicati-ons Magazine,1998,5(1):23-27
[21]Cuppini Monica a genetic algorithm for channel assignment problems.Europe-an Transactions on Telecommunications and Related Technologies,1994,5(2):285
-294
[22]Ren Q S,Ye Z X.Genetic searching algorithm for optimal runlength-limited codes with error control[J].Jourmal of China Institute of Communications,1997,19 (3):54-59
[23]Ozcan E,Mohan C K.Partial shape matching using genetic algorithms[J].Patte-rn Recoginition letters,1997,18(10):987-992
[24]任庆生,叶中行,曾进.对常用选择算子的分析[J].上海交通大学学报,2000,4
[25]李小文,李贵勇等.TD-SCDMA第三代移动通信系统、信令及实现.北京：人民邮电出版社,2003
[26]金荣洪,耿军平,范瑜.无线通信中的智能天线.北京邮电大学出版社,2006
[27]Kim M,Ichige K,Arai H.Implementation of FPGA based Fast DOA Estimator using Unitary MUSIC algorithm.Proceedings of IEEE Vehicular Technology Conference,2003,1:213-217
[28]Sun C,Hirata A,Shimizu T,et al.Sectorized calibration of an ESPAR antenna for CUBA-MUSIC direction of arrival estimation.Proceedings of IEEE International Symposium on Antennas and Propagation Society.2005,4:14-17
[29]J van de Laar.TIME-MUSIC DOA estimation based on the exploitation of an arbitrary-order temporal structure in the data.Proceedings of Sensor Array and Multichannel Signal Processing Workshop.2004:308-312
[30]王永良,陈辉,彭应宁,万群.空间谱估计理论与算法[M].北京：清华大学出版社,2004
[31]Oh S.K., Un C.K. Improved MUSIC algorithm for high-resolution array processing. Electronic Letters,1989, vol.25, no.22,1523-1525.
[32]Vasylyshyn V.I. High-resolution phased array signal processing via DFT Beamspace TLSESPRIT with structure weighting. Proc. of 2003 IEEE Phased Array Systems and Technology Symposium, Boston, Massachusetts,2003, 605-610
[33]Wax M., Kailath T. Detection of signals by information theoretic criteria. IEEE Trans. ASSP,1985, vol.33,387-392.
[34]黄辉宁.信号检测与估计[M].北京：北京理工大学出版社.1997,3：115-150
[35]何振亚.自适应信号处理[M].北京：科学出版社.2003,5：21-66
[36]赵春辉,张朝柱,李刚.自适应信号处理[M].哈尔滨：哈尔滨工程大学出版社.2006,3：191-197
[37]S.Haykin.Adaptive Filter Theory[J].Prentice Hall New Jersey.1991
[38]S.Salhi Defining tabu list size and aspiration criterion within tabu search methods Computers & Operations Research 29 (2002):67-86
[39]Liang Yanchun,Wang Zaishen,Zhou chunguang.A study on convergence of canonial genetic algorithms with natural selections.Chinese Journal of Electronics, 1997,6(3):71-75
[40]GLOVER F,KELLY J,LAGUNA M.Genetic algorithms and tabu search: hybrids for optimization[J].Comput & OpsRes,1995,22(1):111-134
[41]ANDRZEJ Jaszkiewicz.Genetic local search for mult-objective combinatorial optimization[J].European Journal of Operational Research,2002,137(1):50-71
[42]王竹芳,潘德惠.用遗传-禁忌搜索混合算法求解组合投资问题.东北大学学报.2006