多用户系统的数字波束形成技术
|
摘要
智能天线通过波达方向估计检测用户方向,然后调节基站各阵元信号的加权幅度和相位来改变阵列的天线方向图,对基站的发射和接收波束进行自适应赋形,将天线波束主瓣指向用户,零陷对准干扰。数字波束形成技术是智能天线的一个重要内容。
本文在阅读大量国内外相关科技研究文献的基础之上,针对多用户系统,围绕数字波束形成技术进行了如下几个方面的研究:
①介绍了阵列天线不同几何模型下接收信号的数学模型,进而阐述了空间谱估计和数字波束形成的基本算法,并进行了仿真分析。
②解决了波束形成中期望和干扰用户的辨识问题。传统波束形成中,虽然可以通过波达方向估计得到期望信号和干扰信号的空间信息,但并不能对二者进行区分。根据移动通信CDMA系统中多用户检测的原理,在用户发送端给不同期望用户分配不同的伪随机码作为标识码,接收端通过相关检测可以很好地区分不同期望信号和干扰信号。仿真结果表明了该方法能保持辨识系统低的虚警概率和漏警概率,准确辨识出特定期望用户的方向。
③提出了一种基于分组的多用户波束形成方法。为抑制小区内同道干扰,提高系统性能,首先通过波达方向估计把一个小区内的多个用户分成若干组,每组用户一个波束形成支路,主瓣对准该组的用户,零陷对准其他组的用户。权矢量与各组用户角度的平均值相对应。各支路波束形成输出分别进行多用户检测,消除组内各用户间的干扰。性能分析和仿真结果证明该方法简化了波束形成的权值求解,克服了用户空间的非正交性,有效降低了系统的误码率。
④波束形成类算法的工程实现具有重要的实际意义。但由于算法中存在大量复杂的矩阵以及矢量的变换和运算,通常的C语言直接编程相当复杂并且很费时。而通过MATLAB这样的CAD工具的帮助,利用其Embedded IDE Link软件直接从SIMULINK模型生成算法的DSP代码,极大地节约了软件开发的时间和成本。以空间谱估计中的多重信号分类算法为例,介绍了基于MATLAB的DSP代码的生成步骤,该步骤同样适用于其他的阵列信号处理算法。
Smart antennas is utilized to generate the radiation pattern of an antenna array by the complex vector weights that adjust the amplitude and phase of the received signal, so that the main beam is directed to the desired user and null is directed to interference user. Digital beamforming technology is an important content of smart antennas. Based on extensive reading of the relevant technology literature, this thesis discusses the digital beamforming technology in multi-user system. The dominant works are illustrated as follows:
①The fundamental signal models employed by different geometric antenna array are explained firstly. Then, the fundamental algorithm for direction of arrival (DOA) estimation and digital beamforming are illustrated with computer simulation analysis.
②The research work gains the solution for identification between interested users and interference users. In the content of traditional digital beamforming, it cannot implement the identification between the desired signals and interferences, although the DOA estimation strategy digs out the spacial information of these signals. Similar as the multi-user detection in CDMA mobile communication system, different users are allocated with one pseudo-noise (PN) code in the transmitters respectively. Furthermore, the receiver generates the replicas of transmitted PN codes and does correlation calculation with the received signals to harness the identification. The simulation shows that proposed approach picks up the desired signals and insures the low false alarm rate and missing detection rate.
③A group-based digital beamforming algorithm is proposed. In CDMA wireless cellular communication system, a new methodology is proposed to combine digital beamforming with multi-user detection technology which harnesses the co-channel interference mitigation and better performance. The proposed approach assigns all the users within a cell into separated groups according to their DOA firstly. Then only one digital beamforming branch is employed for a singular group so that the main lobe is steered to the desired users in the group and null is directed to the mobile stations in other group. Furthermore, inter-group interference is degraded by multi-user detection following the digital beamforming. The new strategy simplifies the weight vector calculation and solves the unorthogonal channel problem. Additionally, it decreases the bit error rate. The analysis and simulation illustrate the fruits of the new mechanism.
④The implementation of digital beamforming plays critical role in the sense of engineering. The traditional C language methodology is extremely complicated and time consuming since there are a lot of matrix transform and calculation. Nevertheless, we can directly generate DSP source code from the SIMULINK model with the help of Embedded IDE Link in MATLAB. Obviously, the expenditure is mitigated considerably. In addition, the steps illustrated here for multiple signal classification(MUSIC) algorithm are good reference for other array signal processing deployment on DSPs.
本文在阅读大量国内外相关科技研究文献的基础之上,针对多用户系统,围绕数字波束形成技术进行了如下几个方面的研究:
①介绍了阵列天线不同几何模型下接收信号的数学模型,进而阐述了空间谱估计和数字波束形成的基本算法,并进行了仿真分析。
②解决了波束形成中期望和干扰用户的辨识问题。传统波束形成中,虽然可以通过波达方向估计得到期望信号和干扰信号的空间信息,但并不能对二者进行区分。根据移动通信CDMA系统中多用户检测的原理,在用户发送端给不同期望用户分配不同的伪随机码作为标识码,接收端通过相关检测可以很好地区分不同期望信号和干扰信号。仿真结果表明了该方法能保持辨识系统低的虚警概率和漏警概率,准确辨识出特定期望用户的方向。
③提出了一种基于分组的多用户波束形成方法。为抑制小区内同道干扰,提高系统性能,首先通过波达方向估计把一个小区内的多个用户分成若干组,每组用户一个波束形成支路,主瓣对准该组的用户,零陷对准其他组的用户。权矢量与各组用户角度的平均值相对应。各支路波束形成输出分别进行多用户检测,消除组内各用户间的干扰。性能分析和仿真结果证明该方法简化了波束形成的权值求解,克服了用户空间的非正交性,有效降低了系统的误码率。
④波束形成类算法的工程实现具有重要的实际意义。但由于算法中存在大量复杂的矩阵以及矢量的变换和运算,通常的C语言直接编程相当复杂并且很费时。而通过MATLAB这样的CAD工具的帮助,利用其Embedded IDE Link软件直接从SIMULINK模型生成算法的DSP代码,极大地节约了软件开发的时间和成本。以空间谱估计中的多重信号分类算法为例,介绍了基于MATLAB的DSP代码的生成步骤,该步骤同样适用于其他的阵列信号处理算法。
Smart antennas is utilized to generate the radiation pattern of an antenna array by the complex vector weights that adjust the amplitude and phase of the received signal, so that the main beam is directed to the desired user and null is directed to interference user. Digital beamforming technology is an important content of smart antennas. Based on extensive reading of the relevant technology literature, this thesis discusses the digital beamforming technology in multi-user system. The dominant works are illustrated as follows:
①The fundamental signal models employed by different geometric antenna array are explained firstly. Then, the fundamental algorithm for direction of arrival (DOA) estimation and digital beamforming are illustrated with computer simulation analysis.
②The research work gains the solution for identification between interested users and interference users. In the content of traditional digital beamforming, it cannot implement the identification between the desired signals and interferences, although the DOA estimation strategy digs out the spacial information of these signals. Similar as the multi-user detection in CDMA mobile communication system, different users are allocated with one pseudo-noise (PN) code in the transmitters respectively. Furthermore, the receiver generates the replicas of transmitted PN codes and does correlation calculation with the received signals to harness the identification. The simulation shows that proposed approach picks up the desired signals and insures the low false alarm rate and missing detection rate.
③A group-based digital beamforming algorithm is proposed. In CDMA wireless cellular communication system, a new methodology is proposed to combine digital beamforming with multi-user detection technology which harnesses the co-channel interference mitigation and better performance. The proposed approach assigns all the users within a cell into separated groups according to their DOA firstly. Then only one digital beamforming branch is employed for a singular group so that the main lobe is steered to the desired users in the group and null is directed to the mobile stations in other group. Furthermore, inter-group interference is degraded by multi-user detection following the digital beamforming. The new strategy simplifies the weight vector calculation and solves the unorthogonal channel problem. Additionally, it decreases the bit error rate. The analysis and simulation illustrate the fruits of the new mechanism.
④The implementation of digital beamforming plays critical role in the sense of engineering. The traditional C language methodology is extremely complicated and time consuming since there are a lot of matrix transform and calculation. Nevertheless, we can directly generate DSP source code from the SIMULINK model with the help of Embedded IDE Link in MATLAB. Obviously, the expenditure is mitigated considerably. In addition, the steps illustrated here for multiple signal classification(MUSIC) algorithm are good reference for other array signal processing deployment on DSPs.
引文
[1]张贤达,保铮.通信信号处理[M].北京:国防工业出版社,2000.
[2]高康强.智能天线波术形成技术研究[D].西安电子科技大学,2002.
[3] Joseph C. Liberti, Theodore S. Rappaport.无线通信中的智能天线IS-95和第3代CDMA应用[M].北京:机械工业出版社,2002.
[4] Zarifi K, Ghrayeb A, Affes S. Distributed Beamforming for Wireless Sensor Networks with Improved Graph Connectivity and Energy Efficiency [J]. IEEE Transactions on Signal Processing, 2010, 58(3): 1904 - 1921.
[5] Suleesathira R, Jindapun J. Combined Adaptive Antenna Array and RAKE Receiver [C] // Russia (Northwest) Section BT/CE/COM Joint Chapter, 2006.ISCE '06. 2006 IEEE Tenth International Symposium on Consumer Electronics, 29 Jun - 01 Jul 2006, St. Petersburg Univ. of Film and Television, St. Petersburg: ISCE, 2006: 1 - 5.
[6] Mundarath J, Kotecha J. Optimal Receive Array Beamforming for Non-collaborative MIMO Space Division Multiple Access[J]. IEEE Transactions on Communications, 2010, 58(1): 218 - 227.
[7] S. Choi, D. Shim. A Novel Adaptive Beamforming Algorithm for a Smart Antenna System in a CDMA Mobile Communication Environment [J]. IEEE Transactions on Vehicular Technology, September, 2000, 49(5): 1793 - 1806.
[8] Zhigang Rong. Simulation of Adaptive Array Algorithm for CDMA Systems [M]. Paper for the Degree of Master of Science in Electrical Engineering, Virginia Polytechnic Institute and State University, 1996.
[9] Lal C. Godara. Applications of Antenna Arrays to Mobile Communications, partⅡ: Beamforming and Direction-of-arrival Considerations [J]. Proceeding of the IEEE, August 1997, 85(8): 1195 - 1245.
[10] Harry L Van Trees. Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory [M].John Wiley & Sons, Inc. 2002: 46 - 48.
[11] Hara Y, Oshima K. Remote Control of Transmit Beamforming in TDD/MIMO Systems[C]. 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications, Sophia Antipolis, 11-14 Sept.2006: 1 - 5.
[12] Sandell M., Ponnampalam V. Smooth Beamforming for OFDM [J]. IEEE Transactions on Wireless Communications, March 2009, 8(3): 1133 - 1138.
[13] Zhou Xiang Yun, Durrani, S., Jones H.M. Connectivity Analysis of Wireless Ad HocNetworks with Beamforming[J]. IEEE Transactions on Vehicular Technology, 2009, 58(9): 5247 - 5257.
[14] Sidney P. APPlebaum. Adaptive Arrays [J]. IEEE transactions on AP, 1976, AP-24(5).
[15] B.Widrow, P.E.Mantey, L.J.Griffiths, et,al. Adaptive Antenna Systems[J], IEEE Proeeddings,1967,55(12): 2143 - 2159.
[16]金荣洪,耿军平,范瑜.无线通信中的智能天线[M].北京:北京邮电大学出版社,2006.
[17] Tyseer Aboulnasr, K. Mayyas. A Robust via Step-size LMS-type Algorithm: Analysis and Simulation [J]. IEEE Transactions on Signal Processing, 1997, 45(3): 631 - 639.
[18] J.CaPon. High-resolution Frequeney-wavenurnber Spectrum Analysis [J]. Proe.of IEEE,1969, 57(8): 1408 - 1418.
[19] Vaidyanathan C, Buckley K M. Performance Analysis of the MVDR Spatial Spectrum Estimator [J]. IEEE Transactions on Signal Processing, 1995, 43(6): 1427 - 1437.
[20]李尚勤,李晓峰.快速自适应信息处理[M].北京:人民邮电出版社,1993.
[21] J. M. Cioffi, T. Kailath. Fast Recursive-Least-Square, Transversal Filters for Adaptive Filtering [J]. IEEE Transactions on Acoustics, Speech, Signal Processing, 1984, ASSP-32: 998 - 1005.
[22] Kawitkar, Rameshwar. Performance of Different Types of Array Structures Based on Multiple Signal Classification (MUSIC) Algorithm [C]// 2009 Fifth International Conference on MEMS, NANO, and Smart Systems (ICMENS), 28-30 Dec. 2009 ,IEEE, Dubai, United Arab Emirates: IEEE, 2009: 159 - 161.
[23] Schmidt R O. Multiple Emitter Location and Signal Parameter Estimation [J]. IEEE Transactions on AP, 1986, 34 (3): 276 - 280.
[24]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.
[25] Roy P., Kailath T. ESPRIT-Estimation of Signal Parameters via Rotational Invariance Techniques [J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, July 1989, 37: 984 - 995.
[26] M.H. Li, Y.L. Lu. Maximum likelihood DOA Estimation in Unknown Colored Noise Fields [J]. IEEE Transactions on Aerospace and Electronic Systems, 2008, 44(3): 1079 - 1090.
[27] J.S. Thompson, P.M. Grant, B. Mulgrew, Performance of Spatial Smoothing Algorithms for Correlated Sources [J]. IEEE Transactions on Signal Processing, 1996, 44(4): 1040 - 046.
[28] Jalali M. Moghaddasi M N, Habibzadeh A. Comparing accuracy for ML, MUSIC, ROOT-MUSIC and spatially smoothed algorithms for 2 users [C]// 2009 Mediterrannean Microwave Symposium (MMS), 15-17 Nov. 2009, IEEE, Tangiers: IEEE, 2009: 1 - 5 .
[29] Tyseer Aboulnasr, K. Mayyas. A Robust via Step-size LMS-type Algorithm: Analysis andSimulation [J]. IEEE Transactions on Signal Processing, 1997, 45(3): 631 - 639.
[30] P. Fabre, C. Gueguen. Improvement of the Fast Recursive-Least-Squares Algorithms via Normalization: A Comparative Study [J]. IEEE Transactions on Acoustics, Speech, Signal Processing, 1986, ASSP-31: 296 - 308.
[31] Xu Ding-Jie, Zhao Guo-Qing, Yu Zhuo-Qi. The Performance Analysis of Rapid PN Code Acquisition Using Iterative Message Passing Algorithm[C]. 2007 International Conference on Icma, Harbin, Harbin Eng. Univ. Press, 2007: 2450 - 2455.
[32] Lee Y H, Kim S J. Sequence Acquisition of DS-CDMA Systems Employing Gold Sequences [J], IEEE Transactions on Vehicular Technology, 2000, 49 (6): 2397 - 2404.
[33] Kawabata M, Niihara S, Itami M, et al. A Study on Good PN Code Allocation for Position Oriented PN Code Allocation Scheme in DS/CDMA Ivc[C]. '07. 7th International Conference on Itst, Sophia Antipolis, 2007: 1 - 5.
[34] Stankovic R.S. Some Remarks on Terminology in Spectral Techniques for Logic Design: Walsh Transform and Hadamard Matrices [J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 1998 ,17(11): 1211 - 1214.
[35] Wu Ye, Zhu Xu, Nandi A. Low Complexity Adaptive Turbo Frequency-Domain Channel Estimation for Single-Carrier Multi-User Detection [J]. IEEE Transactions on Wireless Communications, 2008, 7(11): 4094 - 4099.
[36] Angelosante D, Giannakis G B, Sidiropoulos N D. Estimating Multiple Frequency-hopping Signal Parameters via Sparse Linear Regression [J]. IEEE Transactions on Signal Processing, 2010, 58(10): 5044 - 5056.
[37] Pelletier B, Champagne B. Group-based Space–time Multiuser Detection with User Sharing [J]. IEEE Transactions on Wireless Communication, Jun. 2007, 6(6): 2034 - 2039.
[38] Pelletier B, Champagne B. Multistage MMSE PIC Space–time Receiver with Non-mutually Exclusive Grouping [J]. IEEE Transactions on Vehicular Technology, 2008, 57(4): 2070 - 2080.
[39] Li Junqiang, Letaief K B, Cao Zhig-Ang. A Group Oriented Multiuser Detection with Beamforming for Multicarrier CDMA Systems [C]//Global Telecommunications Conference, 2001. GLOBECOM '01. IEEE, Nov 25-29, 2001, San Antonio, TX: IEEE, 2001: 733 - 737 .
[40] Vishnu Vardhan K, Mohammed S K, Chockalingam A, et al. A Low-complexity Detector for Large MIMO Systems and Multicarrier CDMA Systems [J]. IEEE Journal on Selected Areas in Communications, 2008, 26(3): 473 - 485.
[41] Liu Wen-Long, Ding Shu-Xue. An Efficient Method to Determine the Diagonal loading Factor Using the Constant Modulus Feature [J]. IEEE Transactions on Signal Processing,2008, 56(12): 6102 - 6106.
[42] Pham Tt, Nguyen H H. Decorrelate-and-forward Relaying Scheme for Multiuser Wireless Code Division Multiple Access Networks [J].IET Communications, 2010, 4(4): 443 - 451.
[43]李真芳,苏涛,黄小宇. DSP程序开发:MATLAB调试及直接目标代码生成[M].西安:西安电子科技大学出版社,2003.
[44] Spectrum Digital Incorporated. TMS320C6711 DSK Technical Reference [DB/OL].Stafford, TX. 2003.5.
[45]曾浩,杨士中,冯文江.基于SVD的特征空间波束合成器[J].电波科学学报. 2008, 23(06): 1194 - 1198.
[46] Mathworks. Embedded IDE link? for Use with Texas Instruments’Code Composer Studio? 4 User’s Guide [DB/OL].2009.
[47] Mathworks. Signal Processing Blockset? 6 User’s Guide [DB/OL].2009.3.
[48] Mathworks. Target Support Package? 4 User’s Guide [DB/OL].2009.3.
[49] Mathworks. Real-Time Workshop? Embedded Coder? 5 User’s Guide [DB/OL].2009.3.
[50] Mathworks. Real-Time Workshop?7 User’s Guide[DB/OL].2009.3.
[2]高康强.智能天线波术形成技术研究[D].西安电子科技大学,2002.
[3] Joseph C. Liberti, Theodore S. Rappaport.无线通信中的智能天线IS-95和第3代CDMA应用[M].北京:机械工业出版社,2002.
[4] Zarifi K, Ghrayeb A, Affes S. Distributed Beamforming for Wireless Sensor Networks with Improved Graph Connectivity and Energy Efficiency [J]. IEEE Transactions on Signal Processing, 2010, 58(3): 1904 - 1921.
[5] Suleesathira R, Jindapun J. Combined Adaptive Antenna Array and RAKE Receiver [C] // Russia (Northwest) Section BT/CE/COM Joint Chapter, 2006.ISCE '06. 2006 IEEE Tenth International Symposium on Consumer Electronics, 29 Jun - 01 Jul 2006, St. Petersburg Univ. of Film and Television, St. Petersburg: ISCE, 2006: 1 - 5.
[6] Mundarath J, Kotecha J. Optimal Receive Array Beamforming for Non-collaborative MIMO Space Division Multiple Access[J]. IEEE Transactions on Communications, 2010, 58(1): 218 - 227.
[7] S. Choi, D. Shim. A Novel Adaptive Beamforming Algorithm for a Smart Antenna System in a CDMA Mobile Communication Environment [J]. IEEE Transactions on Vehicular Technology, September, 2000, 49(5): 1793 - 1806.
[8] Zhigang Rong. Simulation of Adaptive Array Algorithm for CDMA Systems [M]. Paper for the Degree of Master of Science in Electrical Engineering, Virginia Polytechnic Institute and State University, 1996.
[9] Lal C. Godara. Applications of Antenna Arrays to Mobile Communications, partⅡ: Beamforming and Direction-of-arrival Considerations [J]. Proceeding of the IEEE, August 1997, 85(8): 1195 - 1245.
[10] Harry L Van Trees. Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory [M].John Wiley & Sons, Inc. 2002: 46 - 48.
[11] Hara Y, Oshima K. Remote Control of Transmit Beamforming in TDD/MIMO Systems[C]. 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications, Sophia Antipolis, 11-14 Sept.2006: 1 - 5.
[12] Sandell M., Ponnampalam V. Smooth Beamforming for OFDM [J]. IEEE Transactions on Wireless Communications, March 2009, 8(3): 1133 - 1138.
[13] Zhou Xiang Yun, Durrani, S., Jones H.M. Connectivity Analysis of Wireless Ad HocNetworks with Beamforming[J]. IEEE Transactions on Vehicular Technology, 2009, 58(9): 5247 - 5257.
[14] Sidney P. APPlebaum. Adaptive Arrays [J]. IEEE transactions on AP, 1976, AP-24(5).
[15] B.Widrow, P.E.Mantey, L.J.Griffiths, et,al. Adaptive Antenna Systems[J], IEEE Proeeddings,1967,55(12): 2143 - 2159.
[16]金荣洪,耿军平,范瑜.无线通信中的智能天线[M].北京:北京邮电大学出版社,2006.
[17] Tyseer Aboulnasr, K. Mayyas. A Robust via Step-size LMS-type Algorithm: Analysis and Simulation [J]. IEEE Transactions on Signal Processing, 1997, 45(3): 631 - 639.
[18] J.CaPon. High-resolution Frequeney-wavenurnber Spectrum Analysis [J]. Proe.of IEEE,1969, 57(8): 1408 - 1418.
[19] Vaidyanathan C, Buckley K M. Performance Analysis of the MVDR Spatial Spectrum Estimator [J]. IEEE Transactions on Signal Processing, 1995, 43(6): 1427 - 1437.
[20]李尚勤,李晓峰.快速自适应信息处理[M].北京:人民邮电出版社,1993.
[21] J. M. Cioffi, T. Kailath. Fast Recursive-Least-Square, Transversal Filters for Adaptive Filtering [J]. IEEE Transactions on Acoustics, Speech, Signal Processing, 1984, ASSP-32: 998 - 1005.
[22] Kawitkar, Rameshwar. Performance of Different Types of Array Structures Based on Multiple Signal Classification (MUSIC) Algorithm [C]// 2009 Fifth International Conference on MEMS, NANO, and Smart Systems (ICMENS), 28-30 Dec. 2009 ,IEEE, Dubai, United Arab Emirates: IEEE, 2009: 159 - 161.
[23] Schmidt R O. Multiple Emitter Location and Signal Parameter Estimation [J]. IEEE Transactions on AP, 1986, 34 (3): 276 - 280.
[24]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.
[25] Roy P., Kailath T. ESPRIT-Estimation of Signal Parameters via Rotational Invariance Techniques [J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, July 1989, 37: 984 - 995.
[26] M.H. Li, Y.L. Lu. Maximum likelihood DOA Estimation in Unknown Colored Noise Fields [J]. IEEE Transactions on Aerospace and Electronic Systems, 2008, 44(3): 1079 - 1090.
[27] J.S. Thompson, P.M. Grant, B. Mulgrew, Performance of Spatial Smoothing Algorithms for Correlated Sources [J]. IEEE Transactions on Signal Processing, 1996, 44(4): 1040 - 046.
[28] Jalali M. Moghaddasi M N, Habibzadeh A. Comparing accuracy for ML, MUSIC, ROOT-MUSIC and spatially smoothed algorithms for 2 users [C]// 2009 Mediterrannean Microwave Symposium (MMS), 15-17 Nov. 2009, IEEE, Tangiers: IEEE, 2009: 1 - 5 .
[29] Tyseer Aboulnasr, K. Mayyas. A Robust via Step-size LMS-type Algorithm: Analysis andSimulation [J]. IEEE Transactions on Signal Processing, 1997, 45(3): 631 - 639.
[30] P. Fabre, C. Gueguen. Improvement of the Fast Recursive-Least-Squares Algorithms via Normalization: A Comparative Study [J]. IEEE Transactions on Acoustics, Speech, Signal Processing, 1986, ASSP-31: 296 - 308.
[31] Xu Ding-Jie, Zhao Guo-Qing, Yu Zhuo-Qi. The Performance Analysis of Rapid PN Code Acquisition Using Iterative Message Passing Algorithm[C]. 2007 International Conference on Icma, Harbin, Harbin Eng. Univ. Press, 2007: 2450 - 2455.
[32] Lee Y H, Kim S J. Sequence Acquisition of DS-CDMA Systems Employing Gold Sequences [J], IEEE Transactions on Vehicular Technology, 2000, 49 (6): 2397 - 2404.
[33] Kawabata M, Niihara S, Itami M, et al. A Study on Good PN Code Allocation for Position Oriented PN Code Allocation Scheme in DS/CDMA Ivc[C]. '07. 7th International Conference on Itst, Sophia Antipolis, 2007: 1 - 5.
[34] Stankovic R.S. Some Remarks on Terminology in Spectral Techniques for Logic Design: Walsh Transform and Hadamard Matrices [J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 1998 ,17(11): 1211 - 1214.
[35] Wu Ye, Zhu Xu, Nandi A. Low Complexity Adaptive Turbo Frequency-Domain Channel Estimation for Single-Carrier Multi-User Detection [J]. IEEE Transactions on Wireless Communications, 2008, 7(11): 4094 - 4099.
[36] Angelosante D, Giannakis G B, Sidiropoulos N D. Estimating Multiple Frequency-hopping Signal Parameters via Sparse Linear Regression [J]. IEEE Transactions on Signal Processing, 2010, 58(10): 5044 - 5056.
[37] Pelletier B, Champagne B. Group-based Space–time Multiuser Detection with User Sharing [J]. IEEE Transactions on Wireless Communication, Jun. 2007, 6(6): 2034 - 2039.
[38] Pelletier B, Champagne B. Multistage MMSE PIC Space–time Receiver with Non-mutually Exclusive Grouping [J]. IEEE Transactions on Vehicular Technology, 2008, 57(4): 2070 - 2080.
[39] Li Junqiang, Letaief K B, Cao Zhig-Ang. A Group Oriented Multiuser Detection with Beamforming for Multicarrier CDMA Systems [C]//Global Telecommunications Conference, 2001. GLOBECOM '01. IEEE, Nov 25-29, 2001, San Antonio, TX: IEEE, 2001: 733 - 737 .
[40] Vishnu Vardhan K, Mohammed S K, Chockalingam A, et al. A Low-complexity Detector for Large MIMO Systems and Multicarrier CDMA Systems [J]. IEEE Journal on Selected Areas in Communications, 2008, 26(3): 473 - 485.
[41] Liu Wen-Long, Ding Shu-Xue. An Efficient Method to Determine the Diagonal loading Factor Using the Constant Modulus Feature [J]. IEEE Transactions on Signal Processing,2008, 56(12): 6102 - 6106.
[42] Pham Tt, Nguyen H H. Decorrelate-and-forward Relaying Scheme for Multiuser Wireless Code Division Multiple Access Networks [J].IET Communications, 2010, 4(4): 443 - 451.
[43]李真芳,苏涛,黄小宇. DSP程序开发:MATLAB调试及直接目标代码生成[M].西安:西安电子科技大学出版社,2003.
[44] Spectrum Digital Incorporated. TMS320C6711 DSK Technical Reference [DB/OL].Stafford, TX. 2003.5.
[45]曾浩,杨士中,冯文江.基于SVD的特征空间波束合成器[J].电波科学学报. 2008, 23(06): 1194 - 1198.
[46] Mathworks. Embedded IDE link? for Use with Texas Instruments’Code Composer Studio? 4 User’s Guide [DB/OL].2009.
[47] Mathworks. Signal Processing Blockset? 6 User’s Guide [DB/OL].2009.3.
[48] Mathworks. Target Support Package? 4 User’s Guide [DB/OL].2009.3.
[49] Mathworks. Real-Time Workshop? Embedded Coder? 5 User’s Guide [DB/OL].2009.3.
[50] Mathworks. Real-Time Workshop?7 User’s Guide[DB/OL].2009.3.