移动通信智能天线关键技术研究
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摘要
智能天线可以改善通信链路性能，大大提高系统容量，提高频谱利用效率，现已成为移动通信中的研究热点。本文系统地阐述了移动通信系统中智能天线的基本理论和相关技术，重点对其中几个核心问题：空时信道特性与建模理论、自适应数字波束形成算法、高分辨的DOA估计算法(重点是相干多径环境下的有效算法)、抗干扰技术(尤其是抗相干干扰)、空时信道多维参数联合估计、空时二维处理理论等方面进行了较为深入研究。
对于空时信道特性和相关建模理论，论文首先介绍了无线空时信道的特点，从理论上分析了时延扩展、多普勒频率扩展和角度扩展对智能天线的频率相关性、时间相关性和空间相关性的影响。在此基础上，(1)本文首次对移动通信环境中不同散射环境下(如拉普拉斯分布、截尾高斯分布等)智能天线的相关性进行了理论推导和数值仿真，得出了天线相关性与散射分布特性之间的定量关系，为移动通信智能天线设计提供了理论依据。(2)对于建模理论，在简单介绍常用的Lee模型及其改进模型、几何单反射(GBSB)模型、高斯广义平稳不相关散射(GWSSUS)模型和扩展抽头延迟线模型等模型的基础上，根据ITU建议的不同环境下的功率时延谱和功率角度谱，本文提出了一种基于统计特性仿真不同空时信道的方法，该方法简便有效，容易构造出适用于不同环境的信道模型，仿真结果验证了该模型能够同时反映信道的空间、时间以及频率特性。
对于波束形成技术，论文简介了LMS和RLS两种非盲算法，重点对恒模算法(CMA)和最小二乘解扩重扩多目标恒模算法(LS-DRMTCMA)两类盲算法进行了深入研究，通过仿真实验对其性能进行了对比分析。在此基础上，(1)论文针对常规恒模算法收敛速度与稳态误差之间的矛盾，基于一种新的代价函数，提出了一种新的自适应步长控制方法，该算法基于高斯函数实现恒模误差和步长之间的非线性映射，参数控制简单，具有超线性加速收敛作用，能够同时兼顾收敛速度、稳态误差和抗随机噪声性能，改善了恒模阵列性能。(2)对于非平稳信道，信号随机衰落会导致同级阵列上各输入信号相对功率快速变化，而恒模算法只是简单地捕捉功率最强信号，这会造成各级阵列捕获的信号摇摆不定，从而无法对目标用户实现稳定的捕获或跟踪，为此，在前述算法基础上，本文进一步提出了一种非对称的步长控制机制，既保证了各级阵列对目标用户的快速捕获，又能保证各级阵列对目标用户的稳定跟踪，提高了阵列抗衰落性能。
对于波达方向估计，论文在介绍常用DOA估计算法的基础上，针对常规MUSIC和ESPRIT不能处理相干源、能够估计的DOA数不能超过阵元数M、不适用于有色噪声且多径分量DOA与用户配对难等特点，按均匀直线阵和均匀圆阵分别研究了适合蜂窝系统中多用户相干多径环境的DOA估计算法。(1)对于均匀直线阵，利用阵列输出四阶累积量对上行信号空间特征实现了全盲估计，并将其用于相干多径环境下的多用户信号DOA的估计。该方法不依赖于信号具体特征，能够抗任意加性高斯噪声，利用M个阵元最多可以估计2M~2／3个DOA，可以突破传统的MUSIC或ESPRIT算法的局限，并使各多径分量与用户自动配对。通过仿真实验研究了估计方差与信噪比和快拍数之间的关系，验证了算法的有效性和鲁棒性。基于空间特征估计，构建了空间滤波器组，实现了多用户信号分离与信源恢复。(2)对于均匀圆阵，分别介绍了阵元空间MUSIC、实波束空间MUSIC和UCA-ESPRIT，通过仿真实验研究了各种算法的性能。由于这些算法都不适用于相干源，而常规的空间平滑技术不能直接用于圆阵，论文采用预处理将均匀圆阵转化为模式空间虚拟线阵后再通过平滑处理，实现了圆阵相干源DOA估计。
相干多径环境下，智能天线性能会严重恶化。论文对此提出了相应的改进方法。(1)针对现有空间平滑解相干算法的不足，本文基于充分利用子阵列自相关和互相关矩阵信息的思想，提出了一种新的自适应全局加权空间平滑算法(AGWSS)，该算法大大提高了小型阵列的解相关性能。该算法是完全自适应的，无需信源角度的先验知识或对其进行预估计。(2)在AGWSS中首次提出采用对称化处理的思想保证平滑后相关矩阵的Hermite对称性，并在此基础上首次导出了AGWSS最优平滑权矩阵的闭式解。(显式表达，不同于某些其它算法的隐式表达)。(3)在AGWSS基础上，针对某些应用场所平滑后相关矩阵应满足半正定的要求，通过本文的对称化处理，在平滑后相关矩阵Toeplitz化、Hermite对称化和半正定的约束下，并基于原始-对偶内点障碍函数法，本文又提出了半正定的全局加权空间平滑算法(SD-AGWSS)。将其用于相干环境下DOA估计，大大提高估计性能，尤其在相干源角度间隔很小或信噪比较低时，分辨能力大大提高。
相干多径环境下，常用的波束形成算法性能都将严重恶化，甚至出现期望信号被对消的现象，而常规的空间平滑算法解相干能力较差，且会损失阵列有效孔径。(1)本文提出了一种改进的波束形成方案：首先利用本文提出的AGWSS算法进行自适应全局加权空间平滑，可以最大程度解相关；然后利用LCMV准则直接矩阵求逆(DMI)得到子阵波束形成器最佳权矢量；在此基础上，为了克服平滑引起的孔径损失，充分利用剩余自由度，论文分别提出在二次零陷加深准则下和在噪声增益最小化准则下的二次加权，大大提高了阵列抗相干(关)干扰和抗噪声能力。(2)论文还首次从理论上和仿真实验定量分析对比了不同平滑算法的解相干能力(相干抑制因子)。(3)论文利用自由度理论首次分析了不同平滑算法的子阵划分条件：对M元阵列，WSS最多可以滤除((M-1)~(1/2)-1)个相干干扰，而采用AGWSS时最多可以滤出(M／2-1)个相干干扰。理论分析和仿真实验证明AGWSS算法性能明显优于现有的各种空间平滑算法，尤其适用于移动通信中的小型智能天线。
论文进一步研究了智能天线中时空多径信道多维参数联合估计及其干扰抑制问题。(1)针对TD-SCDMA系统中的均匀圆阵，提出了一种新的空时扩展阵列结构，该算法能实现时空信道多径的俯仰角-方位角-时延-多普勒频移四维参数联合估计。本算法同时具备：无需训练序列或预先知道信道冲激响应、可用于多用户环境、每个用户的多径数目可以超过阵元数、且多参数自然配对等特点。在算法处理过程中，可同时从码域、空域、时域和频域对信道中的多址干扰、符号间干扰和多普勒频率干扰进行抑制，大大提高了智能天线抗干扰性能。(2)为了提高多维参数估计时的搜索速度，本文还采用了粒子群优化(PSO)算法进行多维搜索。针对基本粒子群优化算法只适合搜索全局最优的局限性，本文应用“函数变换”将原空时谱函数变换为等高峰函数，并通过修改粒子速度更新公式和“聚积处理”等手段实现了PSO算法在空时谱多峰位搜索中的应用。
最后，论文对采用智能天线后移动通信系统的信噪比、系统容量等方面进行了分析，并讨论了智能天线对原有系统可能的影响。
Smart antennas can improve the quality of communication links, greatly increase the capacity of communication systems and enhance the efficiency of frequency, which has become a "hotspot" of research in mobile communication. This dissertation dissertated the basic theory and relevant techniques of smart antennas in mobile communication systems, and detailedly studied on some key problems, which including the spatial-temporal channel property and modeling theory, adaptive digital beamforming algorithms, super-resolution algorithms for DOA estimation (especially, effective algorithms for coherent multipaths environment), interference suppression techniques (especially suppression of coherent interference), joint multi-dimension parameter estimation in spatial-temporal channel, and the 2D spatial-temporal processing.
As for the spatial-temporal channel property and modeling theory, firstly, the thesis introduced the property of wireless spatial-temporal channel, and theoretically analyzed the effects on the frequency correlativity, temporal correlativity and spatial correlativity caused by delay spreading, Doppler frequency spreading and angle spreading, respectively. (1) For different scattering environments in mobile communications, we theoretically deduced and numerically simulated the correlativity of smart antennas, and obtained the relationship between antennas correlativity and the distributing property of scattering, which can be provided as theoretical reference for smart antennas designs. (2) As for channel modeling theory, the thesis simply introduced the conventional models including the Lee's model and its improved model, the Geometrically Based Single Bounce (GBSB) model, the Gaussian Wide Sense Stationary Uncorrelated Scattering (GWSUS) model and the Expanded Tapped-Delay-Line model. Then, base on the power-delay spectrum and power-angle spectrum suggested by ITU for different environments, we proposed a method based on statistical property to simulate the spatial-temporal channel. The method is simple and effective, can easily construct different channels. Simulation results confirmed the model can reflect the channel property in spatial domain, temporal domain and frequency domain simultaneously.
As to the beamforming techniques, the thesis simply introduced two kind of non-blind algorithms—LMS and RLS, detailedly studied on the two kind of blind algorithms—Constant Modules Algorithm (CMA) and Least Square De-spread Re-spread Multi Target Constant Modules Algorithm (LS-DRMTCMA), and analyzed their performance via simulation experiments. (1) Aimed at the contradictory between convergence speed and the steady-state errs in the conventional CMA, based on a new cost function, the thesis proposed a novel method to control the step-size adaptively. The algorithm uses Gauss function to realize the mapping from constant modulus err to step-size, its parameters are simple to be control, and it has super-linear accelerating effect, can obtain excellent convergence speed, small steady-state err and excellent noise resisting ability simultaneously, which can improve the performance of constant modulus array. (2) In non-stationary channel, the relative power of the signals input in the same stage will change quickly owing to the random fading, however, the CMA simply tends to capture the strongest signal, which might cause the signals captured by each stages to fluctuate, and each stage can't maintain a steadily capture or tracing to the target user. So, based on the improved algorithm proposed before, we further introduced a dissymmetrical mechanism to control the step-size, which can not only ensure each stage to capture the target user quickly, but also ensure each stage to trace the target user steadily, and enhance the anti-fading ability of the array.
As to DOA estimation, the thesis simply introduced the commonly used DOA estimation algorithms. The thesis noticed the problems that, MUSIC and ESPRIT can't deal with coherent sources, the number of DOAs that can be estimated can't exceed the element number of array, the algorithms are not fitted for colored noise, and it's difficult to pair the DOAs with the users. Aiming at the cellular system, according to uniform linear array and uniform circular array respectively, the thesis studied on algorithms that suitable for coherent mutipath environment in cellular systems. (1) For uniform linear array, using the fourth order cumulant of array outputs, we realized the blind estimation of spatial signature in uplink, and use it to estimate the multi-user's DOAs in coherent mutipath environment. The algorithm is not depended upon the specific property of signals, can be employed to additive arbitrary Gaussian noise, can estimate 2M~2/3 DOAs by M elements, can breakthrough the limit of conventional MUSIC and ESPRIT, and can pair the multipath with users automatically. Through simulation experiments, the relations between estimation variance, SNR and snapshot number were studied, which confirmed the availability and robustness of the algorithm. Based on spatial signature estimation, the thesis constructed a spatial filter bank, and realized the separation of multi-user and the recovery of sources. (2) For uniform circular array, the thesis firstly introduced the element space MUSIC, real beam space UCA-RB-MUSIC and UCA-ESPRIT, then studied and evaluated their performance via simulation experiment. Because all algorithms mentioned above are invalid in coherent environment, and uniform circular arrays are not fit for directly spatial smoothing, the thesis used a pre-processing technique to transform the UCA of element space into a virtual uniform linear array of mode space, and then used spatial smoothing to realize the DOA estimation for coherent sources in UCA.
In coherent multipath environment, the performance of smart antenna will decline dramatically. The thesis proposed an improved method to overcome the problem. (1) To overcome the shortcoming of the existing spatial smoothing algorithm, and base on the idea that fully utilize each auto-correlation matrix and cross-correlation matrix of sub-arrays, the thesis proposed an algorithm calledadaptive-globally-weighted-spatial-smoothing (AGWSS), and greatly improved the de-correlation ability of small array. The algorithm is completely adaptive and does not need the prior knowledge of the source angles or pre-estimation of source angles. (2) In AGWSS, for the first time, the thesis proposed an idea of symmetrical processing (in page 121) to ensure the Hermitian property of the smoothed correlation matrix, and, base on this idea, the thesis deduced the closed-form solution of the optimal smoothing weight matrix for the AGWSS (i.e., explicit formulation, not implicit formulation as some other algorithms). (3) Furthermore, considering the requirement of semi-definite to the smoothed correlation matrix in some applications, using symmetrical processing techniques, under the constraints that the smoothed correlation matrix should be Toeplitzian, Hermitian and semi-definite, and based on the Primal-Dual-Interior-Point-Barrier-Function method, the thesis proposed an algorithm called semi-definite adaptive globally weighted spatial smoothing (SD-AGWSS). The algorithm was used to estimate DOAs in coherent environment, and greatly improved the estimating performance, especially, when the coherent sources are close or the SNR is very low, the resolution can be enhanced greatly.
In coherent multipath environment, the commonly used beamforming algorithms will become ineffective, and the desired signal in array might be cancelled. The conventional spatial smoothing technique has poor de-correlating ability, and it will reduce the "effective aperture" of array. (1) The thesis proposed an improved beamforming scheme: Firstly, adopting the AGWSS algorithm proposed in this thesis, which, through globally weighted averaging of the auto-correlation matrices and cross-correlation matrix of each subarray, can de-correlate the coherency to the utmost extent; and then, using the linear-constrained-minimum-variance (LCMV) criterion for directly matrix inverse, the optimum weight vector of subarray beamformer can be found; at last, in order to avoid the aperture loss caused by smoothing and fully utilize the residual freedom degrees, the thesis proposed a technique of second-weighting under the criterion of null deepening or noise gain minimization respectively, which greatly improved the ability of array to suppress coherent (or correlative) interference and noise. (2) By theoretical analysis and simulations, the thesis compared the de-correlating ability of different smoothing algorithms for the first time. (3) Using freedom degree theory, for the first time, the thesis analyzed and compared the conditions for subarray division in different smoothing algorithms: for an array with M elements, WSS can suppress ((M-1)~(1/2)-1) coherent interferences, but AGWSS can suppress (M/2-1) coherent interferences. Theoretical analysis and simulations showed that the AGWSS outperforms the existing spatial smoothing algorithms obviously, and especially it's suitable for small smart antennas in mobile communications.
The thesis further studied the problem of joint multi-dimension parameters estimation of spatial-temporal channel in smart antennas and its techniques of interference suppression. (1) For circular array in TD-SCDMA system, it provided an architecture of expanded spatial-temporal array, and realized the joint 4D parameters estimation of elevation, azimuth, delay and doppler frequency-offset for multipaths in spatial-temporal channel. The method does not need training sequences or pre-estimation of channel impulse response, can work in multi-user environments. The multipaths number of each user can exceed the element number of array, and all parameters are paired automatically. During the procedure, from PN code domain, spatial domain, temporal domain and frequency domain, the method can simultaneously suppressed the MAI, ISI and Doppler frequency interference in the channel, which greatly improved the interference suppression ability of smart antennas. (2) In order to increase the searching speed in multi-dimension parameters estimation, Particle Swarm Optimization (PSO) algorithm was employed to realize multi-dimension searching. Considering the limit that the basic PSO is only fit to search the global optimum, the thesis transformed the original spectrum function into an equal-peaks function, and, through some measures, such as modification to the particle speed updating formula and "congestion handling", it realized the application of PSO in the peaks searching for spatial-temporal spectrum.
At last, the thesis analyzed the SNR, system capacity of mobile communication systems employing smart antennas, and discussed the possible effects on original system caused by smart antennas.
对于空时信道特性和相关建模理论，论文首先介绍了无线空时信道的特点，从理论上分析了时延扩展、多普勒频率扩展和角度扩展对智能天线的频率相关性、时间相关性和空间相关性的影响。在此基础上，(1)本文首次对移动通信环境中不同散射环境下(如拉普拉斯分布、截尾高斯分布等)智能天线的相关性进行了理论推导和数值仿真，得出了天线相关性与散射分布特性之间的定量关系，为移动通信智能天线设计提供了理论依据。(2)对于建模理论，在简单介绍常用的Lee模型及其改进模型、几何单反射(GBSB)模型、高斯广义平稳不相关散射(GWSSUS)模型和扩展抽头延迟线模型等模型的基础上，根据ITU建议的不同环境下的功率时延谱和功率角度谱，本文提出了一种基于统计特性仿真不同空时信道的方法，该方法简便有效，容易构造出适用于不同环境的信道模型，仿真结果验证了该模型能够同时反映信道的空间、时间以及频率特性。
对于波束形成技术，论文简介了LMS和RLS两种非盲算法，重点对恒模算法(CMA)和最小二乘解扩重扩多目标恒模算法(LS-DRMTCMA)两类盲算法进行了深入研究，通过仿真实验对其性能进行了对比分析。在此基础上，(1)论文针对常规恒模算法收敛速度与稳态误差之间的矛盾，基于一种新的代价函数，提出了一种新的自适应步长控制方法，该算法基于高斯函数实现恒模误差和步长之间的非线性映射，参数控制简单，具有超线性加速收敛作用，能够同时兼顾收敛速度、稳态误差和抗随机噪声性能，改善了恒模阵列性能。(2)对于非平稳信道，信号随机衰落会导致同级阵列上各输入信号相对功率快速变化，而恒模算法只是简单地捕捉功率最强信号，这会造成各级阵列捕获的信号摇摆不定，从而无法对目标用户实现稳定的捕获或跟踪，为此，在前述算法基础上，本文进一步提出了一种非对称的步长控制机制，既保证了各级阵列对目标用户的快速捕获，又能保证各级阵列对目标用户的稳定跟踪，提高了阵列抗衰落性能。
对于波达方向估计，论文在介绍常用DOA估计算法的基础上，针对常规MUSIC和ESPRIT不能处理相干源、能够估计的DOA数不能超过阵元数M、不适用于有色噪声且多径分量DOA与用户配对难等特点，按均匀直线阵和均匀圆阵分别研究了适合蜂窝系统中多用户相干多径环境的DOA估计算法。(1)对于均匀直线阵，利用阵列输出四阶累积量对上行信号空间特征实现了全盲估计，并将其用于相干多径环境下的多用户信号DOA的估计。该方法不依赖于信号具体特征，能够抗任意加性高斯噪声，利用M个阵元最多可以估计2M~2／3个DOA，可以突破传统的MUSIC或ESPRIT算法的局限，并使各多径分量与用户自动配对。通过仿真实验研究了估计方差与信噪比和快拍数之间的关系，验证了算法的有效性和鲁棒性。基于空间特征估计，构建了空间滤波器组，实现了多用户信号分离与信源恢复。(2)对于均匀圆阵，分别介绍了阵元空间MUSIC、实波束空间MUSIC和UCA-ESPRIT，通过仿真实验研究了各种算法的性能。由于这些算法都不适用于相干源，而常规的空间平滑技术不能直接用于圆阵，论文采用预处理将均匀圆阵转化为模式空间虚拟线阵后再通过平滑处理，实现了圆阵相干源DOA估计。
相干多径环境下，智能天线性能会严重恶化。论文对此提出了相应的改进方法。(1)针对现有空间平滑解相干算法的不足，本文基于充分利用子阵列自相关和互相关矩阵信息的思想，提出了一种新的自适应全局加权空间平滑算法(AGWSS)，该算法大大提高了小型阵列的解相关性能。该算法是完全自适应的，无需信源角度的先验知识或对其进行预估计。(2)在AGWSS中首次提出采用对称化处理的思想保证平滑后相关矩阵的Hermite对称性，并在此基础上首次导出了AGWSS最优平滑权矩阵的闭式解。(显式表达，不同于某些其它算法的隐式表达)。(3)在AGWSS基础上，针对某些应用场所平滑后相关矩阵应满足半正定的要求，通过本文的对称化处理，在平滑后相关矩阵Toeplitz化、Hermite对称化和半正定的约束下，并基于原始-对偶内点障碍函数法，本文又提出了半正定的全局加权空间平滑算法(SD-AGWSS)。将其用于相干环境下DOA估计，大大提高估计性能，尤其在相干源角度间隔很小或信噪比较低时，分辨能力大大提高。
相干多径环境下，常用的波束形成算法性能都将严重恶化，甚至出现期望信号被对消的现象，而常规的空间平滑算法解相干能力较差，且会损失阵列有效孔径。(1)本文提出了一种改进的波束形成方案：首先利用本文提出的AGWSS算法进行自适应全局加权空间平滑，可以最大程度解相关；然后利用LCMV准则直接矩阵求逆(DMI)得到子阵波束形成器最佳权矢量；在此基础上，为了克服平滑引起的孔径损失，充分利用剩余自由度，论文分别提出在二次零陷加深准则下和在噪声增益最小化准则下的二次加权，大大提高了阵列抗相干(关)干扰和抗噪声能力。(2)论文还首次从理论上和仿真实验定量分析对比了不同平滑算法的解相干能力(相干抑制因子)。(3)论文利用自由度理论首次分析了不同平滑算法的子阵划分条件：对M元阵列，WSS最多可以滤除((M-1)~(1/2)-1)个相干干扰，而采用AGWSS时最多可以滤出(M／2-1)个相干干扰。理论分析和仿真实验证明AGWSS算法性能明显优于现有的各种空间平滑算法，尤其适用于移动通信中的小型智能天线。
论文进一步研究了智能天线中时空多径信道多维参数联合估计及其干扰抑制问题。(1)针对TD-SCDMA系统中的均匀圆阵，提出了一种新的空时扩展阵列结构，该算法能实现时空信道多径的俯仰角-方位角-时延-多普勒频移四维参数联合估计。本算法同时具备：无需训练序列或预先知道信道冲激响应、可用于多用户环境、每个用户的多径数目可以超过阵元数、且多参数自然配对等特点。在算法处理过程中，可同时从码域、空域、时域和频域对信道中的多址干扰、符号间干扰和多普勒频率干扰进行抑制，大大提高了智能天线抗干扰性能。(2)为了提高多维参数估计时的搜索速度，本文还采用了粒子群优化(PSO)算法进行多维搜索。针对基本粒子群优化算法只适合搜索全局最优的局限性，本文应用“函数变换”将原空时谱函数变换为等高峰函数，并通过修改粒子速度更新公式和“聚积处理”等手段实现了PSO算法在空时谱多峰位搜索中的应用。
最后，论文对采用智能天线后移动通信系统的信噪比、系统容量等方面进行了分析，并讨论了智能天线对原有系统可能的影响。
Smart antennas can improve the quality of communication links, greatly increase the capacity of communication systems and enhance the efficiency of frequency, which has become a "hotspot" of research in mobile communication. This dissertation dissertated the basic theory and relevant techniques of smart antennas in mobile communication systems, and detailedly studied on some key problems, which including the spatial-temporal channel property and modeling theory, adaptive digital beamforming algorithms, super-resolution algorithms for DOA estimation (especially, effective algorithms for coherent multipaths environment), interference suppression techniques (especially suppression of coherent interference), joint multi-dimension parameter estimation in spatial-temporal channel, and the 2D spatial-temporal processing.
As for the spatial-temporal channel property and modeling theory, firstly, the thesis introduced the property of wireless spatial-temporal channel, and theoretically analyzed the effects on the frequency correlativity, temporal correlativity and spatial correlativity caused by delay spreading, Doppler frequency spreading and angle spreading, respectively. (1) For different scattering environments in mobile communications, we theoretically deduced and numerically simulated the correlativity of smart antennas, and obtained the relationship between antennas correlativity and the distributing property of scattering, which can be provided as theoretical reference for smart antennas designs. (2) As for channel modeling theory, the thesis simply introduced the conventional models including the Lee's model and its improved model, the Geometrically Based Single Bounce (GBSB) model, the Gaussian Wide Sense Stationary Uncorrelated Scattering (GWSUS) model and the Expanded Tapped-Delay-Line model. Then, base on the power-delay spectrum and power-angle spectrum suggested by ITU for different environments, we proposed a method based on statistical property to simulate the spatial-temporal channel. The method is simple and effective, can easily construct different channels. Simulation results confirmed the model can reflect the channel property in spatial domain, temporal domain and frequency domain simultaneously.
As to the beamforming techniques, the thesis simply introduced two kind of non-blind algorithms—LMS and RLS, detailedly studied on the two kind of blind algorithms—Constant Modules Algorithm (CMA) and Least Square De-spread Re-spread Multi Target Constant Modules Algorithm (LS-DRMTCMA), and analyzed their performance via simulation experiments. (1) Aimed at the contradictory between convergence speed and the steady-state errs in the conventional CMA, based on a new cost function, the thesis proposed a novel method to control the step-size adaptively. The algorithm uses Gauss function to realize the mapping from constant modulus err to step-size, its parameters are simple to be control, and it has super-linear accelerating effect, can obtain excellent convergence speed, small steady-state err and excellent noise resisting ability simultaneously, which can improve the performance of constant modulus array. (2) In non-stationary channel, the relative power of the signals input in the same stage will change quickly owing to the random fading, however, the CMA simply tends to capture the strongest signal, which might cause the signals captured by each stages to fluctuate, and each stage can't maintain a steadily capture or tracing to the target user. So, based on the improved algorithm proposed before, we further introduced a dissymmetrical mechanism to control the step-size, which can not only ensure each stage to capture the target user quickly, but also ensure each stage to trace the target user steadily, and enhance the anti-fading ability of the array.
As to DOA estimation, the thesis simply introduced the commonly used DOA estimation algorithms. The thesis noticed the problems that, MUSIC and ESPRIT can't deal with coherent sources, the number of DOAs that can be estimated can't exceed the element number of array, the algorithms are not fitted for colored noise, and it's difficult to pair the DOAs with the users. Aiming at the cellular system, according to uniform linear array and uniform circular array respectively, the thesis studied on algorithms that suitable for coherent mutipath environment in cellular systems. (1) For uniform linear array, using the fourth order cumulant of array outputs, we realized the blind estimation of spatial signature in uplink, and use it to estimate the multi-user's DOAs in coherent mutipath environment. The algorithm is not depended upon the specific property of signals, can be employed to additive arbitrary Gaussian noise, can estimate 2M~2/3 DOAs by M elements, can breakthrough the limit of conventional MUSIC and ESPRIT, and can pair the multipath with users automatically. Through simulation experiments, the relations between estimation variance, SNR and snapshot number were studied, which confirmed the availability and robustness of the algorithm. Based on spatial signature estimation, the thesis constructed a spatial filter bank, and realized the separation of multi-user and the recovery of sources. (2) For uniform circular array, the thesis firstly introduced the element space MUSIC, real beam space UCA-RB-MUSIC and UCA-ESPRIT, then studied and evaluated their performance via simulation experiment. Because all algorithms mentioned above are invalid in coherent environment, and uniform circular arrays are not fit for directly spatial smoothing, the thesis used a pre-processing technique to transform the UCA of element space into a virtual uniform linear array of mode space, and then used spatial smoothing to realize the DOA estimation for coherent sources in UCA.
In coherent multipath environment, the performance of smart antenna will decline dramatically. The thesis proposed an improved method to overcome the problem. (1) To overcome the shortcoming of the existing spatial smoothing algorithm, and base on the idea that fully utilize each auto-correlation matrix and cross-correlation matrix of sub-arrays, the thesis proposed an algorithm calledadaptive-globally-weighted-spatial-smoothing (AGWSS), and greatly improved the de-correlation ability of small array. The algorithm is completely adaptive and does not need the prior knowledge of the source angles or pre-estimation of source angles. (2) In AGWSS, for the first time, the thesis proposed an idea of symmetrical processing (in page 121) to ensure the Hermitian property of the smoothed correlation matrix, and, base on this idea, the thesis deduced the closed-form solution of the optimal smoothing weight matrix for the AGWSS (i.e., explicit formulation, not implicit formulation as some other algorithms). (3) Furthermore, considering the requirement of semi-definite to the smoothed correlation matrix in some applications, using symmetrical processing techniques, under the constraints that the smoothed correlation matrix should be Toeplitzian, Hermitian and semi-definite, and based on the Primal-Dual-Interior-Point-Barrier-Function method, the thesis proposed an algorithm called semi-definite adaptive globally weighted spatial smoothing (SD-AGWSS). The algorithm was used to estimate DOAs in coherent environment, and greatly improved the estimating performance, especially, when the coherent sources are close or the SNR is very low, the resolution can be enhanced greatly.
In coherent multipath environment, the commonly used beamforming algorithms will become ineffective, and the desired signal in array might be cancelled. The conventional spatial smoothing technique has poor de-correlating ability, and it will reduce the "effective aperture" of array. (1) The thesis proposed an improved beamforming scheme: Firstly, adopting the AGWSS algorithm proposed in this thesis, which, through globally weighted averaging of the auto-correlation matrices and cross-correlation matrix of each subarray, can de-correlate the coherency to the utmost extent; and then, using the linear-constrained-minimum-variance (LCMV) criterion for directly matrix inverse, the optimum weight vector of subarray beamformer can be found; at last, in order to avoid the aperture loss caused by smoothing and fully utilize the residual freedom degrees, the thesis proposed a technique of second-weighting under the criterion of null deepening or noise gain minimization respectively, which greatly improved the ability of array to suppress coherent (or correlative) interference and noise. (2) By theoretical analysis and simulations, the thesis compared the de-correlating ability of different smoothing algorithms for the first time. (3) Using freedom degree theory, for the first time, the thesis analyzed and compared the conditions for subarray division in different smoothing algorithms: for an array with M elements, WSS can suppress ((M-1)~(1/2)-1) coherent interferences, but AGWSS can suppress (M/2-1) coherent interferences. Theoretical analysis and simulations showed that the AGWSS outperforms the existing spatial smoothing algorithms obviously, and especially it's suitable for small smart antennas in mobile communications.
The thesis further studied the problem of joint multi-dimension parameters estimation of spatial-temporal channel in smart antennas and its techniques of interference suppression. (1) For circular array in TD-SCDMA system, it provided an architecture of expanded spatial-temporal array, and realized the joint 4D parameters estimation of elevation, azimuth, delay and doppler frequency-offset for multipaths in spatial-temporal channel. The method does not need training sequences or pre-estimation of channel impulse response, can work in multi-user environments. The multipaths number of each user can exceed the element number of array, and all parameters are paired automatically. During the procedure, from PN code domain, spatial domain, temporal domain and frequency domain, the method can simultaneously suppressed the MAI, ISI and Doppler frequency interference in the channel, which greatly improved the interference suppression ability of smart antennas. (2) In order to increase the searching speed in multi-dimension parameters estimation, Particle Swarm Optimization (PSO) algorithm was employed to realize multi-dimension searching. Considering the limit that the basic PSO is only fit to search the global optimum, the thesis transformed the original spectrum function into an equal-peaks function, and, through some measures, such as modification to the particle speed updating formula and "congestion handling", it realized the application of PSO in the peaks searching for spatial-temporal spectrum.
At last, the thesis analyzed the SNR, system capacity of mobile communication systems employing smart antennas, and discussed the possible effects on original system caused by smart antennas.
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