Adaptive multistage beamforming using cyclic higher orderstatistics (CHOS)

A new blind beamforming algorithm for signals that exhibit higher order cyclostationarity is presented. Exploiting some previous theoretical developments, we show how cyclic cumulants of the received signals can be used to obtain the weights of the beamformer that perform blind extraction. The method is based on a spatial interpretation of a deconvolution procedure known as the super-exponential algorithm. The basic block processing algorithm is made fully adaptive using an adaptive URV scheme and applied to a typical mobile communications scenario where several cochannel interferers corrupt the signals of interest     

Fast adaptive super-exponential multistage beamforming for cellularbase-station transceivers with antenna arrays

A new blind adaptive beamforming algorithm is introduced. We show how cumulants of the received signals can be used to obtain the weights of the beamformer that perform blind extraction. The method is based on a spatial interpretation of a deconvolution procedure known as the super-exponential algorithm. The basic block processing algorithm is attractive because it can be transformed in an efficient adaptive algorithm which exhibits good tracking capability. To prove the effectiveness of the idea, we show results for a typical mobile communications scenario where several cochannel interferers corrupt the signals of interest     

基于稀疏时频分解的盲波束形成算法

针对现有盲波束形成算法通用性差,所需采样数据量大等问题,该文提出一种基于稀疏时频分解的盲波束形成算法。算法首先将传统的短时傅里叶变换转化为稀疏重构问题,利用交替分裂Bregman算法进行迭代求解。然后利用对各阵元的接收信号进行稀疏时频分解的结果,结合聚类和不确定集方法,实现导向矢量的最优估计。最后利用MVDR算法获得最优权矢量。该算法无需利用信号统计特性,实现了高效的盲波束形成。仿真实验结果表明,该算法所需数据量小,迭代步骤易于工程实现,较现有盲波束形成算法输出性能更优,适用范围更广。     

Batch processing algorithms for blind equalization using higher-order statistics

Statistical signal processing has been one of the key technologies in the development of wireless communication systems, especially for broadband multiuser communication systems which severely suffer from intersymbol interference (ISI) and multiple access interference (MAI). This article reviews batch processing algorithms for blind equalization using higher-order statistics for mitigation of the ISI induced by single-input, single-output channels as well as of both the ISI and MAI induced by multiple-input, multiple-output channels. In particular, this article reviews the typical inverse filter criteria (IFC) based algorithm, super-exponential algorithm, and constant modulus algorithm along with their relations, performance, and improvements. Several advanced applications of these algorithms are illustrated, including blind channel estimation, simultaneous estimation of multiple time delays, signal-to-noise ratio (SNR) boost by blind maximum ratio combining, blind beamforming for source separation in multipath, and multiuser detection for direct sequence/code division multiple access (DS/CDMA) systems in multipath.     

Joint hybrid beamforming and power splitting design in millimeter-wave simultaneous wireless information and power transfer system

A joint hybrid beamforming and power splitting(JHBPS) design problem for simultaneous wireless information and power transfer(SWIPT) in millimeter-wave(mmWave) system is studied.The considered scenario is a multi-antenna base station(BS) transfers information and energy simultaneously to multiple single-antenna receivers.BS adopts hybrid digital and analog beamforming architecture to reduce hardware costs.Receivers separate acquired signals with power splitters either for information decoding(ID) or energy harvesting(EH).The aim is minimizing total transmission power by joint design of hybrid beamforming and PS under ID and EH requirements.It is difficult to obtain the optimal hybrid beamformer directly since the analog beamformer and digital beamformer are multiplied.Therefore,a two-stage algorithm is proposed to solve the problem.In the first stage,the optimal beamformer and PS ratios are obtained by solving the joint transmission beamforming and PS design problem.In the second stage,the optimal beamformer is approximated with the product of analog beamformer and digital beamformer.The superiority of proposed algorithm over the existing algorithms is demonstrated through simulations.Moreover,the effectiveness of approximation algorithm is testified.     

一种基于恒模算法的多用户盲波束形成新方法

提出了一种适用于多用户的盲波束形成新方法.该方法基于最小二乘恒模算法,当最小二乘恒模算法收敛于某一信号后,我们导出了算法的权向量与其它用户波达方向的关系,进而在不同用户的波达方向上形成初始增益,从而实现对所有用户的波束形成.文中给出了算法的并行和串行实现方案.     

Blind IB-MSNR Beamforming for DSSS-based Communication Systems

The spread spectrum technique is widely used and effective in combating narrowband interference with a moderate power as well as co-channel interference (CCI) and noise. However, it requires a configuration with long signature sequence for interference suppression, which is practically impossible. In addition, a system will exhibit a substantial degradation in performance due to both strong interference and desired coherent signals introduced by multipaths. In this paper, a novel detector is first proposed to determine the number of strong interferers for direct sequence spread spectrum (DSSS) based communication systems. Furthermore, the blind interference-blocked (IB) maximum signal-to-noise ratio (MSNR) beamforming is then proposed to collect desired coherent signals and to suppress strong interference. Theoretical analysis and numerical results demonstrate that the proposed IB-MSNR beamformer can achieve nearly the same performance as the optimal non-blind beamformer.     

Super-exponential methods for blind detection of asynchronous CDMA signals over multipath channels

In this letter, code-constrained super-exponential algorithms (CSEA) are presented for blind detection of asynchronous short-code direct-sequence code-division multiple-access signals over multipath channels. Constrained SEA leads to the extraction of the desired user whereas unconstrained SEA leads to the extraction of any one of the actives users. The results are further improved by following the constrained SEA by unconstrained SEA. Convergence of the constrained SEA is proved and simulation examples are provided to illustrate the proposed approaches.     

Applications of cumulants to array processing. III. Blindbeamforming for coherent signals

For pt.II see ibid., vol.43, no.7, p.1663-7, 1995. We provide a cumulant-based blind beamforming method for recovery of statistically independent narrowband source signals in the presence of coherent (or perfectly correlated) multipath propagation. Our method is based on the fact that for a blind beamformer, the presence of coherent multipaths is equivalent to the case of independent sources with a different steering matrix. Our approach is applicable to any array configuration having unknown response. Signal sources must have nonzero fourth-order cumulants. There is no need to estimate the directions of arrival. Our method maximizes signal-to-interference plus noise ratio (SINR). A comparable result does not exist using just second-order statistics     

Asymptotic properties of the algebraic constant modulus algorithm

The algebraic constant modulus algorithm (ACMA) is a noniterative blind source separation algorithm. It computes jointly beamforming vectors for all constant modulus sources as the solution of a joint diagonalization problem. We analyze its asymptotic properties and show that (unlike CMA) it converges to the Wiener beamformer when the number of samples or the signal-to-noise ratio (SNR) goes to infinity. We also sketch its connection to the related JADE algorithm and derive a version of ACMA that converges to a zero-forcing beamformer. This gives improved performance in applications that use the estimated mixing matrix, such as in direction finding     

A New Post-filter Algorithm Combined with Two-step Adaptive Beamformer

The optimal microphone array, in the sense of minimum mean square errors (MMSE), includes two processing blocks: the minimum variance distortionless response (MVDR) beamformer and the single-channel Wiener filter, which acts as post-filter. In this paper, we propose a new post-filter algorithm based on assumptions that both the noise power attenuation factor (NPAF) and signal power attenuation factor (SPAF) are time invariant in the reverberant room. The algorithm recursively estimates both factors from available measurements and uses them in estimation of the post-filter parameters. Additionally, to overcome the problem of the poor performance of the MVDR beamformer in reverberant conditions, we propose the usage of the two-step (TS) MVDR algorithm. This algorithm improves the robustness of the beamformer and its ability to suppress the interferences using an estimate of the desired speaker transfer function. Although TS MVDR beamformer and proposed post-filter can work separately, or combined with other algorithms, the best performance is obtained when they work together. The performance of the proposed combination of new post-filter algorithm and TS MVDR beamformer is tested in a simulated reverberant room and compared with similar algorithms, which gave rather good results.     

CDMA系统智能天线盲自适应波束形成

给出了基于最大化信号对干扰和噪声的功率比(MSINR)准则的盲自适应波束形成在线递推算法,旨在提高DS-CDMA系统中智能天线的性能.将MSINR准则转化为一种新的等价的无约束准则函数,通过最大化此准则函数来在线估计最优波束形成向量.算法直接利用了DS-CDMA系统解扩前和解扩后的观测信号,无须训练序列.通过在线迭代估计,降低了计算波束权值的复杂度.不同通信环境中的仿真结果表明,该算法具有较高的估计精度和很好的抗多址干扰能力.     

Adaptive Beamforming and Recursive DOA Estimation Using Frequency-Invariant Uniform Concentric Spherical Arrays

This paper proposes recursive adaptive beamforming and broadband 2-D direction-of-arrival (DOA) estimation algorithms for uniform concentric spherical arrays (UCSAs) having nearly frequency-invariant (FI) characteristics. The basic principle of the FI-UCSA is to transform the received signals to the phase mode and remove the frequency dependency of individual phase modes through a digital beamforming network. Hence, the far-field pattern of the array is determined by a set of weights. Thanks to the FI characteristic, traditional narrowband adaptive beamforming algorithms such as minimum variance beamforming and the generalized sidelobe canceller method can be applied to the FI-UCSA. Simulation results show that the proposed adaptive FI-UCSA beamformer achieves a lower steady-state error and converges faster than the conventional tapped-delay line approach while requiring fewer adaptive coefficients. A new broadband 2-D DOA estimation algorithm using ESPRIT techniques for FI-UCSA is proposed to recursively estimate the DOAs of the moving targets. Simulation results show that the proposed DOA estimation algorithm achieves a satisfactory performance for slowly varying sources at low arithmetic complexity.      

Blind multiuser detection for code-hopping DS-CDMA signals in asynchronous multipath channels

Blind detection of a desired user's signal in a code-hopping (CH) direct sequence code-division multiple access (CDMA) system is considered. In CH CDMA systems each user switches between a predetermined set of short-code sequences. A user signal in such systems may be treated as the superposition of several virtual short-code signals. A code-constrained inverse filter criterion (IFC)-based blind detector for short-code CDMA signals in asynchronous multipath channels to detect a desired user's signal was recently presented by Tugnait and Li (2001). A novel approach combining the code-constrained IFC and a penalty function is proposed to simultaneously extract all virtual users associated with a given CH user. Global minima of the proposed cost function are analyzed. An extension of an existing subspace-based approach is also investigated. An illustrative simulation example is provided where the proposed algorithm is compared with a clairvoyant matched filter receiver, two linear minimum mean-square error (MMSE) receivers with channels known, and the subspace-based approach.     

多径衰落信道MPSK信号超指数迭代盲解调算法

为了提高多径衰落信道下的盲解调性能,提出了一种结构简单的MPSK信号盲解调算法。首先利用超指数迭代分数间隔盲均衡器实现联合定时同步与均衡,然后对均衡器输出信号进行非线性变换实现载波频偏的估计,最后利用二阶数字判决锁相环跟踪相位变化纠正剩余频偏和相偏。仿真结果表明,在多径衰落信道条件下,与现有算法相比,基于超指数迭代分数间隔盲均衡器的盲解调算法实现简单,误码率低,而且具有收敛速度快、性能稳定等优点。     

Two-dimensional frequency-domain blind system identification usinghigher order statistics with application to texture synthesis

In this paper, Shalvi and Weinstein's (1993) super-exponential (SE) algorithm using higher order statistics for blind deconvolution of one-dimensional (1-D) linear time-invariant systems is extended to a two-dimensional (2-D) SE algorithm. Then, a 2-D frequency-domain blind system identification (BSI) algorithm for 2-D linear shift-invariant (LSI) systems using the computationally efficient 2-D SE algorithm and the 2-D linear prediction error filter is proposed. In addition to the LSI system estimate, the proposed BSI algorithm also provides a minimum mean square error (MMSE) equalizer estimate and an MMSE signal enhancement filter estimate. Then, a texture synthesis method (TSM) using the proposed BSI algorithm is presented. Some simulation results to support the efficacy of the proposed BSI algorithm and some experimental results to support the efficacy of the proposed TSM are presented. Finally, some conclusions are drawn     

一种能有效接收相干信号的波束形成技术

在假设事先估计得到不相关干扰信号方向的条件下,本文提出了一种能有效接收相干信号的波束形成方法.该方法首先利用估计得到的不相关干扰信号的方向构造变换矩阵,然后基于变换矩阵估计得到期望信号和相干干扰信号的合成导向矢量,最后利用得到的合成导向矢量和阵列相关矩阵求得波束形成的权矢量.计算机仿真结果证实本文所提方法基本上达到理论上的最优性能,且能快速收敛.     

GSVD-based optimal filtering for single and multimicrophone speech enhancement

A generalized singular value decomposition (GSVD) based algorithm is proposed for enhancing multimicrophone speech signals degraded by additive colored noise. This GSVD-based multimicrophone algorithm can be considered to be an extension of the single-microphone signal subspace algorithms for enhancing noisy speech signals and amounts to a specific optimal filtering problem when the desired response signal cannot be observed. The optimal filter can be written as a function of the generalized singular vectors and singular values of a speech and noise data matrix. A number of symmetry properties are derived for the single-microphone and multimicrophone optimal filter, which are valid for the white noise case as well as for the colored noise case. In addition, the averaging step of some single-microphone signal subspace algorithms is examined, leading to the conclusion that this averaging operation is unnecessary and even suboptimal. For simple situations, where we consider localized sources and no multipath propagation, the GSVD-based optimal filtering technique exhibits the spatial directivity pattern of a beamformer. When comparing the noise reduction performance for realistic situations, simulations show that the GSVD-based optimal filtering technique has a better performance than standard fixed and adaptive beamforming techniques for all reverberation times and that it is more robust to deviations from the nominal situation, as, e.g., encountered in uncalibrated microphone arrays.     

MIMO Transmit Beamforming Under Uniform Elemental Power Constraint

We consider multi-input multi-output (MIMO) transmit beamforming under the uniform elemental power constraint. This is a nonconvex optimization problem, and it is usually difficult to find the optimal transmit beamformer. First, we show that for the multi-input single-output (MISO) case, the optimal solution has a closed-form expression. Then we propose a cyclic algorithm for the MIMO case which uses the closed-form MISO optimal solution iteratively. The cyclic algorithm has a low computational complexity and is locally convergent under mild conditions. Moreover, we consider finite-rate feedback methods needed for transmit beamforming. We propose a simple scalar quantization method, as well as a novel vector quantization method. For the latter method, the codebook is constructed under the uniform elemental power constraint and the method is referred as VQ-UEP. We analyze VQ-UEP performance for the MISO case. Specifically, we obtain an approximate expression for the average degradation of the receive signal-to-noise ratio (SNR) caused by VQ-UEP. Numerical examples are provided to demonstrate the effectiveness of our proposed transmit beamformer designs and the finite-rate feedback techniques.     

Adaptive joint beamforming and B‐MMSE detection for CDMA signal reception under multipath interference

The combination of antenna array beamforming with multiuser detection can effectively improve the detection efficiency of a wireless system under multipath interference, especially in a fast‐fading channel. This paper studies the performance of an adaptive beamformer incorporated with a block‐wise minimum mean square error(B‐MMSE) detector, which works on a unique signal frame characterized by training sequence preamble and data blocks segmented by zero‐bits. Both beam‐former weights updating and B‐MMSE detection are carried out by either least mean square (LMS) or recursive least square (RLS) algorithm. The comparison of the two adaptive algorithms applied to both beamformer and B‐MMSE detector will be made in terms of convergence behaviour and estimation mean square error. Various multipath patterns are considered to test the receiver's responding rapidity to changing multipath interference. The performance of the adaptive B‐MMSE detector is also compared with that of non‐adaptive version (i.e. through direct matrix inversion). The final performance in error probability simulation reveals that the RLS/B‐MMSE scheme outperforms non‐adaptive B‐MMSE by 1–5 dB, depending on the multipath channel delay profiles of concern. The obtained results also suggest that adaptive beamformer should use RLS algorithm for its fast and robust convergence property; while the B‐MMSE filter can choose either LMS or RLS algorithm depending on antenna array size, multipath severity and implementation complexity. Copyright © 2004 John Wiley & Sons, Ltd.