Mean-Squared Error Sampling and Reconstruction in the Presence of Noise

One of the main goals of sampling theory is to represent a continuous-time function by a discrete set of samples. Here, we treat the class of sampling problems in which the underlying function can be specified by a finite set of samples. Our problem is to reconstruct the signal from nonideal, noisy samples, which are modeled as the inner products of the signal with a set of sampling vectors, contaminated by noise. To mitigate the effect of the noise and the mismatch between the sampling and reconstruction vectors, the samples are linearly processed prior to reconstruction. Considering a statistical reconstruction framework, we characterize the strategies that are mean-squared error (MSE) admissible, meaning that they are not dominated in terms of MSE by any other linear reconstruction. We also present explicit designs of admissible reconstructions that dominate a given inadmissible method. Adapting several classical estimation approaches to our particular sampling problem, we suggest concrete admissible reconstruction methods and compare their performance. The results are then specialized to the case in which the samples are processed by a digital correction filter     

Minimum Mean-Squared Error Iterative Successive Parallel Arbitrated Decision Feedback Detectors for DS-CDMA Systems

In this paper we propose minimum mean squared error (MMSE) iterative successive parallel arbitrated decision feedback (DF) receivers for direct sequence code division multiple access (DS-CDMA) systems. We describe the MMSE design criterion for DF multiuser detectors along with successive, parallel and iterative interference cancellation structures. A novel efficient DF structure that employs successive cancellation with parallel arbitrated branches and a near-optimal low complexity user ordering algorithm are presented. The proposed DF receiver structure and the ordering algorithm are then combined with iterative cascaded DF stages for mitigating the deleterious effects of error propagation for convolutionally encoded systems with both Viterbi and turbo decoding as well as for uncoded schemes. We mathematically study the relations between the MMSE achieved by the analyzed DF structures, including the novel scheme, with imperfect and perfect feedback. Simulation results for an uplink scenario assess the new iterative DF detectors against linear receivers and evaluate the effects of error propagation of the new cancellation methods against existing ones.     

Sparse Bayesian Learning Approach to Adaptive Beamforming Assisted Receivers

In this letter, a new adaptive beamforming assisted receiver based on sparse Bayesian learning is proposed. We consider a general probabilistic Bayesian learning framework for obtaining sparse solutions to adaptive beamforming assisted receivers to improve the performance of an adaptive beamforming assisted receiver based on the minimum mean squared error (MMSE) scheme. Simulation experiments show that the bit error rate (BER) performance of the sparse Bayesian beamforming receiver shows an outstanding BER performance compared to MMSE beamforming receivers     

谱相减与波束形成相结合的语音增强算法

根据阵列信号语音增强的思想,提出一种基于频城处理的谱相减与波束形成相结合的语音增强结构。结构为多路信号输入,每路含噪信号在谱相减后,增加了波束形成结构,不仅有效地消除了背景噪声,也抑制了谱相减后的音乐噪声。并使用该算法对实际环境中采集到的含噪语音信号进行了仿真,结果显示经过该系统处理后的增强语音的信噪比有了较大的提高,主观试听效果也很好。     

基于到达角误差约束的稳健宽带波束合成算法

针对阵列天线存在系统误差的情况,在Frost结构的基础上提出了一种改进的稳健宽带波束合成算法.该算法以信号到达角(DOA)误差为约束条件合成期望信号,并把滤波器优化设计转化为凸优化问题,使用内点迭代法有效解决,进一步使得期望的信号响应具有一定的波动性,从而使得更多的自由度应用在干扰和噪声的抑制上,达到优化加权制的目的....     

针对循环频率误差的稳健CAB算法

当循环频率估计存在误差时,循环自适应波束形成算法的性能会显著下降。针对这一不足,本文提出了对循环频率误差稳健的循环自适应波束形成算法。仿真实验表明,当存在循环频率误差时,本文提出的算法性能接近没有循环频率误差时循环自适应波束形成算法的性能。     

阵列误差对Capon波束形成算法的影响分析

针对阵列误差存在时经典(Capon)波束形成算法的性能严重恶化问题,介绍了均匀圆阵阵列流型下的Capon波束形成算法,对阵列天线各阵元间的幅度误差、相位误差、水平位置误差和垂直位置误差进行了数学建模,仿真分析了各种阵列误差对Capon波束形成算法的影响,并给出了该影响的量化分析结果,从而对该算法工程实现时的指标确定提供依据。     

Multiple Composite Hypothesis Testing: A Competitive Approach

There are many problems in science and engineering where the signals of interest depend simultaneously on continuous and q-ary parameters, i.e. parameters which can take only one out of q possible values. This problem is generally known as multiple composite hypothesis testing. The probability function of the observed data for a given hypothesis is uncertain, as it depends on the parameters of the system. When there is no statistical model for the unknown continuous parameters, the GLRT is the usual criterion for the binary case. Although the GLRT philosophy can be extended to accommodate multiple composite hypotheses, unfortunately the solution is not satisfactory in the general case. In this paper, we restrict the general scenario and consider problems with q-ary input vectors and linear dependence on a unique set of continuous parameters; i.e. all the hypotheses depend on the same set of parameters. Direct application of the GLRT is feasible in this case, but it suffers from an exponential increase in complexity with data length. In this paper, we derive a low-complexity stochastic gradient procedure for this problem. The resulting algorithm, which resembles the LMS, updates the unknown parameters only along the direction of the winning hypothesis. This approach also presents similarities with competitive learning techniques, in the sense that at each iteration the different hypotheses compete to train the parameters. The validity of the proposed approach is shown by applying it to blind system identification/equalization, and chaotic AR(1) model estimation.     

RIS-Aided Constant-Envelope Beamforming for Multiuser Wireless Power Transfer:A Max-Min Approach

As a revolutionary hardware technology that can reconfigure the propagation environment,reconfigurable intelligent surfaces(RISs)have been regarded as a promising solution to enhance wireless networks.In this paper,we consider a multiuser multiple-input single-output(MISO)wireless power transfer(WPT)system,which is assisted by several RISs.In order to improve energy efficiency and reduce hardware cost,we consider that the energy transmitter(ET)in the WPT system is equipped with a constant-envelope analog beamformer,instead of a digital beamformer.Focusing on user fairness,we study a minimum received power maximization problem by jointly optimizing the ET beamforming and the RIS phase shifts,subject to the constant-envelope constraints.We iteratively solve this non-convex maxmin problem by leveraging both the successive convex approximation(SCA)method and the alternating direction method of multipliers(ADMM)algorithm.Numerical results demonstrate the effectiveness of the proposed algorithm and show attractive performance gain brought by RISs.     

On Downlink Beamforming Methods: Capacity and Error Probability Performance

In space-division multiple access (SDMA), different beamforming or space-domain precoding techniques can be applied. We investigate two different space-domain precoding methods, the maximum capacity (MC) and the minimum mean square error (MMSE) precoders, for the downlink channel. It is shown that the MMSE precoding, which is practically implementable, can provide a reasonable performance in terms of the capacity and error probability, while the MC precoding is not practical (although it is optimum in terms of the capacity). Space-domain precoding methods are also applied to code-division multiple access (CDMA) systems.This work was supported by the HY-SDR Research Center at Hanyang University, Seoul, Korea, under the ITRC Program of MIC, Korea.Jinho Choi was born in Seoul, Korea. He recieved the B.E. degree (magna cum laude) in electronics engineering from Sogang University in 1989 and the M.S.E. and Ph.D. degree in electrical engineering from the Korea Advanced Institute of Science and Technology in 1991 and 1994, respectively. Currently he is a Senior Lecturer in the School of Electrical Engineering and Telecommunications,University of New South Wales, Australia. Dr. Choi received the 1999 Best Paper Award of Signal Processing from EURASIP.Seungwon Choi received the B.S. degree from Hanyang University, Seoul, Korea, in 1980 and the M.S. degree from Seoul National University, Seoul, in 1982, both the electronic engineering. He received the M.S. degree in computer engineering in 1985 and the Ph.D degree in electrical engineering in 1988 from Syracuse University, Syracuse, NY.From 1982 to 1984, he was with LG Electronics Co. Ltd., Seoul, where he helped developed the 8-mm camcorder system. From 1988 to 1989, he was with the Department of Electrical and Computer Engineering, Syracuse University, as an Assistant Professor. In 1989, he joined the Electronics and Telecommunications Research Institute, daejeon, Korea, where he developed the adaptive algorithm for real-time application in secure telephone systems. From 1990 to 1992, he was with yhe Communication Research Laboratory, Tokyo, Japan, as a science and Technology Agency Fellow, developing adaptive antenna array system and adaptive equalizing filters for applications in land-mobile communications. He joined Hanyang University, Seoul, in 1992 as an Assistant Professor. He is a Professor in the School of Electrical and Computer Engineering, Hanyang University. His research interests include digital communications and adaptive signal processing with a recent focus on the real-time implementation of smart antenna system for 3G mobile communication system.     

一种天波超视距雷达自适应波束形成方法

天波超视距雷达利用自适应波束形成技术抑制短波干扰以增强探测性能,但是在相干处理间隔内电离层运动通常会使干扰呈现明显的空间非平稳性,增加了自适应处理的难度.由于在距离-多普勒域上进行自适应波束形成时电离层的影响显著降低,文中提出了在距离-多普勒域上对雷达阵列接收信号进行自适应波束形成的方法.实测数据处理表明,该方法能有效地克服干扰的非平稳性以抑制干扰,而且易于工程实现.     

时间相干信道下波束赋形系统的有限反馈方法

该文提出一种新的基于树形码书的有限反馈方法,由于相邻帧的时间相干性,信道向量的量化码字可建模为一阶有限状态马尔可夫链,当前帧信道向量被量化到前一帧最大转移概率码字的子码字上,该子码字的索引以1 bit反馈给发射端。链路仿真结果表明本文所提方法相比普通反馈方法可明显改善误码率性能,某些条件下还可降低反馈速率。     

基于传声器阵列的近场宽带波束形成方法

提出了一种适合于近场宽带传声器阵列处理的空时子带波束形成新方法。该方法通过将一个空域子带阵列和时域子带多速率滤波器组合并来同时获得空域和时域两种子带系统的优点。计算机仿真比较了其与全带自适应波束形成方法的性能,结果表明该方法对干扰有较强的抑制能力,改善了宽带波束形成频域不一致问题,并且能够并行处理,为实际语音通信系统的应用提供了一种有利途径。     

一种用于宽带机载SAR的空变相位误差补偿算法

该文提出了一种用于机载合成孔径雷达(SAR)的方位向空变相位误差补偿算法。传统的机载SAR运动补偿技术只补偿方位向相位误差的空不变分量,而常常忽略空变分量。对于高分辨率宽带SAR,传统的运动补偿算法由于没有补偿空变相位误差,不能满足分辨率要求。该文提出的子孔径算法通过在距离-多普勒域将SAR数据分为若干子孔径,每个子孔径数据进行单独的相位误差补偿,从而实现了空变相位误差的补偿。在传统的运动补偿处理中嵌入该算法可以大大提高SAR图像方位向分辨率。     

高信噪比大指向误差环境中的波束形成

基于协方差矩阵加权的波束形成方法(SMI)在计算加权向量时引进干扰和噪声的影响,投影方法在计算加权向量时引进干扰信号的影响,这些都造成了波束形成效果的不理想。在有用信号的信噪比较高且出现较大的指向误差时,SMI和投影方法失效。本文针对上述问题提出了利用信号周期平稳性,采用周期波束形成方法来解决上述问题。模拟实验验证了本文的方法。     

一种新型波束赋形算法

为了使智能天线获得最大的处理增益,基于传统的on-off波束赋形算法,提出了一种新型的波束赋形算法。该算法通过利用最速下降法最大化用户数据的SINR,获得入射平面波到达各阵元相对到达参考阵元距离差的最优解,从而极大化目标函数,在此基础上,求取智能天线阵元的最优波束赋形权值。仿真表明,采用论文提出的算法可以大大改善智能天线系统性能。     

Adaptive Minimum Symbol Error Rate Beamforming Assisted Detection for Quadrature Amplitude Modulation

We consider beamforming assisted detection for multiple antenna aided multiuser systems that employ the bandwidth efficient quadrature amplitude modulation scheme. A minimum symbol error rate (MSER) design is proposed for the beamforming assisted receiver, and it is shown that this MSER design provides significant performance enhancement, in terms of achievable symbol error rate, over the standard minimum mean square error (MMSE) design. A sample-by-sample adaptive algorithm, referred to as the least symbol error rate, is derived for adaptive implementation of the MSER beamforming solution. The proposed adaptive MSER scheme is evaluated in simulation using Rayleigh fading channels, in comparison with the adaptive MMSE benchmarker.     

天线校准误差建模及对开环波束赋形技术的影响

时分双工系统中上下行无线信道具有互易性,使得基站可以利用获得的上行信道信息实施开环波束赋形技术.但是基站天线口与基带处理模块之间的射频通道并不对称,在进行校准后由于硬件精度所限会有天线校准误差.为此,根据实测数据对天线校准误差进行建模,通过仿真得出,射频通道校准幅度误差标准差在1 dB、角度误差在20°以内时,开环波束赋形技术在误码率为10-5时性能损失小于1 dB.并由此给出了对天线校准误差的要求.