Spatial and temporal equalization for broadband wireless indoornetworks at millimeter waves

The combined use of adaptive antennas and decision feedback equalization (DFE) is analyzed in a realistic propagation scenario at millimeter waves, taking the direction of arrivals (DOA's) of the received paths into account. The joint antennas and DFE scheme, with one forward filter for each antenna and a single feedback filter (FBF), can be viewed as a spatial and temporal DFE (ST-DFE). The performance of this solution is compared with the cascade of adaptive antenna used for beamforming and DFE. It is found that ST-DFE achieves better performance since it combines the beamforming capability of the antenna array with the equalization properties of the DFE, with great advantages especially when rays arrive from similar angles. The mean square error (MSE) is analytically derived for infinitely long filters in a quasi-static environment with multiple rays having different DOAs, and compared (for the two-path model) with simulation results assuming filters with a small number of taps. Finally, service availability through coverage evaluation is developed and compared with that of a coded-orthogonal frequency division multiplexing (C-OFDM) system     

Antenna diversity combining and finite-tap decision feedbackequalization for high-speed data transmission

The next-generation wireless communication systems are expected to support high-speed data transmission. Associated with high transmission rates, however, is the problem of multipath intersymbol interference (ISI) due to frequency-selective fading. Decision feedback equalization (DFE) and antenna diversity combining are two practical techniques for combating multipath ISI. Through simulations we investigate the performance of diversity combining, together with DFE, under various numbers of antenna branches and equalization taps, in a quasistationary frequency-selective fading environment with additive white Gaussian noise (AWGN) and cochannel interference (CCI). We consider joint optimization combining and power selection diversity combining. We simulate the combiner, using quaternary phase shift keying (QPSK) modulation with up to four antenna branches. Our results show that using antenna diversity and DFE with joint optimization combining provides performance improvement with lower computational complexity, as compared to that of using either DFE or diversity combining alone for combating ISI     

Adaptive Bayesian decision feedback equalizer for dispersive mobileradio channels

The paper investigates adaptive equalization of time-dispersive mobile radio fading channels and develops a robust high performance Bayesian decision feedback equalizer (DFE). The characteristics and implementation aspects of this Bayesian DFE are analyzed, and its performance is compared with those of the conventional symbol or fractional spaced DFE and the maximum likelihood sequence estimator (MLSE). In terms of computational complexity, the adaptive Bayesian DFE is slightly more complex than the conventional DFE but is much simpler than the adaptive MLSE. In terms of error rate in symbol detection, the adaptive Bayesian DFE outperforms the conventional DFE dramatically. Moreover, for severely fading multipath channels, the adaptive MLSE exhibits significant degradation from the theoretical optimal performance and becomes inferior to the adaptive Bayesian DFE     

Optical techniques for reconfiguring microwave phased arrays

Very large phased array antennas, particularly in radar and adaptive receive applications as opposed to communications usages, require large amounts of digital data processing for beamsteering, null-formation, imaging, and signal correlation computations. Such processing requires a computational capability which is effectively proportional to the square of the antenna size, and can readily become one of the main design drivers. This processing bottleneck problem is addressed for large phased array antennas. An approach in terms of parallel processing in the optical domain is presented as a potential solution. The defining equations for a phased array antenna system are given, along with the transfer functions for an embedded optical spatial filter control element. Such a control element is shown to have the potential of rapidly reconfiguring a large phased array antenna without the speed penalties associated with conventional sequential addressing methods. A hypothetical phased array antenna, with optical spatial filter control elements, is simulated in a computer model and performance results are presented     

A step-by-step quasi-Newton algorithm in the frequency domain and its application to adaptive channel equalization

In this paper, a new efficient adaptive filtering algorithm belonging to the Quasi-Newton (QN) family is proposed. In the new algorithm, the involved inverse Hessian matrix is approximated by a proper expansion, consisting of powers of a Toeplitz matrix. Due to this formulation, the algorithm can be implemented in the frequency domain (FD) using the fast Fourier transform (FFT). Efficient recursive relations for the frequency domain quantities updated on a step-by-step basis have been derived. The proposed algorithm turns out to be particularly suitable for adaptive channel equalization in wireless burst transmission systems. Based on this approach, new adaptive linear equalization (LE) and decision feedback equalization (DFE) algorithms have been developed. These algorithms enjoy the combined advantages of QN formulation and FD implementation, exhibiting faster convergence rate than their stochastic gradient counterparts and less computational complexity, as compared with other Newton-type algorithms.     

Subspace methods for blind joint channel estimation and multiuser detection in CDMA systems

Recently developed subspace techniques for blind adaptive multiuser detection are briefly reviewed first. In particular, blind methods based on signal subspace tracking for adapting linear multiuser detectors in AWGN CDMA channels are considered, as well as extensions of these techniques to frequency selective fading channels, dispersive channels, and antenna array spatial processing. In addition, subspace‐based nonlinear adaptive techniques for robust blind multiuser detection in non‐Gaussian ambient noise channels are also described. Several new techniques are then developed within the subspace framework for blind joint channel estimation and multiuser detection, under some specific channel conditions. These include (1) an adaptive receiver structure for joint multiuser detection and equalization in dispersive CDMA channels, (2) a subspace method for joint multiuser detection and equalization in unknown correlated noise, and (3) a method for joint interference suppression and channel tracking in time‐varying fading channels. This revised version was published online in August 2006 with corrections to the Cover Date.     

Fast adaptive equalization/diversity combining for time-varyingdispersive channels

We examine adaptive equalization and diversity combining methods for fast Rayleigh-fading frequency selective channels. We assume a block adaptive receiver in which the receiver coefficients are obtained from feedforward channel estimation. For the feedforward channel estimation, we propose a novel reduced dimension channel estimation procedure, where the number of unknown parameters are reduced using a priori information of the transmit shaping filter's impulse response. Fewer unknown parameters require a shorter training sequence. We obtain least-squares, maximum-likelihood, and maximum a posteriori (MAP) estimators for the reduced dimension channel estimation problem. For symbol detection, we propose the use of a matched filtered diversity combining decision feedback equalizer (DFE) instead of a straightforward diversity combining DFE. The matched filter form has lower computational complexity and provides a well-conditioned matrix inversion. To cope with fast time-varying channels, we introduce a new DFE coefficient computation algorithm which is obtained by incorporating the channel variation during the decision delay into the minimum mean square error (MMSE) criterion. We refer to this as the non-Toeplitz DFE (NT-DFE). We also show the feasibility of a suboptimal receiver which has a lower complexity than a recursive least squares adaptation, with performance close to the optimal NT-DFE     

机载多通道天线SAR自适应杂波抑制

本文通过分析多通道天线SAR的空间几何关系,建立了完善的多通道天线SAR回波信号模型,提出了基于相控阵天线空域阵元混迭式结构形成多个接收通道天线的多通道天线SAR自适应杂波抑制方法和实现结构.理论分析和计算机仿真结果表明,利用多通道天线技术并结合时空二维自适应杂波抑制技术,可以在进行机载SAR成像中对慢速运动目标具有良好的检测性能.     

Adaptive decision feedback equalization for digital satellitechannels using multilayer neural networks

This paper introduces an adaptive derision feedback equalization using the multilayer perceptron structure of an M-ary PSK signal through a TDMA satellite radio channel. The transmission is disturbed not only by intersymbol interference (ISI) and additive white Gaussian noise, but also by the nonlinearity of transmitter amplifiers. The conventional decision feedback equalizer (DFE) is not well-suited to detect the transmitted sequence, whereas the neural-based DFE is able to take into account the nonlinearities and therefore to detect the signal much better. Nevertheless, the applications of the traditional multilayer neural networks have been limited to real-valued signals. To overcome this difficulty, a neural-based DFE is proposed to deal with the complex PSK signal over the complex-valued nonlinear MPSK satellite channel without performing time-consuming complex-valued back-propagation training algorithms, while maintaining almost the same computational complexity as the original real-valued training algorithm. Moreover, a modified back-propagation algorithm with better convergence properties is derived on the basis of delta-bar-delta rule. Simulation results for the equalization of QPSK satellite channels show that the neural-based DFE provides a superior bit error rate performance relative to the conventional mean square DFE, especially in poor signal-to-noise ratio conditions     

Joint coding and decision feedback equalization for broadbandwireless channels

This paper introduces a new approach for joint convolutional coding and decision feedback equalization (DPE). To minimize error propagation, the DFE uses a combination of soft decisions and delayed tentative decisions to cancel intersymbol interference (ISI). Soft decisions are obtained by passing the DFE output through a (soft) nonlinear device. This simple method is shown to perform almost as well as an optimum soft feedback approach on wireless channels with diversity. Tentative decisions from the Viterbi decoder are used to cancel ISI due to multipath with large delays, thus remedying the increasing effect of error propagation in channels with large delay spreads. We consider the use of this soft/delayed feedback DFE (S/D-DFE) technique in broadband wireless channels (with delay spreads up to several tens of the symbol period) typical in high-bitrate mobile data applications. Simulation results indicate that the proposed joint coding and S/D-DFE technique performs to within 1-2 dB [in required signal-to-noise ratio (SNR)] of an ideal coded DFE without error propagation. When combined with antenna diversity and a reduced-complexity DFE concept with adaptive feedforward tap assignment, it provides high packet throughput against Rayleigh fading, severe delay spreads, and high Doppler rates     

RLS Algorithm with Variable Fogetting Factor for Decision Feedback Equalizer over Time-Variant Fading Channels

In a high-rate indoor wireless personal communication system, the delay spread due to multipath propagation results in intersymbol interference (ISI) which can significantly increase the transmission bit error rate (BER). Decision feedback equalizer (DFE) is an efficient approach to combating the ISI. Recursive least squares (RLS) algorithm with a constant forgetting factor is often used to update the tap-coefficient vector of the DFE for ISI-free transmission. However, using a constant forgetting factor may not yield the optimal performance in a nonstationary environment. In this paper, an adaptive algorithm is developed to obtain a time-varying forgetting factor. The forgetting factor is used with the RLS algorithm in a DFE for calculating the tap-coefficient vector in order to minimize the squared equalization error due to input noise and due to channel dynamics. The algorithm is derived based on the argument that, for optimal filtering, the equalization errors should be uncorrelated. The adaptive forgetting factor can be obtained based on on-line equalization error measurements. Computer simulation results demonstrate that better transmission performance can be achieved by using the RLS algorithm with the adaptive forgetting factor than that with a constant forgetting factor previously proposed for optimal steady-state performance or a variable forgetting factor for a near deterministic system.     

Spatio-temporal blind adaptive multiuser detection

We propose blind multiuser detection schemes with antenna arrays, which is based on signal subspace estimation. They are a multichannel extension of the decorrelating and minimum mean-square-error detectors, and therefore they share their immunity to near-far effects. The blind scheme may be seen as an extension of the results in of Wang and Poor (see IEEE Trans. Inform. Theory, vol.44, p.677-90, 1998). However, it is seen that compared with the latter results when spatial diversity is considered, the proposed spatio-temporal detectors offer, with little attendant increase in computational complexity, a better performance. A blind adaptive implementation based on a new orthogonal PAST (projection approximation subspace tracking) algorithm, which is shown to be efficient for subspace tracking, is proposed. Also, we develop a blind estimation of the spatial signature based on the orthogonality between noise and signal subspaces. It is seen that the blind adaptive multiuser detection and blind spatio-temporal signature estimation can he integrated jointly     

Reuse within a cell-interference rejection or multiuser detection?

We investigate the use of an antenna array at the receiver in frequency-division multiple-access/time-division multiple-access systems to let several users share one communication channel within a cell. A decision-feedback equalizer (DFE) which simultaneously detects all incoming signals is compared to a set of DFEs, each detecting one signal and rejecting the remaining as interference. We also introduce the existence of a zero-forcing solution to the equalization problem as an indicator of near-far resistance of different detector structures. Near-far resistance guarantees good performance if the noise level is low. Simulations show that with an increased number of users in the cell, the incremental performance degradation is small for the multiuser detector. We have also applied the proposed algorithms to experimental measurements from a DCS-1800 antenna array testbed. The results from these confirm that reuse within a cell is indeed possible using either an eight-element array antenna or a two-branch diversity sector antenna. Multiuser detection will, in general, provide better performance than interference rejection, especially when the power levels of the users differ substantially. The difference in performance is of crucial importance when the available training sequences are short     

Decision-feedback equalization of time-dispersive channels withcoded modulation

An extension is presented of the work of V.M. Eyubogin (see ibid., vol.36, p.401-9, Apr. 1988) on decision-feedback equalization (DFE) applied to coded systems with interleaving. The authors study the adaptive implementation of the DFE using recursive-least-squares algorithms (RLS). System performance on time-dispersive channels with nulls as well as on channels with relatively small intersymbol interference is investigated. A reference insertion method is used to improve system performance, and a two-stage processing technique is adopted to use the more reliable decisions from the decoder in equalizer coefficient adaptation. Simulation results show that the RLS-implemented DFE systems with coded modulation can successfully combat severe channel distortion while maintaining the coding gain over corresponding uncoded systems     

Adaptive algorithms for channel equalization with soft decisionfeedback

A new approach based on joint entropy maximization (JEM) is taken and adaptive algorithms are developed for channel equalization with a decision feedback equalizer (DFE). The proposed work generalizes the existing algorithms for DFE with a hard decision device. Previous research has shown that when the hard decisions in a DFE are replaced with soft decisions, the performance of the adaptive algorithms [e.g., minimum mean square error (MMSE)] improves dramatically. The soft decisions can be introduced naturally via the viewpoint taken here. Additionally, constant modulus and other (blind) algorithms for DFE with soft decisions can be derived from this JEM approach     

A new adaptive functional-link neural-network-based DFE forovercoming co-channel interference

A new approach for the decision feedback equalizer (DFE) based on the functional-link neural network is described. The structure is applied to the problem of adaptive equalization in the presence of intersymbol interference (ISI), additive white Gaussian noise, and co-channel interference (CCI). It is shown through simulation results for a severe amplitude distorted co-channel system that the decision feedback functional-link equalizer (DFFLE) provides significantly superior bit-error rate (BER) performance characteristics compared to the conventional DFE, the linear transversal equalizer (LTE), the nonlinear radial basis function (RBF) neural-network-based structures and the feed-forward functional-link equalizer (FFLE)-based structures. The DFFLE is also shown to have a significantly simpler computational requirement relative to the RBF and the FFLE     

Adaptive processing using real weights based on a direct data domain least squares approach

In traditional, adaptive signal processing algorithms one change both the amplitude and phase of the weight vectors associated with an array at each of the antenna elements. The use of complex weights offers greater control over the array response at the expense of system complexity. However, it is easier if one requires only amplitude variation with a fixed phase for all the weight vectors associated with all the antenna elements. Because one uses only real arithmetic operations to find the amplitude of the weights connected to the antenna, the computational complexity is reduced considerably. Hence, this paper addresses the use of real weights in an adaptive system. In this paper we describe a new direct data domain least squares (D/sup 3/LS) method using real weights, which utilizes only a single snapshot of the data for adaptive processing. This technique may be useful for real time implementation of the D/sup 3/LS method on a chip.     

短波单载波空时分组码的频域均衡研究

短波通信受多径衰落、干扰复杂等影响严重。空时分组码(Space Time Block Code,STBC)技术在无需增加频谱资源和天线发射功率的前提下,可以利用多输入多输出(Multiple-Input Multiple-Output,MIMO)信道提供的分集增益提升传输可靠性。分析短波MIMO研究现状,提出短波单载波STBC频域均衡(Frequency-Domain Equalization,FDE)系统架构,针对短波信道引入的码间干扰研究MIMO MMSE-FDE均衡技术,并将单载波STBC频域均衡与时域均衡及短波现有波形进行仿真对比。仿真结果表明,相较于短波现有波形,单载波STBC频域均衡系统的可靠性有较大幅度提升,且性能与STBC时域均衡接近,但计算复杂度远低于STBC时域均衡。     

Blind adaptive multiuser detection for DS/SSMA communications withgeneralized random spreading

A new spreading scheme and an accompanying blind adaptive receiver structure are proposed for direct-sequence spread-spectrum multiple-access communications in a slowly-varying, frequency-selective fading channel. Each user's spreading sequence is given by the Kronecker product of a long-period pseudonoise (PN) sequence, which is accurately modeled by a random sequence, and a short-length deterministic signature code. This spreading scheme bridges the gap between pure PN spreading and pure short-code spreading schemes. It is shown that with this spreading scheme, the channel response to the desired signal component is easily estimated without relying on the spectral decomposition of the signal correlation matrix. With the estimate of the channel response, the receiver suppresses interference based on the maximum signal-to-interference ratio criterion. The blind adaptive receiver requires only coarse timing information and a priori knowledge of the desired user's PN sequence for adaptation. Numerical results show that the adaptive receiver significantly suppresses interference by successfully estimating the channel response and the interference statistics with a low computational complexity. An extension to spatio-temporal processing using an array antenna is also discussed     

空域分解的机载MIMO雷达空时处理方法

相对于传统机载相控阵雷达,应用于机载多输入多输出雷达中的空时自适应处理（MIMO-STAP）技术可以获得杂波抑制和动目标检测能力的大幅提升.但是传统MIMO-STAP所需要的计算量和样本需求量巨大,无法满足实际处理要求.为了解决这一问题,我们提出了一种基于空域多级分解的机载MIMO雷达后多普勒自适应方法.该方法将后多普勒自适应权系数进行分解,使其变为几个短向量的Kronecker乘积,然后利用循环迭代的思想求解自适应权.实验表明该方法具有快速收敛性,在小样本大阵列条件下该方法明显优于传统的后多普勒处理方法.