Performance of Adaptive Modulation Scheme for Adaptive Minimum Symbol Error Rate Beamforming Receiver

This paper considers adaptive beamforming receiver that support multiple users, each having one transmit antenna. In certain circumstances, symbol error rate (SER) performance of the beamforming receiver degrades severely. In order to minimize the SER, minimum symbol error rate (MSER) beamforming receiver is utilized. Then, we propose an adaptive modulation scheme for the receiver to maintain the average SER below the target SER while maximizing the average throughput. The scheme uses the information on the direction of arrival and the average signal-to-noise ratio to decide the appropriate modulation mode. For comparison, the proposed scheme is also applied to minimum mean square error (MMSE) beamforming receiver system. Simulations were carried out in the presence of single and two interferers. Simulation results show that the performance of the proposed algorithm employing MSER beamforming is superior to its MMSE counterpart, with the largest advantage of 0.21 in the outage probability.     

Adaptive minimum symbol-error-rate decision feedback equalization for multilevel pulse-amplitude modulation

The design of decision feedback equalizers (DFEs) is typically based on the minimum mean square error (MMSE) principle as this leads to effective adaptive implementation in the form of the least mean square algorithm. It is well-known, however, that in certain situations, the MMSE solution can be distinctly inferior to the optimal minimum symbol error rate (MSER) solution. We consider the MSER design for multilevel pulse-amplitude modulation. Block-data adaptive implementation of the theoretical MSER DFE solution is developed based on the Parzen window estimate of a probability density function. Furthermore, a sample-by-sample adaptive MSER algorithm, called the least symbol error rate (LSER), is derived for adaptive equalization applications. The proposed LSER algorithm has a complexity that increases linearly with the equalizer length. Computer simulation is employed to evaluate the proposed alternative MSER design for equalization application with multilevel signaling schemes.     

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     

Finite dictionary techniques for MSER equalization in RKHS

Adaptive channel equalization is a signal processing technique to mitigate inter-symbol interference in a time dispersive channel. For adaptive equalization, minimum mean square error (MMSE) criterion-based reproducing kernel Hilbert spaces (RKHS) approaches such as the kernel least mean squares (KLMS) algorithm and its variants have been suggested in the literature for nonlinear channels. Another optimality criterion, based on minimum bit/symbol error rate (MBER/MSER), is a better choice for adapting an equalizer as compared to MMSE criterion. A kernel-based minimum symbol error rate (KMSER) equalization algorithm combines minimum symbol error rate (MSER)-based approaches with RKHS techniques. However, most algorithms in RKHS such as KMSER/KLMS require infinite storage requirement and hence cannot be practically implemented. To curtail the infinite memory requirement, and make adaptive algorithm suitable for implementation with finite memory and processing power, we propose quantized KMSER (QKMSER) and fixed-budget quantized KMSER (FBQKMSER)-based equalizers in this paper. In this paper, we derive the dynamical equation for MSE evolution of the QKMSER and FBQKMSER and find their performance to be asymptotically close to the MSE behavior of the KMSER. Also, it is found via simulations that the tracking performance of FBQKMSER is better than all the compared algorithms in this paper which is particularly useful for non-stationary channels.     

MBER Space-Time Decision Feedback Equalization Assisted Multiuser Detection for Multiple Antenna Aided SDMA Systems

This paper proposes a space-time decision feedback equalization (ST-DFE) assisted multiuser detection (MUD) scheme for multiple receiver antenna aided space division multiple access systems. A minimum bit error rate (MBER) design is invoked for the MUD, which is shown to be capable of improving the achievable bit error rate performance and enhancing the attainable system capacity over that of the standard minimum mean square error (MMSE) design. An adaptive implementation of the MBER ST-DFE assisted MUD is proposed using a stochastic gradient-based least bit error rate algorithm, which is demonstrated to consistently outperform the classical least mean square (LMS) algorithm, while achieving a lower computational complexity than the LMS algorithm for the binary signalling scheme. Our simulation results demonstrate that the MBER ST-DFE assisted MUD is more robust to channel estimation errors as well as to potential error propagation imposed by decision feedback errors, compared to the MMSE ST-DFE assisted MUD.     

Adaptive minimum bit-error rate beamforming

An adaptive beamforming technique is proposed based on directly minimizing the bit-error rate (BER). It is demonstrated that this minimum BER (MBER) approach utilizes the antenna array elements more intelligently than the standard minimum mean square error (MMSE) approach. Consequently, MBER beamforming is capable of providing significant performance gains in terms of a reduced BER over MMSE beamforming. A block-data adaptive implementation of the MBER beamforming solution is developed based on the Parzen window estimate of probability density function. Furthermore, a sample-by-sample adaptive implementation is considered, and a stochastic gradient algorithm, referred to as the least bit error rate, is derived. The proposed adaptive MBER beamforming technique provides an extension to the existing work for adaptive MBER equalization and multiuser detection.     

Noncoherent MMSE interference suppression for DS-CDMA

A novel robust noncoherent receiver for minimum mean-squared error (MMSE) interference suppression for direct-sequence code-division multiple access (DS-CDMA) is proposed. The receiver consists of a linear MMSE filter and a decision-feedback differential detector (DF-DD). The performance of the proposed scheme is investigated analytically and by computer simulations. It is shown that the loss compared to coherent MMSE interference suppression is limited and can be made arbitrarily small by increasing the observation window used for calculation of the reference symbol of the DF-DD. Hence, the regarded noncoherent receiver is near-far resistant. For adjustment of the MMSE filter coefficients three noncoherent adaptive algorithms are proposed. In contrast to coherent adaptive algorithms, these noncoherent algorithms have the important advantage that they also converge if the channel phase is time-variant     

Multiuser Detection in SDMA–OFDM Wireless Communication System Using Complex Multilayer Perceptron Neural Network

The space division multiple access–orthogonal frequency division multiplexing (SDMA–OFDM) wireless system has become very popular owing high spectral efficiency and high load capability. The optimal maximum likelihood multiuser detection (MUD) technique suffers from high computational complexity. On the other hand the linear minimum mean square error (MMSE) MUD techniques yields poor performance and also fails to detect users in overload scenario, where the number of users are more than that of number of receiving antennas. By contrast, the differential evolution algorithm (DEA) aided minimum symbol error rate (MSER) MUD can sustain in overload scenario as it can directly minimizes probability of error rather than mean square error. However, all these classical techniques are still complex as these do channel estimation and multiuser detection sequentially. In this paper, complex multi layer perceptron (CMLP) neural network model is suggested for MUD in SDMA–OFDM system as it do both channel approximation and MUD simultaneously. Simulation results prove that the CMLP aided MUD performs better than the MMSE and MSER techniques in terms of enhanced bit error rate performance with low computational complexity.     

Space-Time Adaptive MMSE Multiuser Decision Feedback Detectors With Multiple-Feedback Interference Cancellation for CDMA Systems

In this paper, we propose a novel space-time minimum mean square error (MMSE) decision feedback (DF) detection scheme for direct-sequence code-division multiple access (DS-CDMA) systems with multiple receive antennas, which employs multiple-parallel-feedback (MPF) branches for interference cancellation. The proposed space-time receiver is then further combined with cascaded DF stages to mitigate the deleterious effects of error propagation for uncoded schemes. To adjust the parameters of the receiver, we also present modified adaptive stochastic gradient (SG) and recursive least squares (RLS) algorithms that automatically switch to the best-available interference cancellation feedback branch and jointly estimate the feedforward and feedback filters. The performance of the system with beamforming and diversity configurations is also considered. Simulation results for an uplink scenario with uncoded systems show that the proposed space-time MPF-DF detector outperforms existing schemes such as linear, parallel DF (P-DF), and successive DF (S-DF) receivers in terms of bit error rate (BER) and achieves a substantial capacity increase in terms of the number of users, compared with the existing schemes. We also derive the expressions for MMSE achieved by the analyzed DF structures, including the novel scheme, with imperfect and perfect feedback and expressions of signal-to-interference-plus-noise ratio (SINR) for the beamforming and diversity configurations with linear receivers.     

Minimum symbol error rate multiuser detection using an effective invasive weed optimization for MIMO/SDMA–OFDM system

Space division multiple access–orthogonal frequency division multiplexing system has become a potential wireless communication system by offering high spectral efficiency, performance and capacity. This article deals with minimum symbol error rate (MSER)‐based multiuser detection (MUD) technique for the space division multiple access–orthogonal frequency division multiplexing system using an efficient invasive weed optimization (IWO) algorithm. The IWO algorithm is used for finding optimal weights such that the probability of error is directly minimized rather than minimizing the mean square error. Because of this, the MSER MUD is able to detect users even in overload scenario, where the number of users is more than the number of receiving antennas, unlike several classical detection techniques. The IWO is inspired from the nature of invasive colonization of weeds and relatively simple compared with other optimization techniques. The bit error rate performance of the proposed IWO‐aided MSER MUD is found to be better than minimum means square error and differential evolution algorithm‐aided MSER MUDs. Simulation results show that the proposed IWO MSER achieves faster convergence and lower complexity compared with the differential evolution MSER MUD. Copyright © 2013 John Wiley & Sons, Ltd.     

Adaptive MMSE receiver with beamforming for DS/CDMA systems

The minimum mean-squared error (MMSE) receiver is a linear filter which can suppress multiple access interference (MAI) effectively in direct-sequence code-division multiple-access (CDMA) communications. An antenna array is also an efficient scheme for suppressing MAI and improving the system performance. In this letter, we consider an adaptive MMSE receiver in conjunction with beamforming in CDMA systems employing an antenna array. The proposed structure is featured as a low complexity receiver, which adapts the MMSE filter coefficients and the beamforming weights simultaneously. However, it does require the channel state information and the direction of arrival (DOA) of the desired user signal. As a result, we propose two adaptation methods to perform joint channel estimation and signal detection without any training sequence. It is demonstrated that the two proposed methods achieve similar bit-error-rate performance. More importantly, their performance degradation compared with the case with perfect channel information is small.     

Channel estimation and interference suppression for uplink CDMA mobile communication systems

Wireless communications for mobile telephone and data transmission is currently undergoing very rapid development. Code division multiple‐access (CDMA) implemented with direct sequence spread spectrum signaling is among the most promising multiplexing technologies for cellular telecommunications services. In this paper, jointly period inserted pilot symbols assisted recursive (PIPSAR) channel estimation and interference suppression techniques are proposed for uplink CDMA mobile communication systems. The uplink CDMA mobile communication system model is described in the form of space‐time domain through antenna array and multipath expression. Interference suppression is achieved by using adaptive minimum mean squared error (MMSE) digital filters that span several successive received chip oversampling vectors of a symbol interval. PIPSAR techniques are used to estimate channel parameters. The correlation between the successive periods is considered to further improve the performance of the proposed scheme. Analysis and simulations are used to evaluate the performance of the proposed scheme. Copyright © 2004 John Wiley & Sons, Ltd.     

Analysis of an adaptive SIC for near-far resistant DS-CDMA

A new multiuser detection scheme is proposed which employs adaptive minimum mean square error (MMSE) detection in combination with successive interference cancellation (SIC). Through theoretical analysis and numerical examples, it is shown that the proposed detector provides superior performance to existing ones in terms of asymptotic multiuser efficiency (AME) and bit error rate (BER)     

Signal Processing by Generalized Receiver in?DS-CDMA Wireless Communication Systems with?Frequency-Selective Channels

The generalized receiver (GR) based on a generalized approach to signal processing (GASP) in noise is investigated in a direct-sequence code-division multiple access (DS-CDMA) wireless communication system with frequency-selective channels. We consider four avenues: linear equalization with finite impulse response (FIR) beamforming filters; channel estimation and spatially correlation; optimal combining; and partial cancellation. We investigate the GR with simple linear equalization and FIR beamforming filters. Numerical results and simulation show that the GR with FIR beamforming filters surpasses in performance the optimum infinite impulse response beamforming filters with conventional receivers, and can closely approach the performance of GR with infinite impulse response beamforming filters. Channel estimation errors are taken into consideration so that DS-CDMA wireless communication system performance will not be degraded under practical channel estimation. GR takes an estimation error of a maximum likelihood (ML) multiple-input multiple-output (MIMO) channel estimation and GR spatially correlation into account in computation of minimum mean square error (MMSE) and log-likelihood ratio (LLR) of each coded bit. The symbol error rate (SER) performance of DS-CDMA employing GR with a quadrature sub-branch hybrid selection/maximal-ratio combining (HS/MRC) scheme for 1-D modulations in Rayleigh fading is obtained and compared with that of conventional HS/MRC receivers. Procedure of selecting a partial cancelation factor (PCF) for the first stage of a hard-decision partial parallel interference cancellation (PPIC) of the GR employed in DS-CDMA wireless communication system is proposed. A range of optimal PCFs is derived based on the Price’s theorem. Computer simulation results show superiority in bit error rate (BER) performance that is very close to that potentially achieved and surpasses the BER performance of the real PCF for DS-CDMA systems discussed in literature.     

Adaptive reduced-rank LCMV beamforming algorithms based on joint iterative optimization of filters: Design and analysis

This paper presents reduced-rank linearly constrained minimum variance (LCMV) beamforming algorithms based on joint iterative optimization of filters. The proposed reduced-rank scheme is based on a constrained joint iterative optimization of filters according to the minimum variance criterion. The proposed optimization procedure adjusts the parameters of a projection matrix and an adaptive reduced-rank filter that operates at the output of the bank of filters. We describe LCMV expressions for the design of the projection matrix and the reduced-rank filter. We then describe stochastic gradient and develop recursive least-squares adaptive algorithms for their efficient implementation along with automatic rank selection techniques. An analysis of the stability and the convergence properties of the proposed algorithms is presented and semi-analytical expressions are derived for predicting their mean squared error (MSE) performance. Simulations for a beamforming application show that the proposed scheme and algorithms outperform in convergence and tracking the existing full-rank and reduced-rank algorithms while requiring comparable complexity.     

Analog antenna combining in transmit correlated channels: Transceiver design and performance evaluation

In this paper we study space-time coding schemes for a novel OFDM-based MIMO system which performs adaptive signal combining in radio-frequency (RF). Assuming perfect channel knowledge at the receiver and statistical channel state information at the transmitter, we consider the problem of selecting the transmit and receive RF weights (beamformers), as well as the time and frequency linear precoders, under the assumption of Rayleigh channels. The transmission scheme is based on orthogonal beam division multiplexing (OBDM) and minimum mean-square error (MMSE) receive beamforming, i.e., the data is transmitted by means of several transmit beamformers matched to the spatial correlation matrix, whereas the receive beamformers are selected to minimize the MSE of the linear MMSE receiver. Finally, the performance of the proposed scheme is evaluated by means of Monte Carlo simulations.     

Error Rate Analysis of Uplink MC-CDMA Systems under Imperfect Channel Estimation

Theoretical error rate performance of wireless communication systems are usually determined assuming that the perfect channel state information (CSI) is available at the receiver. However, in actual practice, the channel gains at the receiver are obtained via using some channel estimation (CE) techniques. Due to inherent presence of noise, the CE is not perfect resulting in the performance degradation. In this paper, we evaluate the error rate performance of an uplink multicarrier code-division multiple-access (MC-CDMA) system, considering different modulation techniques, where CE is performed using pilot symbol assisted (PSA) minimum mean-square error (MMSE) CE technique. The symbol error rate (SER) analysis of an uplink MC-CDMA system using multiuser detection techniques, such as MMSE and zero forcing (ZF), is presented under imperfect CE. Simulated results for SER are also shown to confirm the accuracy of the analytically derived results.     

稀疏多径信道的T/2间隔CFE均衡器研究

完全反馈均衡器(Complete Feedback Equalizer, CFE)是判决反馈均衡器(DFE)的改进。该文提出了一种T/2分数间隔稀疏CFE(T/2 Sparse CFE, T/2-SCFE)结构,以避免接收机对于符号定时误差的敏感性,并有效利用长时延扩展多径信道的稀疏性来降低均衡器的复杂度。理论分析与基于实测信道的计算机仿真表明, T/2-SCFE均衡器对符号定时误差保持了稳健性,总体性能优于符号间隔CFE及分数间隔DFE。     

基于后验概率估计的软输出MMSE MIMO排序串行干扰抵消检测算法

该文研究了信道编码无线MIMO通信系统中的软输出MMSE排序串行干扰抵消检测算法。利用MMSE滤波器输出的高斯近似表示,提出了基于后验概率估计的判决误差传播抑制算法,以提高检测算法输出的编码比特对数似然比的可靠性;利用检测器的矩阵结构和矩阵求逆引理,进一步提出了降低复杂度的实现方法。仿真结果表明:提出的检测算法优于现有算法,当BER为10-4,在所给的仿真条件下有1～3dB的性能增益。     

An asynchronous multiuser CDMA detector based on the Kalman filter

We introduce a multiuser receiver based on the Kalman filter, which can be used for joint symbol detection and channel estimation. The proposed algorithm has the advantage of working even when the spreading codes used have a period larger than one symbol interval (“long codes”), unlike adaptive equalizer-type detectors. Simulation results which demonstrate the performance advantage of the proposed receiver over the conventional detector, the minimum mean squared error (MMSE) detector and a recursive least squares (RLS) multiuser detector are presented. A thorough comparison of the MMSE detector and the proposed detector is attempted because the Kalman filter also solves the MMSE parameter estimation problem, and it is concluded that, because the state space model assumed by the Kalman filter fits the code division multiple access (CDMA) system exactly, a multiuser detector based on the Kalman filter must necessarily perform better than a nonrecursive, finite-length MMSE detector. The computational complexity of the detector and its use in channel estimation are also studied