Adaptive Minimum Mean Square Error Research Articles

Interference Mitigation by Adaptive Analog Spatial Filtering for MIMO Receivers

Exposed to strong cochannel/adjacent-channel interference, digital multiple-input–multiple-output (MIMO) receivers require high-dynamic-range analog-to-digital converters (ADCs). Hybrid beamforming featuring spatial filtering before the ADCs can adaptively mitigate interference in both the analog and digital domains; hence relaxing the required dynamic ranges of the ADCs. This article demonstrates the effectiveness of hybrid beamforming in this mitigation utilizing adaptive minimum mean square error (MMSE) and error vector magnitude (EVM) as an optimization criterion. Extensive EVM measurements are carried out with a conductive setup using a four-element 22-nm FD-SOI CMOS prototype MIMO receiver chip to verify the performance of the adaptive MMSE algorithm. Over-the-air (OTA) measurements with a linear four-element dipole antenna array with half-wavelength spacing in the 2.4-GHz industrial scientific and medical (ISM) band quantify the improvement for real-world scenarios, e.g., having a multipath propagation channel and mutual coupling between the antenna array elements. OTA results show that a rejection of 22.5 and 24.5 dB can be achieved on average in an in-door laboratory environment utilizing vector modulator (VM) constellations with 16 and 64 points, respectively.

Performance improvement of space diversity technique using space time block coding for time varying channels in wireless environment

Performance improvement of space diversity technique using space time block coding for time varying channels in wireless environment

Digital Cancellation of Harmonic and Intermodulation Distortion in Wideband SAW-Less Receivers

This brief presents a digital distortion equalizer that compensates for the effects of both the harmonic mixing and intermodulation products in wideband surface acoustic wave (SAW)-less receivers. A mathematical framework is derived for analyzing signal distortion in the presence of harmonic and out-of-band interferers. This framework models a ${K}$ -path SAW-less ${M}$ -phase receiver, which provides sufficient front-end observations to cancel the distortion products. An adaptive minimum mean-squared error (MMSE) digital equalizer is employed to estimate the desired signal in the presence of distortion products. The MMSE equalizer jointly accounts for distortion products as well as correlated noise of the two paths. A dual-path 4-phase receiver fabricated in 130 nm CMOS process has been used to validate the distortion compensation scheme.

Comparative performance evaluation of MMSE-based speech enhancement techniques through simulation and real-time implementation

In this article, a generic model of minimum mean square error (MMSE) based speech enhancement technique has been presented and implemented on the hardware. Models for different MMSE-based methods were obtained by changing the gain function in the generic model. In all the methods, modified cascaded median-based noise estimation method has been used for noise estimation. Performances of all these MMSE-based methods were compared, among themselves and also with the spectral subtraction method for speech enhancement. The results have been evaluated using objective measures, subjective measure and composite objective measures for different noisy speech files. Results, in terms of objective evaluation parameters, indicated that the adaptive β-order MMSE method yielded better performance than the other methods. In subjective quality test (according to MOS listening test), β-order MMSE and adaptive β-order MMSE method yielded high scores. Real-time implementation has been carried out using TMS320C6416T DSP starter kit and code composer studio software. Estimation of memory consumption and execution time has been done for all the methods.

Tight Upper Bound Performance of Full-Duplex MIMO-BICM-IDD Systems in the Presence of Residual Self-Interference

In this paper, we derive a tight upper bound on the performance of a coded full-duplex multiple-input multiple-output (MIMO)-based bidirectional transceiver. Iterative detection and decoding (IDD) are proposed to suppress the residual self-interference (SI) remaining after applying different stages of SI cancellation. IDD comprises an adaptive minimum mean-squared error filter with log-likelihood ratio demapping, while the soft decoder by using soft-in soft-out decoding utilizes the maximum a posteriori algorithm. Furthermore, bit-interleaved coded modulation is considered in the presence of additive white Gaussian noise over MIMO frequency non-selective Rayleigh fading channels. Simulation results are presented to demonstrate the bit-error rate (BER) performance as a function of the signal-to-noise ratio showing a close match to the SI-free case for the proposed system. Furthermore, we validate our results by deriving a tight upper bound on the performance of the proposed system using rate-1/2 convolutional codes together with $M$ -ary quadrature amplitude modulation, which asymptotically exhibits a close agreement with the simulated BER performance. Moreover, extrinsic information transfer chart analysis is used to investigate the convergence behavior of the proposed IDD receiver and to determine the number of iterations required for this convergence.

A Dual-Path 4-Phase Nonuniform Wideband Receiver With Digital MMSE Harmonic Rejection Equalizer

This paper presents a dual-path nonuniform blocker tolerant wideband receiver that employs digital harmonic rejection to suppress local oscillator (LO) harmonic interferers. The proposed receiver performs harmonic rejection of any LO harmonic including seventh and ninth using only four uniformly spaced clocks each with 25% duty cycle. An adaptive minimum mean-squared error (MMSE) harmonic rejection equalizer is developed that minimizes the desired signal distortion in the mean-squared error sense in the presence of harmonic interferers and the correlated noise between the two paths. The chip prototype is fabricated in 130 nm CMOS process and achieved harmonic rejection ratio (HRR) >75 dB for LO harmonic interferers up to the measured 11th harmonic. The 3.1 dB noise figure (NF) at 1 GHz frequency, 14.5 dBm out-of-band third-order intermodulation intercept point (OBIIP3) at 80 MHz offset from 1 GHz and higher than 10 dB return loss in the frequency range of 100–1450 MHz is measured for the proposed receiver.

A Tight Upper Bound on the Performance of Iterative Detection and Decoding for Coded Full-Duplex SIMO Systems

In this letter, we investigate a coded full-duplex (FD) bidirectional transceiver based on single-input multiple-output (SIMO). Iterative detection and decoding (IDD) are proposed to mitigate the residual self-interference (SI) remaining after applying passive suppression and two stages of SI cancellation (SIC) filters in analog and digital domains. IDD comprises an adaptive minimum mean-squared error (MMSE) filter with log-likelihood ratio (LLR) demapping, while the soft-in soft-out (SISO) decoder utilizes the maximum a posteriori (MAP) algorithm. The proposed system’s performance is evaluated in the presence of additive white Gaussian noise (AWGN) over SIMO Rayleigh fading channels. Simulation results are presented to demonstrate the bit-error rate (BER) performance as a function of the signal-to-noise ratio (SNR), demonstrating a close match to the SI-free case for the proposed system. Furthermore, we validate our results by deriving a tight upper bound on the performance of the proposed system using rate-1/2 convolutional codes together with quadrature phase-shift keying (QPSK) modulation, which asymptotically exhibits a close agreement with the simulated BER performance.

Bidirectional algorithms for interference suppression in multiuser systems

This paper presents adaptive bidirectional minimum mean-square error parameter estimation algorithms for fast-fading channels. The time correlation between successive channel gains is exploited to improve the estimation and tracking capabilities of adaptive algorithms and provide robustness against time-varying channels. Bidirectional normalized least mean-square and conjugate gradient algorithms are devised along with adaptive mixing parameters that adjust to the time-varying channel correlation properties. An analysis of the proposed algorithms is provided along with a discussion of their performance advantages. Simulations for an application to interference suppression in multiuser DS-CDMA systems show the advantages of the proposed algorithms.

CMA Channel Equalization Through An Adaptive MMSE Equalizer Based RLS Algorithm

The adaptive algorithm has been widely used in the digital signal processing like channel estimation, channel equalization, echo cancellation, and so on. One of the most important adaptive algorithms is the RLS algorithm. We present in this paper n multiple objective optimization approach to fast blind channel equalization. By investigating first the performance (mean-square error) of the standard fractionally spaced CMA (constant modulus algorithm) equalizer in the presence of noise, we show that CMA local minima exist near the minimum mean-square error (MMSE) equalizers. Consequently, CMA may converge to a local minimum corresponding to a poorly designed MMSE receiver with considerable large mean-square error. The step size in the RLS algorithm decides both the convergence speed and the residual error level, the highest speed of convergence and residual error level.

Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for Multi-Antenna Systems

In this work, decision feedback (DF) detection algorithms based on multiple processing branches for multi-input multi-output (MIMO) spatial multiplexing systems are proposed. The proposed detector employs multiple cancellation branches with receive filters that are obtained from a common matrix inverse and achieves a performance close to the maximum likelihood detector (MLD). Constrained minimum mean-squared error (MMSE) receive filters designed with constraints on the shape and magnitude of the feedback filters for the multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive implementation of the proposed MB-MMSE-DF detector is developed along with a recursive least squares-type algorithm for estimating the parameters of the receive filters when the channel is time-varying. A soft-output version of the MB-MMSE-DF detector is also proposed as a component of an iterative detection and decoding receiver structure. A computational complexity analysis shows that the MB-MMSE-DF detector does not require a significant additional complexity over the conventional MMSE-DF detector, whereas a diversity analysis discusses the diversity order achieved by the MB-MMSE-DF detector. Simulation results show that the MB-MMSE-DF detector achieves a performance superior to existing suboptimal detectors and close to the MLD, while requiring significantly lower complexity.

Adaptive MMSE Equalizer for Optical Multipath Dispersion in Indoor Visible Light Communication

Multipath dispersion results from optical signals passing through more than one path. In this paper, we investigate a non-directed line of sight (LOS) model using white light emitting diode illumination. Typically in such a link, the optical signals are modeled as a reflection component and a directed LOS component over optical wireless (OW) channels. However, inter-symbol interference (ISI) induced by multipath dispersion critically influences the performance of OW communications. In this paper, we propose the adaptive minimum mean squared error (MMSE) equalizer scheme to suppress the multipath ISI, since this scheme can minimize the mean square error (MSE) between the desired equalizer output and the actual equalizer output. We compared the following two algorithms: Least mean square and recursive least square. Our computer simulations demonstrated that visible light communication using an adaptive MMSE equalizer can alleviate the serious effects of optical multipath dispersion.

A new optimal MUD algorithm based on searching in the local space of sub-optimal MMSE solutions for DS-UWB communication systems

In this paper, we have studied the multiuser detection (MUD) technology applied in multiaccess (MA) direct sequence ultrawideband (DS-UWB) systems. Some typical MUD algorithms were analyzed and a new approximate optimal MUD algorithm based on searching in the local space of suboptimal minimum mean-squared error (MMSE) solution was proposed. In this new algorithm, the suboptimal solution of MMSE is considered as the initial value for the local search, and then a local solution space of this suboptimal solution is constructed by Euclidean distance. Within this space, some likely solutions for the classical optimal MUD algorithm (OMUD) are searched and the optimal one of them is chosen as the solution of this new optimal MUD algorithm. Theoretical analysis and simulation results indicate that, the BER performance and the Near-far Effect resistant ability of this proposed algorithm are much better than those of MMSE and adaptive MMSE detections, which are very close to those of OMUD. Furthermore, its time complexity is much lower than OMUD's. Compared to adaptive MMSE, this algorithm has no difficulty in choosing the suitable parameters for adaptive MMSE. Besides these, we examine the application of this new algorithm to the problem of suppressing the digital narrowband interference (NBI). It is clearly seen that this approximate optimal algorithm has perfect performance under strong NBI circumstance and coincides with the classical OMUD algorithm bound in the same condition.

Convergence Properties of Adaptive Equalizer Algorithms

In this paper, we provide a thorough stability analysis of two well known adaptive algorithms for equalization based on a novel least squares reference model that allows to treat the equalizer problem equivalently as system identification problem. While not surprising the adaptive minimum mean-square error (MMSE) equalizer algorithm behaves <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -stable for a wide range of step-sizes, the even older zero-forcing (ZF) algorithm however behaves very differently. We prove that the ZF algorithm generally does not belong to the class of robust algorithms but can be convergent in the mean square sense. We furthermore provide conditions on the upper step-size bound to guarantee such mean squares convergence. We specifically show how noise variance of added channel noise and the channel impulse response influences this bound. Simulation examples validate our findings.

Blind adaptive MMSE equalization of underwater acoustic channels based on the linear prediction method

The problem of blind adaptive equalization of underwater single-input multiple-output (SIMO) acoustic channels was analyzed by using the linear prediction method. Minimum mean square error (MMSE) blind equalizers with arbitrary delay were described on a basis of channel identification. Two methods for calculating linear MMSE equalizers were proposed. One was based on full channel identification and realized using RLS adaptive algorithms, and the other was based on the zero-delay MMSE equalizer and realized using LMS and RLS adaptive algorithms, respectively. Performance of the three proposed algorithms and comparison with two existing zero-forcing (ZF) equalization algorithms were investigated by simulations utilizing two underwater acoustic channels. The results show that the proposed algorithms are robust enough to channel order mismatch. They have almost the same performance as the corresponding ZF algorithms under a high signal-to-noise (SNR) ratio and better performance under a low SNR.

Adaptive DFE Multiuser Receiver for CDMA Systems using Two-Step LMS-Type Algorithm: An Equalization Approach

This paper presents an adaptive decision feedback equalizer (DFE) based multiuser receiver for code division multiple access (CDMA) systems over smoothly time-varying multipath fading channels using the two-step LMS-type algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh-distributed tap coefficients. The receiver uses an adaptive minimum mean square error (MMSE) multiuser channel estimator based on the reduced Kalman least mean square (RK-LMS) algorithm to predict these tap coefficients (Kohli and Mehra, Wireless Personal Communication 46:507---521, 2008). We propose the design of adaptive MMSE feedforward and feedback filters by using the estimated channel response. Unlike the previously available Kalman filtering algorithm based approach (Chen and Chen, IEEE Transactions on Signal Processing 49:1523---1532, 2001), the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser receiver. The computer simulation results are presented to show the substantial improvement in its bit error rate performance over the conventional LMS algorithm based receiver. It can be inferred that the proposed multiuser receiver proves to be robust against the nonstationarity introduced due to channel variations, and it is also beneficial for the multiuser interference cancellation and data detection in CDMA systems.

Error probability of direct sequence-code division multiple access systems with adaptive antenna minimum mean-square error multiuser receivers in Rayleigh-lognormal fading

In direct sequence-code division multiple access (DS-CDMA) cellular systems spreading codes, fading and positions of the users can be modelled as independent random variables and the corresponding multiuser interference (MUI) experienced by the base station is non-stationary. Here we evaluate in closed form the bit error probability for space-time linear minimum mean square error (MMSE) multiuser receivers for symbol-synchronous DS-CDMA system (bounds are provided for symbol-asynchronous system) by extending the known asymptotic results for random spreading sequences to non-stationary MUI. The analysis is based on the effective interference at the decision variable that is carried out to account for the non-stationary MUI that results from the multiuser beamforming that adapts each spatial filter to the randomness of the angle of arrivals of all the users. Propagation for each user is Rayleigh-lognormal faded channels as it is fairly general to model the imperfect power-control. The numerical validation proves that a simple geometrical model is accurate to evaluate the error probability for any arbitrary system loading.

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.

Convolutionally Coded Adaptive Space-Time MMSE Receiver for W-CDMA Systems in Multipath Channels

In this paper, we consider the use of convolutionally coded adaptive space-time minimum mean-square error (MMSE) receiver for wideband code division multiple access (W-CDMA) systems in multipath channels. In the adaptive space-time MMSE receiver, antenna array processing is combined with MMSE multiuser detection (MUD). Simulations are carried out to evaluate the performance in the directional multi path quasi-static Rayleigh fading channels. Simulation results show that substantial performance improvement may be obtained by using convolutional codes jointly with the adaptive space-time MMSE receiver. Only requirement to implement the receiver is a training sequence and a priori knowledge of the users’ timing for only the strongest path.

Turbo Interference Mitigation in Layered Space-Time MIMO DS-CDMA Uplink with TTCM(Turbo Trellis Coded Modulation)

In this paper we propose the use of a turbo receiver for the uplink of a MIMO CDMA system employing layered space-time transmission. The proposed receiver consists of a low complexity layered space-time multi-user detector using minimum mean squared error (MMSE) filtering with a-priori information and a bank of MAP SISO decoders. Using the soft estimates from a bank of MAP decoders we obtain soft values of the interfering symbols. The SISO multiuser detector subtracts the vector of the interfering symbols from the incoming signal. The resulting vector is then filtered by an adaptive MMSE filter to reduce the residual MAI. This process iterates by exchanging extrinsic informations between the bank of MAP decoders and the SISO multiuser detector. Turbo Trellis Coded Modulation (TTCM) is used as Forward Error Correcting (FEC) code due to its high bandwidth efficiency. Our computer simulations show that the proposed structure outperforms a classical iterative receiver based on parallel interference cancellation (PIC) as well as a non-iterative MMSE receiver. Furthermore, in a multiuser context, the proposed receiver offers an error performance similar to that of single-user case at high SNR.

Space-Time Joint Interference Cancellation Using Fuzzy-Inference-Based Adaptive Filtering Techniques in Frequency-Selective Multipath Channels

An adaptive minimum mean-square error (MMSE) array receiver based on the fuzzy-logic recursive least-squares (RLS) algorithm is developed for asynchronous DS-CDMA interference suppression in the presence of frequency-selective multipath fading. This receiver employs a fuzzy-logic control mechanism to perform the nonlinear mapping of the squared error and squared error variation, denoted by (,), into a forgetting factor. For the real-time applicability, a computationally efficient version of the proposed receiver is derived based on the least-mean-square (LMS) algorithm using the fuzzy-inference-controlled step-size. This receiver is capable of providing both fast convergence/tracking capability as well as small steady-state misadjustment as compared with conventional LMS- and RLS-based MMSE DS-CDMA receivers. Simulations show that the fuzzy-logic LMS and RLS algorithms outperform, respectively, other variable step-size LMS (VSS-LMS) and variable forgetting factor RLS (VFF-RLS) algorithms at least 3 dB and 1.5 dB in bit-error-rate (BER) for multipath fading channels.