Modified Minimum Mean Square Error Research Articles

Learning-Based Sparse Recovery for Joint Activity Detection and Channel Estimation in Massive Random Access Systems

We consider the problem of joint activity detection and channel estimation in massive random access. When the receiver has multiple antennas, this is a joint sparse recovery problem with multiple measurement vectors (MMV). For the general setting where the channels could be correlated across antennas, we first develop a modified minimum mean squared error (MMSE) shrinkage function to be used in the Trainable Iterative Soft Thresholding Algorithm (TISTA). Then, we learn this MMSE shrinkage function using a model-based neural network. In the simulation results, the proposed learning-based method, L-MMSE-MMV-TISTA, offers a 30-40% reduction in preamble length requirement compared to TISTA. We also compare L-MMSE-MMV-TISTA with the state-of-the-art MMV sparse Bayesian learning (M-SBL) method. While M-SBL can provide better performance at the cost of higher complexity in highly measurement-constrained settings, LMMSE-MMV-TISTA provides a significant complexity advantage when only a slightly larger number of measurements are available.

An Enhanced Precoder for Multi User Multiple-Input Multiple-Output Downlink Systems

Recently, as the demand for data rate of users has increased, wireless communication systems have aimed to offer high throughput. For this reason, various techniques which guarantee high performance have been invented, such as massive multiple-input multiple-output (MIMO). However, the implementation of huge base station (BS) antenna array and decrease of reliability as the number of users increases are chief obstacles. In order to mitigate these problems, this paper proposes an adaptive precoder which provides high throughput and bit error rate (BER) performances to achieve the desired data rate in multi user (MU) MIMO downlink systems which have a practical BS antenna array (up to 16). The proposed scheme is optimized with a modified minimum mean square error (MMSE) criterion in order to improve BER gain and reduce data streams in order to obtain diversity gain at low signal to noise ratio (SNR). It is shown that the BER and throughput performances of the proposed scheme are improved.

Speckle noise reduction and motion artifact correction based on modified statistical parameters estimation in OCT images

Reducing coherent noise is particularly important in interferometry-based applications, especially optical coherence tomography where more information about images can be extracted by statistical denoising and jitter refinement methods. In this paper, we not only investigate two types of medical image quality degradation factors including speckle noise and motion artifacts, but also describe the relation between them. We applied the concept of using modified approach based on statistical methods for estimation the multiplicative speckle noise parameters and utilizing the modified Minimum Mean-Squared Error noise-free estimation. After the noise reduction, the method reconstructs images based on estimated values calculated from particles jitter and displacements. This algorithm helps us to correct the location of layers to increase the quality of consecutive imaging using multiple-image input filters. Simulation results demonstrate that this method is capable of denoising when compared to the others in terms of signal-to-noise, mean squared error, and edge preservation (η) measures, and has the best results of motion artifact correction error in comparison to the classic methods.

Throughput Enhancement in OFDM System using Low Overhead Pilot Insertion Scheme over Slow Fading Rayleigh Channel

Orthogonal Frequency Division Multiplexing (OFDM) is a widespread adopted technique for wireless and wired communication systems because of its inherent feature of the spectral efficiency and robustness to channel impairments. The throughput deterioration of the OFDM system due to pilots can be reduced by minimizing the density of pilots. A Modified Minimum Mean Square Error (M-MMSE) estimator with low computational complexity based on Low overhead Pilot Insertion (LPI) scheme is also proposed. The pilot overhead in the LPI scheme is reduced compared to blocktype channel estimation. The comparative analysis of the MMMSE estimator for the LPI scheme with MMSE estimator for block-type pilot arrangement shows significant performance improvement of the proposed channel estimation algorithm.

Modified MMSE Estimator based on Non-Linearly Spaced Pilots for OFDM Systems

This paper proposes a Modified Minimum Mean Square Error (M-MMSE) estimator for an Orthogonal Frequency Division Multiplexing (OFDM) System over fast fading Rayleigh channel. The proposed M-MMSE estimator considered the effects of the efficient placement of pilots based on the channel energy distribution. The pilot symbols were placed in a non-linear manner according to the density of the channel energy. Comparative analysis of the MMSE estimator for a comb-type pilot arrangement and M-MMSE estimator for the proposed pilot insertion scheme revealed significant performance improvement of the M-MMSE estimator over the MMSE estimator.

A Low Complexity MMSE for OFDM Systems over Frequency-Selective Fading Channels

Channel estimation is one of the key technologies in Orthogonal Frequency Division Multiplexing (OFDM) systems, which has received more and more consideration. A modified Minimum Mean Square Error (MMSE) is proposed and simulated by MATLAB over a frequency-selective fading channel. Comparing with the conventional MMSE, this algorithm has the advantage of low complexity. Meanwhile, it shows little attenuation of Mean Square Error (MSE) and Bit Error Rate (BER) performances according to the final simulation results, which is promising for practical applications.

A Time-Varying Modified MMSE Detector for Multirate CDMA Signals in Fast Rayleigh Fading Channels

In this paper, we propose a time-varying modified minimum mean-squared error (MMSE) detector for the detection of higher data rate signals in a multirate asynchronous code-division multiple-access (CDMA) system which is signaled in a fast Rayleigh fading channel. The interference viewed by a higher data rate symbol will be periodic due to the presence of a lower data rate symbol which spans multiple higher data rate symbols. The detection is carried out on the basis of a modified MMSE criterion which incorporates differential detection and the ratio of channel coefficients in two consecutive observation intervals inherently compensating the fast variation of the channel due to fading. The numerical results obtained by the MMSE detector with time-varying detection show around 3 dB (M=2) and 6 dB (M=4) performance improvement at a BER of 10−3 in the AWGN channel, while introducing more computational complexity than the MMSE detector without time-varying detection. At a higher Eb/N0, the proposed scheme can achieve a BER of approximately 10−3 in the presence of fast channel variation which is an improvement over other schemes.

Regularized Channel Diagonalization for Multiuser MIMO Downlink Using a Modified MMSE Criterion

We propose a regularized channel diagonalization method for a joint transmit-receive linear optimization in the downlink of a multiuser multiple-input multiple-output (MIMO) communication system. This method is based on the use of a modified minimum mean-square error (MMSE) criterion, which employs a weighted information symbol vector for the target and signal scaling. The weights for the target are the equivalent channel gain resulting from a zero-forcing (ZF)-based MIMO channel diagonalization. A joint iterative algorithm for minimizing the mean-square error (MSE) under a total transmit power constraint is derived, and its convergence is proved. The signal-to-interference-plus-noise ratio (SINR) is analyzed and the sum rates evaluated in a computer simulation. The results demonstrate that the proposed method outperforms the existing ZF- and MMSE-based methods

A Baud-Rate Timing Recovery Scheme With a Dual-Function Analog Filter

This brief presents a baud-rate timing recovery scheme that is aided by signals generated from a dual-function analog filter. The analog filter functions as a simultaneous low-pass and bandpass filter to generate the data and its slope, respectively. Peaking is introduced in the low-pass data path to equalize a lossy channel. The timing recovery loop utilizes the equalized data and slope signals obtained from the dual-function analog filter to recover a clock based on a modified minimum mean squared error (MMSE) criterion. Unlike previously published baud-rate techniques for multigigabit per second nonreturn-to-zero data, this technique can lock to either random or alternating data patterns, even from a closed eye. As a proof of concept, a prototype dual-function analog filter was fabricated in a 0.18-mum CMOS process and used to recover a 2-GHz clock from a 2-Gb/s 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">31</sup> -1 random data sequence based on the modified MMSE criterion

MMSE decision-feedback detectors for DS-CDMA in fast-fading channels

A multiuser decision-feedback detector (DFD) for direct-sequence code-division multiple-access (DS-CDMA) is proposed for fast-fading channels. The proposed modified minimum mean-squared error (MMSE)-DFD (termed precombining MMSE-DFD) is shown to be independent of the instantaneous channel coefficients. Hence, it can be adaptively implemented unlike the standard MMSE-DFD (termed postcombining MMSE-DFD), where it is known to break down in fast-fading channels due to the severe tracking problems. A two-stage MMSE-DFD is also derived which consists of two cascaded MMSE-DFDs, each performing parallel or successive interference cancellation prior to multipath combining. The performance of the various MMSE-DFDs is investigated and compared to the linear MMSE detector (i.e. no feedback) over different fading-channel models, using the Gaussian approximation. The numerical results show that, in all cases, the postcombining receivers perform significantly better than the corresponding precombining receivers. Finally, a simple adaptive implementation for the two-stage detector is derived based on the normalised least-mean-square (NLMS) algorithm. The performance of this two-stage receiver is examined using both the Gaussian approximation and Monte Carlo simulations.

Performance Improvement of MAI Cancellation in Fading DS/CDMA Channels

In this paper, we propose a single-user strategy for demodulating asynchronous direct-sequence code-division multiple access (DS/CDMA) signals for improving the performance of the adaptive receiver in fast fading channels. Since the adaptive receiver depends on the channel coefficient of all users, it cannot be implemented adaptively in fading channels due to severe tracking problem. A proposed adaptive receiver based on the modified minimum mean-squared-error (MMSE) criterion is used for solving this problem. By simulation, it is verified that our proposal is a promising method to solve the problem, and the results show that the proposed adaptive receiver has substantially larger capacity than the conventional adaptive receiver in fast fading channels.

A DS-CDMA tracking mode receiver with joint channel/delay estimation and MMSE detection

A tracking mode receiver for asynchronous direct-sequence CDMA is presented based on the extended Kalman filter (EKF). The EKF jointly estimates the delays and multipath coefficients of the received CDMA waveform, and provides a modified minimum mean-square error (MMSE) estimate of the user data (MMSE-EKF). In order to obtain a practical algorithm, each user signal is tracked individually, with the remaining users modeled as colored Gaussian noise. However, the EKFs are coupled through the multiple access interference (MAI) covariance estimates. In order to obtain meaningful performance measures, approximate worst-case undesired user delays that minimize the desired user SNR and delay estimation Cramer-Rao bound are obtained. It is shown that such worst-case delays can be efficiently computed using the alternating maximization (A-M) algorithm. The resulting bit error rate (BER) performance of the MMSE-EKF tracking receiver is evaluated through a combination of simulation and analysis. The mean-time to lose lock (MTTLL) for a genie-aided EKF delay estimator is also obtained using the A-M computed delays.