RLS and LMS blind adaptive multi-user detection method and comparison in acoustic communication

RLS and LMS blind adaptive multi-user detection algorithm and multi-user detector was proposed to solve the problem of multi-user signal detection problem encountered in underwater acoustic communication networks.In simulation analysis,RLS and the LMS blind adaptive multi-user detector were designed and tested for synchronous and asynchronous multi-user communication process.The results of SIR comparison and MMSE comparison show that,both of the two methods can realize blind adaptive detection when any user change in multi-user communication,during this process,the training communication sequences are not needed.The RLS algorithm has about 5 dB higher in SIR compared with LMS algorithm,and the convergence velocity of RLS algorithm is also higher than LMS algorithm when the communication users change.RLS algorithm has better ability in multi-user detection than that of LMS algorithm,and it has great attraction and guiding significance for solving the problem of multiple access interference(MAI) in multi-user communication.

New blind adaptive approach to multiuser detection in CDMA systems

Due to a number of advantages, blind adaptive multiuser detector has become a research hotspot in recent years. But low convergence rate problem occurs to many blind adaptive algorithms. A new blind adaptive approach to multiuser detection is presented. The simulation results show that by reasonably choosing time varying step size, the proposed detector can not only improve the convergence rate, but also reduce the bit error rate (BER) of the system, and so it can effectively improve the system performance with less computational cost.

A Novel Stochastic Blind Adaptive Multiuser Detector for CDMA Systems

Blind adaptive multiuser detector has become a research hotspot in recent years due to a number of advantages, but many blind adaptive algorithms involve low convergence rate. This paper presents a novel stochastic blind adaptive multiuser detector without requiring training sequences, which needs only two system parameters: the signature sequence of the desired user i, s i and the variance of the additive white Gaussian noise (AWGN),σ 2. Simulation results show that by reasonably choosing time varying step size, the proposed detector can not only improve the convergence rate, but also reduce the limiting NSE (Normalized Squared Error) values, so it can effectively increase the performance of the system.

AN IMPROVED SUBSPACE TRACKING ALGORITHM FOR BLIND ADAPTIVE MULTIUSER DETECTION

As the Projection Approximation Subspace Tracking with deflation(PASTd) algorithm is sensitive to impulsive noise, an improved subspace tracking algorithm is proposed and applied to blind adaptive multi-user detection. Simulation results show that the improved PASTd algorithm not only remains the properties of the conventional PASTdalgorithm, but also has good Bit Error Rate(BER) performance in impulsive noise environment, thus it can effectively improve the system performance.

HYBRID INTERFERENCE CANCELLATION SCHEME FOR BLIND MULTIUSER DETECTION IN MULTIPATH FADING CHANNELS

This paper introduces and analyzes a detection scheme for adaptive suppression of Multiuser Access Interference (MAI) and MultiPath Distortion (MPD) for mobile station of DS/CDMA system. The proposed detection scheme may amount to a RAKE receiver structure,wherein each branch is considered as a linear multiuser filter designed under a Linear Constrained Minimum Variance (LCMV) optimization strategy to suppress MAI, followed by a proper combining rule to suppress MPD. The adaptive blind multiuser detecting and optimum combining of the proposed receiver are realized, based on the Least-Mean-Square (LMS) algorithm and an adaptive vector tracking algorithm respectively. Finally, the feasibility of the above two algorithms is proved by the numerical results provided by computer simulation.

Non-Negative Matrix Factorization Based UKF Algorithm for Constant Modulus Signals in Adaptive Beamforming

Blind adaptive beamforming is getting appreciated for its various applications in contemporary communication systems where sources are statistically dependent or independent that are allowed to formulate new algorithms. Qualitative performance and time complexity are the main issues. In this paper, we propose a technique for constant modulus signals applying basic non-negative matrix factorization (BNMF) in blind adaptive beamforming environment. We compared the existing Unscented Kalman Filter based Constant Modulus Algorithm (UKF-CMA) with proposed NMF-UKF-CMA algorithm. We see there is a better improvement of sensor array gain, signal to interference plus noise ratio (SINR) and mean squared deviation (MSD) as the noise variance and the array size increase with reduced computational complexity with the UKF-CMA.

Inspection of the Output of a Convolution and Deconvolution Process from the Leading Digit Point of View—Benford’s Law

In the communication field, during transmission, a source signal undergoes a convolutive distortion between its symbols and the channel impulse response. This distortion is referred to as Intersymbol Interference (ISI) and can be reduced significantly by applying a blind adaptive deconvolution process (blind adaptive equalizer) on the distorted received symbols. But, since the entire blind deconvolution process is carried out with no training symbols and the channel’s coefficients are obviously unknown to the receiver, no actual indication can be given (via the mean square error (MSE) or ISI expression) during the deconvolution process whether the blind adaptive equalizer succeeded to remove the heavy ISI from the transmitted symbols or not. Up to now, the output of a convolution and deconvolution process was mainly investigated from the ISI point of view. In this paper, the output of a convolution and deconvolution process is inspected from the leading digit point of view. Simulation results indicate that for the 4PAM (Pulse Amplitude Modulation) and 16QAM (Quadrature Amplitude Modulation) input case, the number “1” is the leading digit at the output of a convolution and deconvolution process respectively as long as heavy ISI exists. However, this leading digit does not follow exactly Benford’s Law but follows approximately the leading digit (digit 1) of a Gaussian process for independent identically distributed input symbols and a channel with many coefficients.

Kurtosis-Based Blind Multiuser Detection in Multipath CDMA Channels

In this paper, we consider a kurtosis-based optimization criterion and then present a blind adaptive decorrelating detector in the multipath CDMA channels. We show that the solution to the optimization problem satisfies the zero-forcing condition, which is also the solution achieved by the decorrelating detector. By use of gradient-descent method, an adaptive algorithm to solve the optimization problem is given. Finally, simulation examples are given to demonstrate the performance of the presented detectors.