Multiuser Detection Problem Research Articles

Synthesis of poly-Gaussian quasioptimal algorithms for multiuser detection problem and non-Gaussian interference

A quasi-optimal multiuser receiver, which realizes an poly-Gaussian algorithm for complex signal processing in non-Gaussian channels, is proposed. This receiver provides the better performance of CDMA uplink at polynomial level of computational complexity.

Algoritimos Heurísticos Aplicados à detecção Multiusuário DS/CDMA DOI: 10.14209/jcis.2005.11

The characteristics of nine heuristic algorithms based on genetic evolution theory and local search, applied to a DS/CDMA (Direct Sequence/Code Division Multiple Access) multi-user detection problem in Flat Rayleigh fading channel are introduced. The algorithms comparisons through the performance versus computational complexity tradeoff are carried out. The computational complexity is determined in terms of the number of operations to reach the Maximum Likelihood (ML) performance. The effects on the performance of the errors in the estimates of the channel coefficients are also considered, as well as the performance degradation due to overload. There are three contributions in this work: a) a compared analysis of the evolutionary, evolutionary with cloning and local search algorithms applied to MuD detector in Flat Rayleigh channels; b) a systematic comparison of these algorithms in terms of the same simulation scenario and performance analysis base; c) a more fair and precise complexity analysis for the MuD detector in terms of the number of the computational operations.

Multiuser Detection in Massive Spatial Modulation MIMO With Low-Resolution ADCs

In this paper, we research the multiuser detection (MUD) in a new Spatial Modulation Multiple-Input-Multiple-Output (SM-MIMO) system, whose Base Station (BS) is equipped with massive Radio-Frequency (RF) chains with low-resolution Analog-to-Digital Convertors (ADCs), and the User Equipments (UEs) have multiple Transmit Antennas (TAs) but single RF chain. In the uplink, UEs transmit their data by the Cyclic-Prefix Single-Carrier (CP-SC) SM technique. The key is how to design practical MU detectors to handle the severely quantized measurements and antenna correlations. Coherent detection is focused, so a Least-Square (LS) channel estimator is designed to acquire the the channel side information (CSI) at the Receiver (CSIR). Then, we firstly solve the MUD problem by the Sum-Product-Algorithm (SPA) on a clustered factor graph (FG) whose variable nodes correspond to the transmitted vectors from the UEs. Next, based on the Central Limit Theorem (CLT) and Taylor expansions, the SPA detector (SPAD) is simplified as a new low-complexity Message Passing De-Quantization Detector (MPDQD), which exploits both the structured sparsity and prior probability distribution of the transmitted signal. By utilizing the clustering technique, damping mechanism, and Analog Spatial Filtering (ASF), the robustness of MPDQD is improved significantly. Simulation results show that MPDQD outperforms the linear detectors, works steadily under strong channel correlations, and even performs similarly as its counterpart in the un-quantized SM-MIMO.

Multi-User Detection for Radar and Communication Multifunction System

A multifunctional system that performs synthetic aperture radar (SAR) and communication tasks is presented. The system depends on orthogonal frequency division multiplexing (OFDM) waveform shaping and multiple input multiple output (MIMO) configuration to achieve enhancement in the spectral efficiency of communication operation and provide interference rejection in SAR imaging. The SAR interval idle time is utilized to enhance the communication signal through diversity. Adaptive system features are introduced to achieve multi-user detection and improve the communication reliability, by means of space division multiple access (SDMA) and space–time block coding (STBC). Investigations of linear and nonlinear multi-user detection (MUD) techniques are provided. Moreover, a genetic algorithm-based system is developed to optimize the MUD problem and to provide near-optimal performance even for overloaded scenarios. A gain of more than 4 dB is achieved at bit error rate of 10-2.

Performance Analysis of Multistage Interference Cancellation in THUWB Systems Using Adaptive Differential Evolution Algorithm with Novel Mutation and Crossover Strategies

We study the application of differential evolution optimization algorithm to the problem of multiuser detection (MUD) and the suppression of multiple-access interference (MAI) in time-hopping UWB (TH-UWB) system is carried out considering the performance-complexity trade-off. The importance of MUD for achieving high data or low bit error rates in these systems has already been established in several studies. However, the optimum MUD can be characterized as a nondeterministic polynomial-time hard combinatorial optimization problem such that the computational complexity increases exponentially with number of user. In this paper, we proposed modified differential evolution (MDE) optimization algorithm with novel mutation and crossover strategy based MUD is investigated by simulations, when communicating over Saleh---Valenzuela (S---V) channel model. The RAKE detector is used as the first stage to initialize the MDE-based MUD. Then, the MDE algorithm is applied to detect the received data bit by optimizing an objective function incorporating the system of the RAKE detector. The performance evaluation with extensive simulations show that our proposed MDE based MUD can go to convergence rapidly under TH-UWB channel model, the bit error ratio performance is better than of the traditional MUD.

LMS Blind Adaptive Multiuser Detection for Underwater Acoustic Communication with MMSE and MOE Criteria

In order to solve detection of multi-user detection in underwater acoustic communication networks, blind adaptive multiuser detection method using LMS algorithm was proposed to solve the MAI problem of multi-user detection in underwater acoustic communication channel when users increase. Two type simulations were executed, including synchronous and asynchronous multi-user simulation analysis, to verify the validity of LMS multi-user detection algorithm and inspection machine. The verification of the effectiveness of the MMSE and MOE algorithm for LMS multi-user detection algorithm was done by simulation.

Channel Estimation and Information Symbol Detection for DS-UWB Communication Systems

The UWB channel estimation and multiuser detection problem are investigated. The information symbol and channel parameter are considered as unknown variables. The multiuser detector and UWB channel estimator are designed jointly. For symbol detection, the one-step predictor of channel parameter is used and the estimation error is treated as a multiplicative noise; then a Riccati equation and a Lyapunov equation will be needed. If the transmitted symbols are uncorrelated and identically distributed random variables with zero mean and unit variance, only a Riccati equation needs to be solved. For UWB channel estimation, the one-step predictor of information symbol is used and the estimation error is also considered as a multiplicative noise. The solutions to the above two problems are obtained by solving a couple of Riccati equations together with two Lyapunov equations.

Multiuser detection using soft particle swarm optimization along with radial basis function

The multiuser detection (MUD) problem was addressed as a pattern classication problem. Due to their strength in solving nonlinear separable problems, radial basis functions, aided by soft particle swarm optimization, were proposed to perform MUD for a synchronous direct sequence code division multiple access system. The proposed solution was shown to exhibit performance better than a number of other suboptimum detectors including the genetic algorithm and the classical particle swarm optimization algorithm.

Dual‐antenna‐based blind joint hostile jamming cancellation and multi‐user detection for uplink of asynchronous direct‐sequence code‐division multiple access systems

The authors investigate the problem of blind multi-user detection (MUD) for uplink of asynchronous direct-sequence code-division multiple access (DS-CDMA) systems with hostile jamming. To cope with the lack of prior knowledge of spread signals, hostile jamming and channel state information, the authors propose a scheme based on blind source separation (BSS) to solve this problem. Dual receive antennas are used in the proposed scheme. By exploiting the structure of the two received signals, a BSS model with dependent sources is formed, and then blind hostile jamming cancellation and MUD are obtained by solving this BSS problem. The proposed scheme does not require to know any information about the hostile jamming, and can work well under multiple kinds of hostile jamming. Simulation results further demonstrate that if such proposed approach is used to cancel hostile jamming and make MUD, then the bit-error-rate performance can be substantially improved as compared with earlier detectors.

Multiuser Detection Based on Adaptive LMS and Modified Genetic Algorithm in DS-CDMA Communication Systems

In this paper, we present an efficient evolutionary algorithm for the multi-user detection (MUD) problem in direct sequence-code division multiple access (DS-CDMA) communication systems. The optimum detector for MUD is the maximum likelihood (ML) detector, but its complexity is very high and involves an exhaustive search to reach the best fitness of transmitted and received data. Thus, there has been considerable interest in suboptimal multiuser detectors with less complexity and reasonable performance. The proposed algorithm is a combination of adaptive LMS Algorithm and modified genetic algorithm (GA). Indeed the LMS algorithm provides a good initial response for GA, and GA will be applied for this response to reach the best answer. The proposed GA reduces the dimension of the search space and provides a suitable framework for future extension to other optimization algorithms. Our algorithm is compared to ML detector, Matched Filter (MF) detector, conventional detector with GA; and Adaptive LMS detector which have been used for MUD in DS-CDMA. Simulation results show that the performance of this algorithm is close to the optimal detector with very low complexity, and it works better in comparison to other algorithms.

Optimized Spread Spectrum Watermarking for Fading-Like Collusion Attack with Improved Detection Performance

This paper proposes an optimized spread spectrum image watermarking scheme robust against fading-like collusion attack using genetic algorithms (GA) in multiband (M-band) wavelet decomposition. M-band decomposition of host data offers advantages in better scale-space tiling and good energy compactness. This makes watermarking robust against frequency selective fading-like attack gain. On the other hand, GA would determine a threshold value for the selection of host coefficients (process gain i.e. the length of spreading code) used in watermark casting along with the respective embedding strengths. We then consider colluder (random gain) identification as multiuser detection problem and use successive interference cancelation (SIC) to accurately detect weak (low gain) colluder and innocent users too. A weighted correlator is developed first where weight factors are calculated through training/learning using a neural network. A closed mathematical form of joint probability of error is developed with the objective of minimizing the probability of false detection i.e. a colluder is identified as an innocent user and an innocent user is identified as a colluder, for a set of colluders involved. Simulation results show the relative performance gain of the weighted correlator and SIC scheme compared to the existing works.

A simple quantum-inspired bee colony algorithm for discrete optimisation problems

To design a novel intelligence algorithm for discrete optimisation problem, a simple quantum-inspired bee colony algorithm SQBCA is proposed. The proposed SQBCA applies the quantum computing theory to bee colony optimisation BCO, which is an effective discrete optimisation algorithm. Then the proposed simple quantum-inspired bee colony algorithm is used to solve benchmark functions and multiuser detection problems of code division multiple access CDMA system. By hybridising the bee colony optimisation and quantum computing theory, the quantum state and binary state of the quantum bees can be well evolved by simulated quantum rotation gate and simulated quantum not gate. The new robust multiuser detection based on SQBCA can search the global optimal solution. Simulation results for CDMA systems are provided to show that the proposed robust multiuser detection method is superior to the multiuser detection based on previous intelligence algorithms.

A Continuous Relaxation Method for Multiuser Detection Problem

Based on the binary quadratic programming model of the code division multiple access maximum likelihood multiuser detection problem, a detection strategy by the continuous relaxation method is presented. The proposed method relaxes the binary quadratic programming as a nonlinear programming, which is a quadratic objective function with simple quadratic constraints. A feasible direction method is used to solve the nonlinear programming. Based on the KKT solution of the nonlinear programming, a near optimal solution is obtained for the multiuser detection problem. Simulation results show that the bit error rate performances of a detection strategy based on the continuous relaxation method is low. Furthermore, average CPU time of continuous relaxation method is much lower than that of the semidefinite programming relaxation method, especially for the large-scale detection problems. This approach provides good approximations to the optimal maximum likelihood performance.

Iterative Multiuser Detection of Spectrally Efficient FDMA CPM

This paper presents two new iterative multiuser detection algorithms for spectrally efficient frequency division multiple access continuous phase modulation in additive white Gaussian noise. The detectors are derived from the sum-product algorithm and the factor graph framework, performing approximate maximum a posteriori (MAP) bit detection. A factor graph of the actual multiuser detection problem is considered, rather than only factor graphs of the individual single user detection problems combined with ad-hoc inter-user interference cancellation. The practical implementation of the detectors is based on the assumption that a suitable set of sum-product messages can be approximated by a Gaussian distribution. This methodology allows to considerably reduce the computational complexity and memory size requirements as compared to a straightforward application of the sum-product rules. The proposed algorithms further succeed in achieving a good error performance.

Electromagnetism‐like method tuned constant modulus algorithm for blind detector in multicarrier CDMA system

SUMMARYThis paper presents an efficient meta‐heuristic algorithm based on electromagnetism‐like method, which has been successfully implemented in multiuser detection problems. The contribution revisits blind multiuser detection for multicarrier code division multiple access systems using a novel combined adaptive step‐size constant modulus algorithm (CMA) and electromagnetism‐like method scheme. To work around potentially computational intractability and improved the capability of suppressing multiple access interference (MAI) for Multicarrier CDMA System, the proposed scheme exploits heuristics in consideration of both global and local exploration of the step size of the CMA. Simulation results obtained confirm that faster convergence and desirable BER performance with low computational complexity can be achieved with electromagnetism‐like method based CMA scheme, compared with the previous step‐size CMA scheme, genetic algorithm, and particle swarm optimization with CMA scheme. Copyright © 2012 John Wiley & Sons, Ltd.

The Spectral Efficiency of Successive Cancellation With Linear Multiuser Detection for Randomly Spread CDMA

We consider the problem of multiuser detection for randomly spread direct-sequence (DS) code-division multiple access (CDMA) over flat fading channels. The analysis focuses on the case of many users, and large spreading sequences such that their ratio, which is the system load, is kept fixed. Spectral efficiency of practical linear detectors such as match-filter and decorrelator employing successive interference cancellation (SIC) at the receiver is derived. This is used to extend the notion of strongest users detectors for SIC receivers. The strongest users detectors system design relies on an outage approach where each user transmits in a single layer (fixed rate), and only users experiencing good channel conditions may be reliably decoded, while the other users are in outage, i.e., not decoded. In this scheme, iterative SIC decoding is studied, and it is shown that for equal power users, the optimal rate allocation, for maximizing the expected spectral efficiency, is equal rates for all users. This outage approach analysis is extended for multilayer coding broadcast approach per user. The expected sum-rate, under iterative decoding with linear multiuser detectors, is optimized, and the optimal layering power distribution is obtained. For small system loads, the achievable spectral efficiency with the continuous broadcast approach and a linear matched filter detector exhibits significant gains over the single layer coding approach.

Local Search Detection in Multiple Access DS/CDMA Networks

This paper demonstrates the effectiveness of local search algorithm (LS) for multiuser detection (MuD) in multiple access DS/CDMA communication networks, using digital sinal processing platform. Even been the simplest search algorithm found in literature, the 1-LS algorithm applied to MuD problem is capable to achieve good performance-complexity tradeoff, indicating a certain efficiency in approaching the optimal solution (NP complete problem) under severe operation system and channel conditions, i.e., flat Rayleigh channel, medium and high system loading and a wide range for signal-noise ratio.

Multiuser detection with sparse spectrum Gaussian process regression

Multiuser detection in direct-sequence code-division multiple access (DS-CDMA) systems can be implemented by using Gaussian process (GP) for regression in the sense of minimum mean square error criterion. In this Letter we investigate the application of sparse spectrum Gaussian process (SSGP) to the multiuser detection problem. The key point of the SSGP is that the sparsity of spectral representation of Gaussian process leads to an algorithm with much lower complexity than the full GP, while keeping almost the same bit error rate (BER) for DS-CDMA systems. Experimental results validate our proposed SSGP based multiuser detection method. It achieves greater efficiency and good BER performance.

Asynchronous code-division random access using convex optimization

Many applications in cellular systems and sensor networks involve a random subset of a large number of users asynchronously reporting activity to a base station. This paper examines the problem of multiuser detection (MUD) in random access channels for such applications. Traditional orthogonal signaling ignores the random nature of user activity in this problem and limits the total number of users to be on the order of the number of signal space dimensions. Contention-based schemes, on the other hand, suffer from delays caused by colliding transmissions and the hidden node problem. In contrast, this paper presents a novel pairing of an asynchronous non-orthogonal code-division random access scheme with a convex optimization-based MUD algorithm that overcomes the issues associated with orthogonal signaling and contention-based methods. Two key distinguishing features of the proposed MUD algorithm are that it does not require knowledge of the delay or channel state information of every user and it has polynomial-time computational complexity. The main analytical contribution of this paper is the relationship between the performance of the proposed MUD algorithm in the presence of arbitrary or random delays and two simple metrics of the set of user codewords. The study of these metrics is then focused on two specific sets of codewords, random binary codewords and specially constructed algebraic codewords, for asynchronous random access. The ensuing analysis confirms that the proposed scheme together with either of these two codeword sets significantly outperforms the orthogonal signaling-based random access in terms of the total number of users in the system.

Interference cancellation for HNNPSO multiuser detection of UWB systems over multipath fading channel

The problem of multiple access interference (MAI) and inter-symbol interference (ISI) suppression in direct-sequence ultra-wideband (DS-UWB) systems is considered. This paper is dedicated to the application of intelligence computational techniques based on bionics to solve the difficult issue of multiuser detection (MUD) design capable of canceling the so-called MAI to reach low bit error rate (BER) with acceptable computation complexity. We apply the stochastic algorithm that employs a Hopfield neural network (HNN) and particle swarm optimization (PSO) for the MUD problem in DS-UWB system. The use of the HNN embedded PSO (HNNPSO) technique for multiuser detection is a novel ideal, and it leads to efficient techniques that can find a satisfactory solution by maximizing likelihood (ML) function in a small number of iterations. The computer experiments showed that the proposed HNNPSO technique not only can find optimal or close-to-optimal solutions but also obtain both better and more robust results than the existing algorithm reported recently in this literature.