Selective Multiuser Detection for Cellular CDMA Systems

Multiuser detection-oriented CDMA systems have been anticipated to significantly improve system capacity in third-generation W-CDMA-based systems. However, they are greatly limited by the computational complexity of multiuser receivers. In this work, we propose a new, computationally efficient approach to multiuser detection (MUD), consisting in MUD of the subset of preselected users, and conventional detection of the rest of users, called selective multiuser detection (SMD). It allows for full exploitation of available processing power at the receiver by use of MUD and provides remedy for computational complexity of MUD techniques when the number of active users increases beyond the processing capability. We propose and examine three different criteria for selection of users to be processed by the multiuser receiver and analyze the capacity for the single-cell and the multicell CDMA cellular system. The capacity improvement with respect to the conventional CDMA detector combines the gain from MUD and reduction of other-cell interference. We apply the analysis to two SMD schemes using decorrelator and successive interference canceller (SIC) as the multiuser receiver. The results indicate that the SMD is a promising alternative for MUD-oriented CDMA systems with large numbers of active users.     

Iterative reduced-complexity multiuser detection based on Chase decoding for synchronous turbo-coded CDMA system

The conventional multiuser detector (MUD) based on the a posteriori probability (APP) algorithm has an exponential computational complexity in terms of the number of users. In this paper, we propose a low-complexity iterative multiuser receiver for synchronous turbo-coded code-division multiple-access (CDMA) systems. The proposed receiver is based on the Chase decoding algorithm that was previously used to decode turbo product codes. Simulation results show that the proposed receiver can significantly reduce the computational complexity with slight performance degradation compared with the APP MUD over highly correlated channels. Moreover, in this paper, we develop a numerical approach to analyze the convergence behavior of iteratively decoded CDMA channels based on density evolution technique. Analytical results are presented and shown to provide a reasonable match with what is observed in simulation.     

A New Algorithm for Optimum Multiuser Detection in Synchronous CDMA Systems

Optimum multiuser detection for Code Division Multiple Access (CDMA) systems requires the solution of an NP-hard combinatorial optimization problem. It is well known that the computational complexity of the optimum multiuser detector is exponential with the number of active users in the system. In order to reduce the complexity of the optimum multiuser detection, we propose a Reduced Complexity Maximum Likelihood (RCML) algorithm that includes a set of novel certain boundary rules and characteristics. We investigate the performance and complexity tradeoffs for the RCML algorithm by conducting a set of simulations; Maximum Likelihood (ML) detection as a reference for performance comparisons, and relaxation based Semidefinite Programming (SDPB) algorithm as a reference for complexity comparisons. We show that the RCML algorithm is a promising algorithm for its computational savings over relaxation based algorithms in lightly-to-moderately loaded CDMA systems, and for its optimality in highly loaded CDMA systems.     

基于离散粒子群算法的CDMA多用户检测方法

研究了离散粒子群算法，并将其应用于CDMA多用户检测问题，提出一种基于离散粒子群优化算法的CDMA多用户检测的方法。该方法应用一种新的选择和分区搜索的策略，改进搜索的质量和效率。分析以及实验仿真表明该方法具有计算复杂度低且可以得到较好误码率性能的特点，为寻求新的多用户检测方法提供了思路。     

Decision-feedback soft-input/soft-output multiuser detector foriterative decoding of coded CDMA

The optimal decoding scheme for a code-division multiple-access (CDMA) system that employs convolutional codes results in a prohibitive computational complexity. To reduce the computational complexity, an iterative receiver structure was proposed for decoding multiuser data in a convolutional coded CDMA system. At each iteration, extrinsic information is exchanged between a soft-input/soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders. However, a direct implementation of the full-complexity SISO multiuser detector also has the exponential computational complexity in terms of the number of users. This paper proposes a low-complexity SISO multiuser detector based on tentative hard decisions that are made and fed back from the channel decoders in the previous iteration. The computational complexity of the proposed detector is linear in terms of the number of users and can be adjusted according to the complexity/performance tradeoff. Simulation results show that even with this simple feedback scheme, the performance of the coded multiuser system approaches that of the single-user system for moderate to high signal-to-noise ratios (SNRs)     

基于粒子滤波算法的DS-CDMA多用户检测

粒子滤波算法是一种基于贝叶斯估计的蒙特卡罗方法,尤其适用于处理非线性、非高斯系统的状态估计问题。该算法应用于DS-CDMA系统的多用户检测中,检测器能在检测性能和计算复杂度之间取得很好的平衡。基于粒子滤波算法的多用户检测器在性能上逼近于最优多用户检测器,而计算复杂度远低于最优多用户检测器,与次优多用户检测器相当。利用白化匹配滤波器的输出可以建立同步DS-CDMA系统的状态空间方程,使得粒子滤波算法应用于多用户检测中。仿真实例证明了基于粒子滤波算法的多用户检测器在等功率和远近效应的情况下的性能优势。     

A low-complexity SISO multiuser detector for iterative decoding of asynchronous CDMA systems with convolutional codes

The optimal decoding scheme for asynchronous code-division multiple-access (CDMA) systems that employ convolutional codes results in a prohibitive computational complexity. To reduce the computational complexity, an iterative receiver structure was proposed for decoding multiuser data in a convolutional coded CDMA system. At each iteration, extrinsic information is exchanged between a soft-input soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders. A direct implementation of the optimal SISO multiuser detector, however, has exponential computational complexity in terms of the number of users which is still prohibitive for channels with a medium to large number of users. This paper presents a low-complexity SISO multiuser detector using the decision-feedback scheme, of which tentative hard decisions are made and fed back to the SISO multiuser from the previous decoding output. In the proposed scheme, the log-likelihood ratios (LLR) as well as the tentative hard decisions of code bits are fed back from the SISO decoders. The hard decisions are used to constrain the trellis of the SISO multiuser detector and the LLRs are used to provide a priori information on the code bits. The detector provides good performance/complexity tradeoffs. The computational complexity of the detector can be set to be as low as linear in the number of users. Simulations show that the performance of the low-complexity SISO multiuser detector approaches that of the single-user system for moderate to high signal-to-noise ratios even for a large number of users.     

遗传算法在多用户检测中的应用研究

本文针对CDMA系统中多用户检测的组合优化问题,提出一种结合遗传算法和Hopfield神经网络的检测方法。该方法首先由遗传算法给神经网络提供一个初始解,神经网络在此基础上再进行局部寻优。研究表明：这种方法具有平方的计算复杂度,优于Hopfield神经网络检测方法、以及单独采用遗传算法的检测方法,对远近问题不敏感,具有良好的误码率性能和抗多址干扰性能。     

Reduced-complexity MAP-based iterative multiuser detection for coded multicarrier CDMA systems

In recent years, combining multiuser detection (MUD) and channel decoding has received considerable attention. The maximum a posteriori (MAP) criterion-based iterative multiuser detector greatly improves the system performance and can approach the performance of single-user coded systems. However, its complexity increases exponentially with the number of users and can become prohibitive for systems with a medium-to-large number of users. In this paper, a reduced complexity MAP-based iterative MUD based on the use of a soft sensitive bits algorithm is proposed for coded multicarrier code-division multiple-access systems. It is shown that it can greatly reduce the computational complexity with a minimal penalty in performance compared to the conventional optimal scheme.     

Suboptimum soft-output detection algorithms for coded multiuser systems

In this paper, we consider coded asynchronous multiuser signals in an additive white Gaussian noise channel. Since optimum joint multiuser detection (MUD) and forward error correction (FEC) decoding is characterized with a very high computational complexity, we consider disjoint MUD and FEC decoding. The optimum disjoint multiuser detector is the soft-output maximum a posteriori detector that provides sequences of a posteriori probabilities to the corresponding FEC decoders. It involves backward and forward recursions resulting in high complexity and processing delay. In this paper, we consider several suboptimum soft output disjoint multiuser detectors that involve only forward recursions and have reduced complexity and delay.     

A generalized probabilistic data association detector for multiple antenna systems

The Probabilistic Data Association (PDA) method for multiuser detection (MUD) over synchronous CDMA channels is extended to the signal detection problem in V-BLAST systems. Computer simulations show that the algorithm has an error probability that is significantly lower than that of the V-BLAST optimal order detector and has a computational complexity that is cubic in the number of transmit antennas.     

Fuzzy step size least mean square algorithm tuned linearly constrained constant modulus algorithm for multi‐carrier code division multiple access blind multiuser detector

Adaptive fuzzy logic step size least mean square algorithm (FLCLMS) tuning unit is designed to adjust the step size of the linear constrained constant modulus algorithm for blind multiuser detection (MUD) in multi‐carrier code division multiple access (MC‐CDMA) systems is presented. In wireless communications system, the conventional constant modulus algorithm for blind MUD has some disadvantages such as slow convergence speed and phase rotation. To overcome these shortages, a modified constant modulus algorithm was developed for blind multiuser detector. On the basis of the deterministic behavior of the FLCLMS algorithm, it has also proposed simplification over the cost function calculation, obtaining more efficient algorithm and creating new perspective for the MUD implementation. The proposed algorithm ensures the algorithm convergence to the desired user and suppresses the multiple access interference in this cost function. Thus, the performance of the system is improved. The computational experiments show that the proposed FLCLMS not only can find optimal or closed‐to‐optimal solutions but also can obtain the low computation complexity both better and more robust results than existing algorithm reported recently in the literature. Copyright © 2013 John Wiley & Sons, Ltd.     

Memory search multiuser detector in DS/CDMA systems

The optimal multiuser detector (MUD) in DS/CDMA systems requires the solution of a NP-hard combinatorial optimisation problem (COP). A near optimal MUD based on solving the COP with memory search method is proposed. With almost the same computational complexity as the parallel interference cancellation (PIC) MUD, it produces a better performance gain than PIC-MUD     

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.     

基于LMK准则的盲自适应多用户检测器

 本文提出了一种加性高斯白噪声(AWGN)信道下,同步直扩码分多址(DS/CDMA)系统的基于LMK(最小平均峰度,Least Mean Kurtosis)准则的线性盲自适应多用户检测器.这种检测器的算法是一种具有较低计算量的基于高阶统计量的算法.分析证明了这种检测器的算法的收敛性和可以实现多用户信号的盲解相关.并对基于该准则的线性盲自适应检测器和基于LMS(最小均方,Least Mean Square)准则的检测器的收敛性能进行了仿真比较.     

Hybrid iterative multiuser detection for channel coded space division multiple access OFDM systems

Space division multiple access (SDMA) aided orthogonal frequency division multiplexing (OFDM) systems assisted by efficient multiuser detection (MUD) techniques have recently attracted intensive research interests. The maximum likelihood detection (MLD) arrangement was found to attain the best performance, although this was achieved at the cost of a computational complexity, which increases exponentially both with the number of users and with the number of bits per symbol transmitted by higher order modulation schemes. By contrast, the minimum mean-square error (MMSE) SDMA-MUD exhibits a lower complexity at the cost of a performance loss. Forward error correction (FEC) schemes such as, for example, turbo trellis coded modulation (TTCM), may be efficiently combined with SDMA-OFDM systems for the sake of improving the achievable performance. Genetic algorithm (GA) based multiuser detection techniques have been shown to provide a good performance in MUD-aided code division multiple access (CDMA) systems. In this contribution, a GA-aided MMSE MUD is proposed for employment in a TTCM-assisted SDMA-OFDM system, which is capable of achieving a similar performance to that attained by its optimum MLD-aided counterpart at a significantly lower complexity, especially at high user loads. Moreover, when the proposed biased Q-function based mutation (BQM) assisted iterative GA (IGA) MUD is employed, the GA-aided system's performance can be further improved, for example, by reducing the bit error ratio (BER) measured at 3 dB by about five orders of magnitude in comparison to the TTCM-assisted MMSE-SDMA-OFDM benchmarker system, while still maintaining modest complexity.     

Population Declining Ant Colony Optimization Multiuser Detection in Asynchronous CDMA Communications

In this paper we present a population declining ant colony optimization (PDACO) multiuser detector for asynchronous CDMA communications. Ant colony optimization (ACO) algorithms have already been used in multiuser detection in CDMA systems; however, as the pheromone accumulates, we may not get a global optimum because it stops searching early. PDACO can enlarge searching range through increasing the initial population of the ant colony, and the population declines in successive iterations. So, the performance of PDACO is superior with the same computational complexity. PDACO is applied to multiuser detection in asynchronous CDMA systems over slowly multipath Rayleigh-fading channels in this paper. Via computer simulations it is shown that the performance of PDACO detector is much better in bit-error rate and near-far effect resistance than conventional detector, ACO detector and genetic algorithm detector, and is close the optimal multiuser detector.     

Genetic algorithm assisted joint multiuser symbol detection andfading channel estimation for synchronous CDMA systems

A novel multiuser code division multiple access (CDMA) receiver based on genetic algorithms is considered, which jointly estimates the transmitted symbols and fading channel coefficients of all the users. Using exhaustive search, the maximum likelihood (ML) receiver in synchronous CDMA systems has a computational complexity that is exponentially increasing with the number of users and, hence, is not a viable detection solution. Genetic algorithms (GAs) are well known for their robustness in solving complex optimization problems. Based on the ML rule, GAs are developed in order to jointly estimate the users' channel impulse response coefficients as well as the differentially encoded transmitted bit sequences on the basis of the statistics provided by a bank of matched filters at the receiver. Using computer simulations, we showed that the proposed receiver can achieve a near-optimum bit-error-rate (BER) performance upon assuming perfect channel estimation at a significantly lower computational complexity than that required by the ML optimum multiuser detector. Furthermore, channel estimation can be performed jointly with symbol detection without incurring any additional computational complexity and without requiring training symbols. Hence, our proposed joint channel estimator and symbol detector is capable of offering a higher throughput and a shorter detection delay than that of explicitly trained CDMA multiuser detectors     

Complexity of Verdu optimum multiuser detection algorithm inmultichannel CDMA systems

A statistical characterization of the complexity function of the Verdu optimum multiuser detection (VOMD) algorithm is presented for a communication system employing a finite number of randomly accessed orthogonal channels and a finite number of simultaneous users. Multichannel code-division multiple-access (CDMA) systems are proposed. It is proved that the probability, in which the individual channel complexity is greater than A^r(1+α), approaches zero exponentially fast as the average number of simultaneous users in each channel increases, where A is the modulation alphabet size and α>0. When the number of simultaneous users is large, the complexity of applying the VOMD algorithm to each individual channel is negligible when compared with the complexity of applying the same algorithm directly to the traditional single-channel CDMA system supporting the same number of simultaneous users. The probability distribution of the joint complexity function of the aggregate system is found. It is shown that when the number of simultaneous users is large, the joint complexity function is negligible compared with applying the VOMD algorithm directly to the traditional single-channel CDMA system supporting the same number of simultaneous users. Therefore, a multichannel CDMA communication system can support a comparable population of simultaneous users to the traditional single-channel CDMA system of comparable bandwidth, while reducing the complexity of optimum multiuser detection to a practical level     

一种基于可变禁忌长度的多用户检测方法

CDMA系统的性能很大程度上受多用户干扰影响。多用户检测是抑制多用户干扰的有效方法。文中介绍一种基于可变禁忌长度的多用户检测方法。该方法以传统匹配滤波器的判决输出为初始解,采用禁忌长度可变的禁忌搜索(TS)算法,使禁忌长度与搜索空间的崎岖程度相适应,以避免搜索限入局部最优。仿真实验证明,该方法具有较好的误比特性能和抗远近效应能力,并具有多项式复杂度。