Multiuser Detection Algorithm Research Articles

Interleave Division Multiple Access for Wireless Communication

[enter Abstract Body]This paper outlines a multiple access technique which exploits the interleaving as only means of user separation instead of by different signatures as in a conventional code division multiple-access (CDMA) scheme. It examines a very simple iterative chip-by-chip multi-user detection strategy for spread spectrum communication systems. The given scheme can achieve near single user performance in situations with very large numbers of users while maintaining very low receiver complexity. This technique shows that high performance can be maintained in multi-path environments. IDMA inherits many advantages from CDMA, such as diversity against fading and mitigation of the worst-case user interference problem. A low-cost iterative chip-by-chip multi-user detection algorithm is also described with complexity independent of the user number and increasing linearly with the path number.

CMA Blind Multiuser Detector Based on FLOS in Impulse Noise

Blind multiuser detector can suppress the MAI(multiple address interference) effectively. Gaussian channel noise is assumed in the traditional methods, but the non-Gaussian channel noise is more realistic. This paper proposes a new CMA(Constant Modulus Algorithm) criterion employing FLOS(fractional lower-order statistic). Theoretical analyses and the computer simulations indicate that the associated FLOS-CMA blind MUD(MultiUser Detection) method,based on a stochastic gradient descent algorithm has a good performance in BER(bit error rate). The traditional MUD algorithm is the special case of this algorithm.

Análise de Complexidade de Detectores Heurísticos DS/CDMA Implementados em Plataforma DSP

This work investigates issues concerning the computational complexity of multiuser receivers in direct sequence code division multiple access (DS/CDMA) systems based on heuristic techniques and implemented on commercial platform for digital signal processing (DSP) ( Texas TMS320C6713 ). The multiuser detection algorithms which were implemented in baseband are based on the heuristic local search (LS) and simulated annealing (SA) approaches. Figures of merit regarding to the computational complexity increasing, due to the system loading increment (number of active users) are discussed, and a brief methodology for the design/implementation of the baseband receiver using DSP platform is presented as well.

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.

Multi-User Detection Techniques for DS-CDMA UWB System

Ultra-wideband(UWB) is currently one of three new technologies of wireless communication. Multi-user detection technique is mainly used to eliminate multiple access interference（MAI）in DS-CDMA UWB communication systems. Linear multi-user detection algorithm for multi-access interference suppression or even elimination has certain results. But for a fixed decision threshold is set to 0, the detection performance of linear multi-user detection algorithm will be decreased significantly. Therefore a kind of multi-user detection with pre-processing has been researched. Through the pre-processing, we set dynamic threshold to direct decision the user's data bit information so as to solve the problem the linear multi-user detector’s decision threshold which is fixed impact the detection performance. We may get the global optimal solution though pre-processing of using the thought of the branch and bound algorithm and forcing rules. Then the original problem changes into a smaller multi-user detection problem, in order to get the aim of reducing MAI, increasing the probability of a correct decision and reducing the bit error rate. From the simulation experiment results, it is shown that it has a significant effect in system detection, because after pre-processing the probability of a correct decision has increased, and the bit error rate has been reduced.

An MBER–BLAST algorithm for OFDM–SDMA communication using particle swarm optimization

AbstractA multiple antenna‐aided, minimum bit error rate–Bell Laboratories‐layered space–time (MBER–BLAST) multiuser detection algorithm is proposed for uplink orthogonal frequency division multiplexing–space division multiple access (OFDM–SDMA) communication to increase the capacity of the system. The proposed algorithm overcomes the limitations of the conventional detectors when the number of users exceed the number of receiver antennas. A particle swarm optimization (PSO) algorithm is employed for finding the optimum weight vectors for MBER detector. PSO is well suited for physically realizable, real‐time applications, where low complexity and fast convergence are of absolute importance, while an optimum maximum likelihood (ML) detection using an exhaustive search method is prohibitively complex. The proposed algorithm outperforms the MBER detector and is capable of achieving performance close to that attained by ML detector at a significantly lower complexity, especially under high user loads. Simulation results show that MBER–BLAST detector promises substantially improved performance compared with the existing systems and offers a good performance–complexity trade‐off. It supports a large number of users by exploiting the capacity advantages of multiple antenna systems in rich scattering environments. Copyright © 2010 John Wiley & Sons, Ltd.

Robust multi-user detection based on quantum bee colony optimisation

To resolve local convergent difficulty of combinatorial optimisation algorithm, a quantum bee colony optimisation (QBCO) that employs novel evolutionary quantum equations is proposed. The proposed QBCO algorithm applies quantum coding and quantum rotation mechanism to evolutionary process of bee colony, which is a simple and effective discrete optimisation algorithm. Then, the proposed quantum bee colony optimisation algorithm is used to solve robust multi-user detection problem of code division multiple access (CDMA) system in the presence of impulsive noise. Furthermore, by hybridising the stochastic Hopfield neural network and quantum bee colony optimisation, the quantum state and measure state of the quantum bee are co-evolutionary in design of robust multi-user detection. The new multi-user detection algorithm can search global optimal solution in faster convergence rate. Simulation results for CDMA system are provided to show that the designed robust detectors are superior to some previous detectors in bit error rate (BER), multiple access interference and near-far resistance.

A novel bandwidth efficient SOC-based turbo coding scheme mid reduced complexity MUD for SA-based MC-CDMA systems

Multiuser-detection (MUD), turbo coding and smart-antennas (SA) are powerful techniques for enhancing the performance and capacity of MC-CDMA systems. Among the MUD algorithms, the maximum-likelihood (ML) method has the best performance but its complexity increases exponentially with the number of users and constellation size. In this paper, we first propose a novel bandwidth-efficient-channel-coding-scheme (BECCS) for a super-orthogonal-code (SOC)-based serially concatenated turbo code (SCSOC) so that by using it, the coded system without extra bandwidth significantly improves the performance of an uncoded system over a fading channel. Second, in order to reduce the complexity of the ML-based turbo MUD technique, an ML algorithm based on the sensitive-bits-algorithm (SBA) and a less-complex-norm-approximation (LCNA) based Euclidean distance is proposed for a SCSOC-based BECCS assisted coded MC-CDMA system accompanied by SA techniques at the receiver. Our analytical and simulation results show that from a performance perspective, at BER=10?2, the proposed SCSOC-based BECCS assisted MC-CDMA system performs 4 dB better than SOC-based coded systems. The latter system has 5 dB gain in comparison with an uncoded one, all in the same bandwidth and over fading channels.

A novel differential multiuser detection algorithm for multiuser MIMO-OFDM systems

We propose an efficient low bit error rate (BER) and low complexity multiple-input multiple-output (MIMO) multiuser detection (MUD) method for use with multiuser MIMO orthogonal frequency division multiplexing (OFDM) systems. It is a hybrid method combining a multiuser-interference-cancellation-based decision feedback equalizer using error feedback filter (MIMO MIC DFE-EFF) and a differential algorithm. The proposed method, termed ‘MIMO MIC DFE-EFF with a differential algorithm’ for short, has a multiuser feedback structure. We describe the schemes of MIMO MIC DFE-EFF and MIMO MIC DFE-EFF with a differential algorithm, and compare their minimum mean square error (MMSE) performance and computational complexity. Simulation results show that a significant performance gain can be achieved by employing the MIMO MIC DFE-EFF detection algorithm in the context of a multiuser MIMO-OFDM system over frequency selective Rayleigh channel. MIMO MIC DFE-EFF with the differential algorithm improves both computational efficiency and BER performance in a multistage structure relative to conventional DFE-EFF, though there is a small reduction in system performance compared with MIMO MIC DFE-EFF without the differential algorithm.

A Novel Graph-Based Suboptimal Multiuser Detector for FDM-CPM Transmissions

We consider a frequency division multiplexed (FDM) system where each user employs a continuous phase modulation (CPM), serially concatenated with an outer code through an interleaver, and iterative detection/decoding. In such a system, the spectral efficiency can be increased by reducing the spacing between two adjacent channels, thus increasing the relevant interference. Hence, we address the design of low-complexity suboptimal multiuser detectors able to effectively cope with such an interference. We extend some well known multiuser detection algorithms proposed for code division multiple access (CDMA) systems. Moreover, we introduce a new detection scheme using the framework based on factor graphs (FGs) and the sum-product algorithm (SPA). The simulation results show that the described algorithms allow to effectively reduce the spacing, thus increasing the spectral efficiency, and in particular, the proposed detection scheme results to be the most effective one in terms of performance and computational complexity.

An Adaptive Multiuser Detection Algorithm for CDMA Systems Using Antenna Diversity

Based on the minimum mean squared error (MMSE) between the data stream and the linear combiner output, a new multiuser detection (MUD) algorithm that combines space–time (ST) processing and antenna array on direct-sequence CDMA signals is proposed. The proposed ST-MUD algorithm is proved to be equivalent to two existing MMSE-based ST-MUD algorithms, and the theoretical BER performances for all the three algorithms are the same. The most attractive feature of the new ST-MUD algorithm is based on the fact that the new method does not require explicit estimation of channel and signaling information. This avoids any channel estimation error, and the method is thus more robust and more accurate than the other two ST-MUD algorithms in practical implementation. Adaptation of the proposed ST-MUD algorithm is implemented by using training sequences. Performance of this new multiuser detector is compared with that of two existing MMSE multiuser detectors and the conventional single-user space–time rake receiver through simulations. The proposed ST-MUD algorithm provides a performance better than existing algorithms and is especially suitable for practical CDMA systems.

A Polynomial Complexity Optimal Multiuser Detection Algorithm Based on Monotonicity Properties

An optimal multiuser detection algorithm with a computational complexity of O(K log K) is proposed for the class of linear multiple-access systems which have constant cross-correlation values. Here the optimal multiuser detection is implemented by searching for a monotone sequence with maximum likelihood, under the ranking of sufficient statistics. The proposed algorithm is intuitive and concise. It is carried out in just two steps, and at each step only one kind of operation is performed. Also, the proposed algorithm can be extended to more complex systems having more than a single cross-correlation value.

Adaptive parallel interference cancellation for CDMA systems—A weight selection and filtering scheme

Parallel interference cancellation (PIC) is a well-known multiuser detection algorithm in direct-sequence code-division multiple-access (DS-CDMA) systems. It is typically implemented with a multi-stage architecture. One problem associated with the PIC is that unreliable interference cancellation may occur in the early stages and the system performance may be degraded. Thus, the partial PIC detector was developed to control the cancellation level by use of interference cancellation factors. Partial PIC can be implemented with an adaptive form, in which optimal weights are derived using the least mean square (LMS) algorithm. In this paper, we propose an algorithm improving the conventional adaptive partial PIC. The main idea is to reduce the number of active weights in the LMS algorithm, and to perform weight post-filtering such that the resultant excess mean square error can be reduced. We also analyze the performance of the proposed algorithm and derive the bit error rate of the second stage output. Simulation results verify that the proposed algorithm outperforms the conventional partial PIC, and derived analytical results are accurate.

Fixed-point blind adaptive multiuser detection algorithm for IR UWB systems in multipath channel

Using the hypothesis that data transmitted by different users are statistically independent of each other, this paper proposes a fixed-point blind adaptive multiuser detection algorithm for Time-Hopping (TH) Impulse Radio (IR) Ultra Wide Band (UWB) systems in multipath channel, which is based on Independent Component Analysis (ICA) idea. The proposed algorithm employs maximizing negentropy criterion to separate the data packets of different users. Then the user characteristic sequences are utilized to identify the data packet order of the desired user. This algorithm only needs the desired user’s characteristic sequence instead of channel information, power information and time-hoping code of any user. Due to using hypothesis of statistical independence among users, the proposed algorithm has the outstanding Bit Error Rate (BER) performance and the excellent ability of near-far resistance. Simulation results demonstrate that this algorithm has the performance close to that of Maximum-Likelihood (ML) algorithm and is a suboptimum blind adaptive multiuser detection algorithm of excellent near-far resistance and low complexity.

Asynchronous CDMA Under Single-Carrier Block Transmission—Architectures and Signal Models

Single-carrier (SC) block transmission with frequency-domain equalization (FDE) is an efficient scheme that avoids complex time-domain equalization in multipath channels. There are also several systems that are proposed that apply SC-FDE in code-division multiple access (CDMA). However, the present CDMA systems with FDE may not be suitable for asynchronous users for lack of a signal model that can suitably express the despread signal in the frequency domain. In this paper, we first propose circularly sliding (CS) despreading that can attain preliminary separation of interference among asynchronous users. Then, we derive a signal model that represents spreading, channel effect, and despreading as a series of circular convolutions. This signal model helps to derive a new FD minimum mean-square error (MMSE) equalization algorithm for SC block transmission asynchronous CDMA. We further extend the signal model by including equalization as another circular convolution. The extended signal model indicates several equivalent architectures of the receiver. For these architectures, despreading and equalization can be implemented in either the time or frequency domain, and the order is exchangeable. Based on the proposed signal model, we also derive a RAKE combiner that can be implemented in the frequency domain. Our architectures and signal model can be applied for further development of multiuser-detection algorithms.

Multi-user detection algorithm based on simulated annealing parallel evolutionary programming

Multi-user detection algorithm based on simulated annealing parallel evolutionary programming

The Subspace-Based Linear Conjugate CMA in BPSK-Modulated MC-CDMA Systems

A subspace-based linear conjugate constant modulus algorithm (CMA) for blind adaptive multiuser detection in BPSK-Modulated MC-CDMA systems is proposed. First, a linear conjugate CMA algorithm is presented which jointly elaborates the received signal and its complex conjugate to utilize the information contained in the pseudo-autocorrelation of the observable, thus is capable of achieving much better performance. Second, to further improve the performance, the subspace method is applied to the linear conjugate CMA algorithm to obtain a subspace-based linear conjugate CMA algorithm, which mitigates the influence of the noise subspace. Finally, an improved projection approximation subspace tracking with deflation algorithm is proposed for adaptive signal subspace estimation to reduce the computational complexity. The proposed algorithm provides an improved robustness against the signature waveform mismatch, good tracking capability in dynamic environment and better output signal-to-interference-plus-noise-ratio and bit error rate performance. The superiority of the proposed algorithm is demonstrated through computer simulations.

Blind multiuser detection for MC-CDMA with antenna array

We investigate the characteristics of the received signal as trilinear model for multi-carrier code division multiple access (MC-CDMA) system with antenna array, and propose a blind multiuser detection method for MC-CDMA system in this paper. The trilinear-based multiuser detection algorithm (Trilinear-MUDE) that we presented exploits the versatile diversity in MC-CDMA system while require neither channel information nor statistical characteristics. The algorithmic performance indicates that the proposed algorithm is very close to the nonblind MMSE method, and better than minimum output energy (MOE) receiver and matched filter. Numerical results also reveal its compatibility in condition of small sampling sizes.

Complexity reduction of signal detection by exploiting correlation characteristics of spreading sequences

AbstractIn this paper, we propose an approach to reduce the multi‐user detection (MUD) complexity based on user grouping and signal replica classification by exploiting the correlation characteristics of spreading sequences in multipath fading channels. The spreading sequences are constructed from inter‐group complementary codes with a sparse and regular correlation matrix and inherit its attractive auto/cross‐correlation properties. Users are first partitioned into independent user groups according to whether or not there is interference among them, and then the replicas of user signals from the same user group are further classified into independent replica classes. The MUD is carried out within each low‐dimensional user group or replica class, respectively, reducing the MUD complexity substantially. This approach can be applied to most of the existing MUD algorithms for complexity reduction, and in this paper optimal MUD and multi‐stage MUD are exemplified. The analytical and simulated results demonstrate that this approach can reduce the MUD complexity significantly under any load conditions without performance loss. Copyright © 2009 John Wiley & Sons, Ltd.

Imperfect cross-correlation and amplitude balance effects on conventional multiuser decoder with turbo encoding

The present work aims to illustrate the improvement that turbo encoding/decoding algorithms can bring to a multiuser detection system, evaluated in terms of bit error rate (BER). Extended simulations have been performed for conventional multiuser detection algorithms and are still under study for other algorithms, like the optimal, the MMSE and the classical MMSE ones. Simulations have been performed in both optimal conditions and imperfect ones, like non-equal power of users and non-zero correlations between them and for different number of users. Several interesting conclusions have been highlighted with respect to parameters influence on overall system performances.