基于Gibbs采样的群盲多用户检测技术

多用户检测是第三代移动通信系统中的一项关键技术。研究存在邻近小区干扰时异步多径DS-CDMA信号的多用户检测问题。提出一种新颖的基于Gibbs采样的群盲多用户检测技术，它根据线性群盲解相关器的输出，利用Gibbs采样进行Bayes多用户检测。存在信道编码时，提出的检测器非常适合做Turbo多用户检测，仍然能够找到Bayes解。该方法具有简单易实现、检测性能好、应用范围广泛的优点。仿真实验证实了这一点。     

Group-blind multiuser detection for uplink CDMA

Previously developed blind techniques for multiuser detection in code division multiple access (CDMA) systems lead to several near-far resistant adaptive receivers for demodulating a given user's data with the prior knowledge of only the spreading sequence of that user. In the CDMA uplink, however, typically the base station receiver has the knowledge of the spreading sequences of all the users within the cell, but not that of the users from other cells. In this paper, group-blind techniques are developed for multiuser detection in such scenarios. These new techniques make use of the spreading sequences and the estimated multipath channels of all known users to suppress the intracell interference, while blindly suppressing the intercell interference. Several forms of group-blind linear detectors are developed based on different criteria. Moreover, group-blind multiuser detection in the presence of correlated noise is also considered. In this case, two receiving antennas are needed for channel estimation and signal separation. Simulation results demonstrate that the proposed group-blind linear multiuser detection techniques offer substantial performance gains over the blind linear multiuser detection methods in a CDMA uplink environment     

Iterative Group-Blind Multiuser Detection and Decoding With Signal Rank Estimation for Coded CDMA Systems

In this paper, a turbo receiver structure is proposed for the uplink of coded code-division multiple-access (CDMA) systems in the presence of unknown users. The proposed receiver consists of two stages following each other. The first stage performs soft interference cancellation and group-blind linear minimum mean square error (MMSE) filtering, and the second stage performs channel decoding. The proposed group-blind linear MMSE filter suppresses the residual multiple-access interference (MAI) from known users based on the spreading sequences and the channel characteristics of these users while suppressing the interference from other unknown users using a subspace-based blind method. The proposed receiver is suitable for suppressing intercell interference in heavily loaded CDMA systems. Since the knowledge of the number of unknown users is crucial for the proposed receiver structure, a novel estimator is also proposed to estimate the number of unknown users in the system by exploiting the statistical properties of the received signal. Simulation results demonstrate that the proposed estimator can provide the number of unknown users with high accuracy; in addition, the proposed group-blind receiver integrated with the new estimator can significantly outperform the conventional turbo multiuser detector in the presence of unknown users.      

一种新颖的异步多径CDMA信号的 贝叶斯多用户检测方法

马尔可夫链蒙特卡罗(MCMC)方法有效地解决了贝叶斯计算的问题,但是不容易将它应用于有未知干扰用户的异步多径CDMA系统.为了克服这一困难,本文提出一种新颖的贝叶斯多用户检测方法,它首先用线性群盲解相关器对接收信号做预处理,然后再用Gibbs采样(一种典型的MCMC算法)做贝叶斯多用户检测.仿真结果表明,该方法的检测性能明显地优于线性群盲多用户检测,其计算复杂度的增加与小区内用户数目呈线性关系.为了进一步提高本文方法的性能,我们使用两级Gibbs采样,根据第一级Gibbs采样的输出得到更精确的参数估计,并把它用于第二级Gibbs采样中.仿真结果证明,与只使用一级Gibbs采样的方法相比,两级Gibbs采样的检测性能明显地改善了.     

A NOVEL DETECTOR FOR UPLINK CDMA SYSTEM WITH UNKNOWN INTERFERENCE

In this letter, the detection of asynchronous DS-CDMA signal with multipath fading and interference from neighboring cells is studied. A novel multiuser detector based on Gibbs sampler is proposed, in which Gibbs sampler is employed to perform the Bayesian multiuser detection according to the linear group-blind decorrelator output. Since Gibbs sampler is dependent of parameter estimation that can be improved by the output of the detector, an enhanced Gibbs sampier based detector using the improved parameter estimation is put forward. The novel multiuser detection technique has the advantages of high performance and wide applications. Computer simulations show its effectiveness.     

Robust multiuser detection in non-Gaussian channels

In many wireless systems where multiuser detection techniques may be applied, the ambient channel noise is known through experimental measurements to be decidedly non-Gaussian, due largely to impulsive phenomena. The performance of many multiuser detectors can degrade substantially in the presence of such impulsive ambient noise. We develop robust multiuser detection techniques for combating multiple-access interference and impulsive noise in CDMA communication systems. These techniques are based on the M-estimation method for robust regression. Analytical and simulation results show that the proposed robust techniques offer significant performance gain over linear multiuser detectors in impulsive noise, with little attendant increase in computational complexity. We also develop a subspace-based technique for blind adaptive implementation of the robust multiuser detectors, which requires only the signature waveform and the timing of the desired user in order to demodulate that user's signal. The robust multiuser detection technique and its blind adaptive version can be applied to both synchronous and asynchronous CDMA channels     

不完全信道状态信息条件下多用户Turbo-BLAST迭代检测算法

该文将空时多用户检测技术和Turbo-BLAST方案相结合,构造了基于CDMA技术的多用户Turbo- BLAST系统模型,提出了不完全信道状态信息条件下的解相关算法和迭代检测算法。在发送端将V-BLAST结构与CDMA技术相结合实现多路复用,在接收端利用空时多用户检测算法去除用户间干扰,得到期望用户的接收信号,然后采用考虑信道估计误差的软干扰抵消迭代检测算法,对期望用户的接收信号进行检测以去除天线间干扰。仿真结果说明,所提算法对于多用户Turbo-BLAST系统是有效的,可在不增加复杂度的条件下达到良好的迭代效果。     

Adaptive transmitter optimization for blind and group-blind multiuser detection

The linear subspace-based blind and group-blind multiuser detectors recently developed represent a robust and efficient adaptive multiuser detection technique for code-division multiple-access (CDMA) systems. In this paper, we consider adaptive transmitter optimization strategies for CDMA systems operating in fading multipath environments in which these detectors are employed. We make use of more recent results on the analytical performance of these blind and group-blind receivers in the design and analysis of the transmitter optimization techniques. In particular, we develop a maximum-eigenvector-based method of optimizing spreading codes for given channel conditions and a utility-based power control algorithm for CDMA systems with blind or group-blind multiuser detection. We also design a receiver incorporating joint optimization of spreading codes and transmitter power by combining these algorithms in an iterative configuration. We will see that the utility-based power control algorithm allows us to efficiently set performance goals through utility functions for users in heterogeneous traffic environments and that spreading code optimization allows us to achieve these goals with lower transmit power. The signal processing algorithms presented here maintain the blind (or group-blind) nature of the receiver and are distributed, i.e., all power and spreading code adjustments can be made using only locally available information.     

Semiblind channel estimation for pulse-based ultra-wideband wireless communication systems

This paper proposes an H/sub /spl infin// based semiblind channel estimation algorithm for pulse-based ultra-wideband (UWB) wireless communication systems. In the proposed scheme, sparsely inserted periodic pilot symbols are exploited to adapt to not only the time-varying channel fading and noise processes but to their changing statistics and potential external disturbances, such as interference. While the existing optimal filtering-based channel estimation schemes, which are optimized mostly for traditional narrowband or wideband systems, require a priori knowledge of the channel and noise statistics, the proposed scheme does not. By further making full use of the channel characteristics unique in UWB systems, the proposed method is thus especially useful for robust operation in the highly frequency-selective UWB indoor channels for which the channel statistics are environment-dependent, and the noise processes do not necessarily satisfy the white Gaussian distribution in the presence of potential narrowband and multiuser interferences. Performance gain of the proposed scheme over the least square method, an existing technique that could also be applied to UWB channels with unknown statistics, and the Wiener filter-based algorithm is also provided.     

Design of Large Scale MU-MIMO System with Joint Precoding and Detection Schemes for Beyond 5G Wireless Networks

The large scale multiuser multiple input multiple output (MU-MIMO) is one of the promising communication technology for 5G wireless networks as it offers reliability, high spectral efficiency and high throughput. The lattice reduction (LR) precoding based user level local likelihood ascent search (ULAS) detection scheme is proposed in this paper for efficient signal detection in large scale MU-MIMO system. The initial solution of ULAS algorithm is obtained from the LR precoding assisted zero forcing detector. The LR precoding transforms the non-orthogonal channel matrix into nearly orthogonal channel, which helps to mitigate inter antenna interference (IAI) exists at each user. The remaining multiuser interference (MUI) imposed to each user from undesired users is cancelled by the proposed ULAS multiuser detection scheme. Thus, the proposed LR precoding assisted ULAS mitigates both IAI and MUI unlike the classical detector, those try to moderate either IAI or MUI. By contrast, the proposed ULAS detector provides performance close to optimal maximum likelihood detector with just a fraction of its complexity.

     

Improved Robust Techniques for Multiuser Detection in Non-Gaussian Channels

In many physical channels where multiuser detection techniques are to be applied, the ambient channel noise is known through experimental measurements to be decidedly non-Gaussian, due largely to impulsive phenomena. This is due to the impulsive nature of man-made electromagnetic interference and a great deal of natural noise. This paper presents a robust multiuser detector for combating multiple access interference and impulsive noise in code division multiple access (CDMA) communication systems. A new M-estimator is proposed for "robustifying" the detector. The approach is corroborated with simulation results to evaluate the performance of the proposed robust multiuser detector compared with that of the linear decorrelating detector, and the Huber and the Hampel M-estimator based detectors. Simulation results show that the proposed detector with significant performance gain outperforms the linear decorrelating detector, and the Huber and the Hampel M-estimator based detectors. This paper also presents an improved robust blind multiuser detection technique based on a subspace approach, which requires only the signature waveform and the timing of the desired user to demodulate that user's signal. Finally, we show that the robust multiuser detection technique and its blind adaptive version can be applied to both synchronous and asynchronous CDMA channels.     

Code-aided interference suppression for DS/CDMA communications. I.Interference suppression capability

A code-aided technique for the simultaneous suppression of narrow-band interference (NBI) and multiple-access interference (MAI) in direct-sequence code-division multiple-access (DS/CDMA) networks is proposed. This technique is based on the linear minimum mean-square error (MMSE) algorithm for multiuser detection. The performance of this technique against MAI has been considered previously. In this paper, its performance against NBI as well as combined NBI and MAI is addressed. Specifically, the performance of this technique against three types of narrow-band interferers, namely, multitone interferers, autoregressive (AR) interferers, and digital interferers, is analyzed. The NBI suppression performance of this method is then compared with performance bounds of the linear and nonlinear estimator-subtracter NBI suppression techniques. It is seen that this method outperforms all of the previous linear or nonlinear methods of NBI suppression, while simultaneously suppressing the MAI     

Joint Frequency-Domain Multiuser Turbo Equalization with Successive Interference Cancellation for Doubly-Selective Fading Channels

A novel multiuser separation and equalization scheme is proposed for single carrier wireless communication systems integrating frequency-domain (FD) multiuser turbo equalization (MUTE) and successive interference cancellation (SIC). The proposed iterative structure consists of multiple layers of detection, and at each layer the user with strongest power is processed by a frequency-domain multiuser equalizer to yield the soft extrinsic information on the coded bits of that user, which is delivered to a channel decoder after deinterleaving. The extrinsic information gleaned by the decoder is fed back to both the current and previous multiuser equalizers for the next iteration as a-priori information. The soft symbols of the current user are evaluated by the a-posteriori information of coded bits provided by the multiuser equalizer, and the interference reconstructed by the current user’s soft symbols is canceled out from the received signals in frequency domain. The interference-canceled signals are fed forward to subsequent layers for detection of other users. The proposed scheme effectively mitigates multiple access interference and intersymbol interference by an iterative (turbo) detection method. Numerical simulation examples demonstrate that the proposed FD MUTE with SIC outperforms the traditional MMSE multiuser equalizer over the severely doubly-selective channels, and the bit-error-rate performance tends to be better with the increase of iterations.     

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.     

Cross‐entropy‐based joint carrier frequency offset estimation and multiuser detection for multicarrier code division multiple access systems

This paper presents a joint carrier frequency offset estimation and multiuser detection based on a maximum likelihood approach in multicarrier code division multiple access systems. With the definition of a score function based on the log‐likelihood, the joint carrier frequency offset estimation and multiuser detection can be formulated as a nonlinear optimization problem over the joint of a multidimensional real space and a multidimensional discrete space. To reduce the computational complexity required by the joint decision statistic, while still obtaining a desirable performance, a new method using cross‐entropy optimization is proposed to solve the nonlinear optimization problem. Because of the robustness of the cross‐entropy optimization, the joint decision statistic can be efficiently solved, and, as shown by the furnished simulation results, the proposed approach can achieve satisfactory performance in various scenarios. Copyright © 2011 John Wiley & Sons, Ltd.     

Iterative (turbo) soft interference cancellation and decoding forcoded CDMA

The presence of both multiple-access interference (MAI) and intersymbol interference (ISI) constitutes a major impediment to reliable communications in multipath code-division multiple-access (CDMA) channels. In this paper, an iterative receiver structure is proposed for decoding multiuser information data in a convolutionally coded asynchronous multipath DS-CDMA system. The receiver performs two successive soft-output decisions, achieved by a soft-input soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders, through an iterative process. At each iteration, extrinsic information is extracted from detection and decoding stages and is then used as a priori information in the next iteration, just as in turbo decoding. Given the multipath CDMA channel model, a direct implementation of a sliding-window SISO multiuser detector has a prohibitive computational complexity. A low-complexity SISO multiuser detector is developed based on a novel nonlinear interference suppression technique, which makes use of both soft interference cancellation and instantaneous linear minimum mean-square error filtering. The properties of such a nonlinear interference suppressor are examined, and an efficient recursive implementation is derived. Simulation results demonstrate that the proposed low complexity iterative receiver structure for interference suppression and decoding offers significant performance gain over the traditional noniterative receiver structure. Moreover, at high signal-to-noise ratio, the detrimental effects of MAI and ISI in the channel can almost be completely overcome by iterative processing, and single-user performance can be approached     

Iterative semiblind multiuser receivers for a space-time block-coded MC-CDMA uplink system

Iterative multiuser detection and space-time coding are two promising techniques to improve the capacity and performance of coded multiuser systems in wireless channels. In this paper, we present iterative multiuser detection schemes for a space-time block-coded multicarrier code-division multiple-access system with multiple transmit and receive antennas. We consider a more general case of an uplink system in the presence of both intra- and intercell interferences. We propose two types of iterative semiblind space-time receivers for such an uplink environment. The first is based on the minimum mean-square error criterion and the second is a hybrid scheme based on a combination of parallel interference cancellation and linear multiuser detection. These iterative receivers are derived, using a subspace approach, which utilizes known users' information for the computation of log-likelihood ratios (LLRs) while blindly suppressing the unknown interference. The LLRs are refined successively during the iterative process by using the extrinsic information available through decoding of all known users. A turbo code is used for channel coding. Simulation results in a frequency-selective Rayleigh-fading environment are presented to verify the performance of the proposed schemes.     

Subspace methods for blind joint channel estimation and multiuser detection in CDMA systems

Recently developed subspace techniques for blind adaptive multiuser detection are briefly reviewed first. In particular, blind methods based on signal subspace tracking for adapting linear multiuser detectors in AWGN CDMA channels are considered, as well as extensions of these techniques to frequency selective fading channels, dispersive channels, and antenna array spatial processing. In addition, subspace‐based nonlinear adaptive techniques for robust blind multiuser detection in non‐Gaussian ambient noise channels are also described. Several new techniques are then developed within the subspace framework for blind joint channel estimation and multiuser detection, under some specific channel conditions. These include (1) an adaptive receiver structure for joint multiuser detection and equalization in dispersive CDMA channels, (2) a subspace method for joint multiuser detection and equalization in unknown correlated noise, and (3) a method for joint interference suppression and channel tracking in time‐varying fading channels. This revised version was published online in August 2006 with corrections to the Cover Date.     

Robust joint interference detection and decoding for OFDM-based cognitive radio systems with unknown interference

Cognitive radio technology facilitates spectrum reuse and alleviates spectrum crunch. One fundamental problem in cognitive radio is to avoid the interference caused by other communication systems sharing the same frequency band. However, spectrum sensing cannot guarantee accurate detection of the interference in many practical situations. Hence, it is crucial to design robust receivers to combat the in-band interference. In this paper, we first present a simple pilot aided interference detection method. To combat the residual interference that cannot be detected by the interference detector, we further propose a robust joint interference detection and decoding scheme. By exploiting the code structure in interference detection, the proposed scheme can successfully detect most of the interfered symbols without requiring the knowledge of the interference distribution. Our simulation results show that, even without any prior knowledge of the interference distribution, the proposed joint interference detection and decoding scheme is able to achieve a performance close to that of the maximum likelihood decoder with the full knowledge of the interference distribution     

Nonparametric multiuser detection in non-Gaussian channels

Existing multiuser detection techniques in wireless systems are based on the assumption that some information on the parameters of the probability density function (pdf) of ambient noise is available. Such information may not be available in all cases, particularly for non-Gaussian and impulsive noises, or may change depending on circumstances. In this paper, we present a technique for multiuser detection that does not require any a priori knowledge about the noise parameters. This method is based on using pseudo norms for linear nonparametric regression. Analytical and simulation results show that the proposed method offers an improved, or at least comparable, performance over existing robust techniques in the absence of any information on the nature of noise in the environment. The increased computational complexity is marginal compared to existing parametric detectors. In addition, the proposed nonparametric detector is portable in the sense that it does not need to be tuned for different noise models without any considerable degradation of performance. We also show that in non-Gaussian noise, the performance of blind adaptive nonparametric multiuser detectors is better than that of robust multiuser detectors.