Group-blind intersymbol multiuser detection for downlink CDMA with multipath

Group-blind multiuser detectors for uplink code-division multiple-access (CDMA) were recently developed by Wang and Host-Madsen. These detectors make use of the spreading sequences of known users to construct a group constraint to suppress the intracell interference. However, such techniques demand the estimation of the multipath channels and the delays of the known users. In this paper, several improved blind linear detectors are developed for CDMA in fading multipath channels. The proposed detectors utilize the correlation information between consecutively received signals to generate the corresponding group constraint. It is shown that by incorporating this group constraint, the proposed detectors can provide different performance gains in both uplink and downlink environments. Compared with the previously reported group-blind detectors, our new methods only need to estimate the multipath channel of the desired user and do not require the channel estimation of other users. Simulation results demonstrate that the proposed detectors outperform the conventional blind linear multiuser detectors.     

一种频选衰落信道下的Turbo多用户检测算法

联合MAP多用户检测与信道解码的迭代多用户检测(MUD)技术可显著提高宽带移动CDMA系统的容量和性能.在多径时变衰落的编码信道下,提出一种迭代实现干扰抑制、符号估计、信道解码的Turbo多用户检测算法.在每次迭代中,MUD自适应地实现干扰抑制并输出符号估计的软信息,软输入软输出的信道解码器使用LOG MAP方法实现信道解码并反馈符号估计的软信息作为下一次TurboMUD迭代的先验信息.仿真结果证实了该算法在频选衰落信道下经两次迭代就能逼近单用户编码CDMA系统的接收性能.     

Blind multiuser detection in uplink CDMA with multipath fading: a sequential EM approach

We consider joint channel estimation and data detection in uplink asynchronous code-division multiple-access systems employing aperiodic (long) spreading sequences in the presence of unknown multipath fading. Since maximum-likelihood (ML) sequence estimation is too complex to perform, multiuser receivers are proposed based on the sequential expectation-maximization (EM) algorithm. With the prior knowledge of only the signature waveforms, the delays and the second-order statistics of the fading channel, the receivers sequentially estimate the channel using the sequential EM algorithm. Moreover, the snapshot estimates of each path are tracked by linear minimum mean-squared error filters. The user data are detected by a ML sequence detector, given the channel estimates. The proposed receivers that use the exact expressions have a computational complexity O(2/sup K/) per bit, where K is the number of users. Using the EM algorithm, we derive low-complexity approximations which have a computational complexity of O(K/sup 2/) per bit. Simulation results demonstrate that the proposed receivers offer substantial performance gains over conventional pilot-symbol-assisted techniques and achieve a performance close to the known channel bounds. Furthermore, the proposed receivers even outperform the single-user RAKE receiver with Nyquist pilot-insertion rate in a single-user environment.     

Distributed multiuser detection for the TDMA cellular uplink

A method for performing multiuser detection using observations from multiple base stations is proposed. Log-likelihood ratio estimates of the data are calculated at each base station and combined to form the final decision statistic. The proposed architecture is applied to the time division multiple access (TDMA) cellular uplink, and it is shown that heavily overloaded systems can perform remarkably well     

Iterative semi-blind multiuser detection for coded MC-CDMA uplink system

We propose two types of iterative semi-blind receivers for coded multicarrier code-division multiple-access (MC-CDMA) uplink systems in the presence of both intracell and intercell interference. The first is based on the minimum mean-square error criterion, and the second is a hybrid scheme, consisting of parallel interference cancellation and linear multiuser detection. These iterative receivers utilize known users' information for the computation of log-likelihood ratios (LLR) while blindly suppressing unknown interference. The LLR are refined successively during the iterative process through decoding of all known users. Simulation results demonstrate that the proposed iterative semiblind methods offer substantial performance gain over conventional noniterative and nonblind iterative receivers.     

Robust multiuser detection for multicarrier CDMA systems

Multiuser detection (MUD) for code-division multiple-access (CDMA) systems usually relies on some a priori channel estimates, which are obtained either blindly or by using training sequences, and the covariance matrix of the received signal, usually replaced by the sample covariance matrix. However, such prior estimates are often affected by errors that are typically ignored in subsequent detection. In this paper, we present robust channel estimation and MUD techniques for multicarrier (MC) CDMA by explicitly taking into account such estimation errors. The proposed techniques are obtained by optimizing the worst case performance over two bounded uncertainty sets pertaining to the two types of estimation errors. We show that although the estimation errors associated with the prior channel estimate and the sample covariance matrix are generally not bounded, it is beneficial to optimize the worst case performance over properly chosen bounded uncertainty sets determined by a parameter called bounding probability. At a slightly higher computational complexity, our proposed robust detectors are shown to yield improved performance over the standard detectors that ignore the prior estimation errors.     

Turbo multiuser detection for differentially modulated CDMA

In this letter, we study differentially modulated, iteratively decoded CDMA. The iterative multiuser receiver proposed consists of an additional soft-input soft-output (SISO) differential decoder, when compared to turbo multiuser detectors for absolutely modulated systems. Algorithms for iterative decoding with and without phase information at the receiver are developed. The resulting turbo receivers with differential modulation outperform coherent receivers with absolute modulation at moderate to high signal to noise ratios due to the interleaver gain associated with recursive inner encoders in serially concatenated encoding structures.     

Subspace blind adaptive detection for multiuser CDMA

Direct adaptive realizations of the linear minimum mean-square error (MMSE) receiver for direct-sequence code-division multiple access possess the attractive feature of not requiring any explicit information of interference parameters such as timing, amplitudes, or spreading sequences; however, they need a training sequence for the desired user. Previously, a new blind adaptive receiver was proposed based on an anchored least mean-squared (LMS) algorithm that requires only the spreading code and symbol timing of the desired user but obviates the need for a training sequence. In this work, it is analytically demonstrated that the blind LMS algorithm always provides (nominally) faster convergence than the training driven LMS-MMSE receiver of but at the cost of increased tap-weight fluctuations or misadjustment. Second, the property that the optimal MMSE or minimum-output energy filter coefficients lies in the signal subspace is exploited to propose a new efficient blind adaptive receiver requiring fewer adaptive coefficients. Improved detector characteristics (superior convergence rates and steady-state signal-to-interference-plus-noise ratios) is indicated by analysis and supported by simulation     

Linear space-time multiuser detection for multipath CDMA channels

We consider the problem of detecting synchronous code division multiple access (CDMA) signals in multipath channels that result in multiple access interference (MAI). It is well known that such challenging conditions may create severe near-far situations in which the standard techniques of combined power control and temporal single-user RAKE receivers provide poor performance. To address the shortcomings of the RAKE receiver, multiple antenna receivers combining space-time processing with multiuser detection have been proposed in the literature. Specifically, a space-time detector based on minimizing the mean-squared output between the data stream and the linear combiner output has shown great potential in achieving good near-far performance with much less complexity than the optimum space-time multiuser detector. Moreover, this space-time minimum mean-squared error (ST-MMSE) multiuser detector has the additional advantage of being well suited for adaptive implementation. We propose novel trained and blind adaptive algorithms based on stochastic gradient techniques, which are shown to approximate the ST-MMSE solution without requiring knowledge of the channel. We show that these linear space-time detectors can potentially provide significant capacity enhancements (up to one order of magnitude) over the conventional temporal single-user RAKE receiver     

Iterative reduced-state multiuser detection for asynchronous coded CDMA

The conventional maximum a posteriori receiver for coded code-division multiple-access (CDMA) systems has exponential computational complexity in terms of the number of users and the memory of the channel code. In this letter, we propose a low-complexity soft-input soft-output (SISO) multiuser detector based on the reduced-state a posteriori probability algorithm. Per-survivor processing and soft interference cancellation are used to remove the residual past and future interference in the branch metric computation. The complexity of the proposed receiver is related to the reduced memory of the CDMA channel and can be adjusted according to the complexity/performance tradeoff. Simulation results show that for asynchronous convolutionally coded systems, the proposed receiver can achieve the near-single-user performance for moderate to high signal-to-noise ratios.     

Layered space-time multiuser detection over wireless uplink systems

In this paper, we investigate the use of layered space-time (also known as the vertical Bell Laboratories layered space-time (V-BLAST) scheme) for multiuser detection in fading channels. The multiple transmit antennas in V-BLAST are treated as individual mobile station transmitters, while the base station consists of multiple receive antennas. In the proposed system, users are organized in groups and allocated a unique spreading code within the same group. Using these codes, we are able to separate the different groups, and layered space-time algorithm is then invoked to further remove the remaining interference between users. A decorrelator-type receiver-based layered space-time detection is proposed for both complex and real constellations. For the latter case, we derive our receiver after evaluating and comparing the performance of two decorrelators based on the V-BLAST scheme. It is demonstrated that a significant performance improvement and increase in system capacity is obtained with very low spreading factors. Further results are also introduced by considering reduced complexity receivers based on serial layered space-time group multiuser detection, and parallel layered space-time group multiuser detection.     

Blind turbo multiuser detection for long-code multipath CDMA

We consider the problem of demodulating and decoding multiuser information symbols in an uplink asynchronous coded code-division multiple-access (CDMA) system employing long (aperiodic) spreading sequences, in the presence of unknown multipath channels, out-cell multiple-access interference (OMAI), and narrow-band interference (NBI). A blind turbo multiuser receiver, consisting of a novel blind Bayesian multiuser detector and a bank of MAP decoders, is developed for such a system. The effect of OMAI and NBI is modeled as colored Gaussian noise with some unknown covariance matrix. The main contribution of this paper is to develop blind Bayesian multiuser detectors for long-code multipath CDMA systems under both white and colored Gaussian noise. Such detectors are based on the Bayesian inference of all unknown quantities. The Gibbs sampler, a Markov chain Monte Carlo procedure, is then used to calculate the Bayesian estimates of the unknowns. The blind Bayesian multiuser detector computes the a posteriori probabilities of the channel coded symbols, which are differentially encoded before being sent to the channel. Being soft-input soft-output in nature, the proposed blind Bayesian multiuser detectors and the MAP decoders can iteratively exchange the extrinsic information to successively refine the performance, leading to the so-called blind turbo multiuser receiver     

Iterative multiuser detection for CDMA with FEC: near-single-userperformance

This paper introduces an iterative multiuser receiver for direct sequence code-division multiple access (DS-CDMA) with forward error control (FEC) coding. The receiver is derived from the maximum a posteriori (MAP) criterion for the joint received signal, but uses only single-user decoders. Iterations of the system are used to improve performance, with dramatic effects. Single-user turbo code decoders are utilized as the FEC system and a complexity study is presented. Simulation results show that the performance approaches single-user performance even for moderate signal-to-noise ratios     

Blind multiuser detection for V-BLAST coded multicarrier CDMA system

Focusing on the space-time coded multiuser mobile communication systems in the frequencyselective fading environment, this paper proposes a Vertical Bell labs LAyered Space-Time （V-BLAST） coded Multicarrier Code-Division Multiple-Access （MC-CDMA） scheme and its blind channel identification algorithm. This algorithm employs an ESPRIT-like method and the singular value decomposition, and the channels between every transmit antenna of every user and every receive antenna of the base station are blindly estimated with a closed-form solution. Based on it, an equivalent Minimum Mean-Squared Error （MMSE） time-domain multiuser detector is derived. Moreover, the proposed scheme exploits the precoding in the transmitter in order to eliminate the constraint of more receive antennas than transmit ones, required by most conventional V-BLAST codec schemes. Computer simulation results demonstrate the validity of this proposed scheme.     

Antenna-diversity-assisted genetic-algorithm-based multiuser detection schemes for synchronous CDMA systems

A spatial diversity reception assisted multiuser code-division multiple-access detector based on genetic algorithms (GAs) is proposed. Two different GA-based individual-selection strategies are considered. In our first approach, the so-called individuals of the GA are selected for further exploitation, based purely on the sum of their corresponding figures of merit evaluated for the individual antennas. According to our second strategy, the GA's individuals are selected based on the concept of the so-called Pareto optimality, which uses the information from the individual antennas independently. Computer simulations showed that the GAs employing the latter strategy achieve a lower bit-error rate as compared to the former strategy. For a 15-user GA-assisted system employing a spreading factor of 31, a complexity reduction factor of 81 was achieved at a performance identical to that of the optimum multiuser detector using a full search.     

基于CDMA系统的加速功率控制和多用户检测

本文中的算法是交织了一个固定点功率控制算法,该算法是利用以多用户检测MMSE为标准的Aitken's过程加速的.通过应用于MMSE滤波器的扩展Steffensen算法,得自关于Lipshitz常量的一个下限.Lipshitz常量是用来保证所提算法的收敛性.此算法体现了渐进二次收敛,是以牛顿方法为基准.最后给出了仿真结果.     

Iterative multiuser detection for asynchronous CDMA withconcatenated convolutional coding

We propose iterative multiuser detectors for asynchronous code-division multiple-access with parallel-concatenated convolutional codes (turbo codes) and with serially concatenated convolutional codes (SCCC). At each iteration we update and exchange the extrinsic information from the multiuser detector and channel decoders and regenerate soft information between constituent convolutional decoders. Simulation results show that with the proposed structure, near-single-user performance can be achieved. We also propose two reduced-complexity techniques, i.e., the reduced-state iterative multiuser detector based on the T-MAP algorithm and the iterative interference canceler based on a noise-whitening filter. Simulation results show a small performance degradation for these two techniques, particularly for the T-MAP receiver     

Breadth-first maximum likelihood detection in multiuser CDMA

In this letter, we derive a recursive, additive metric for complexity-constrained maximum likelihood detection for multiuser CDMA using breadth-first detection algorithms. The metric requires linear filtering of the matched-filtered received signal vector. It is shown that a class of filters fulfilling certain requirements lead to identical performance     

Space-time multiuser detection in multipath CDMA channels

The problem of multiuser detection in multipath CDMA channels with receiver antenna array is considered. The optimal space-time multiuser receiver structure is first derived, followed by linear space-time multiuser detection methods based on iterative interference cancellation. Blind adaptive space-time multiuser detection techniques are then proposed, which require prior knowledge of only the spreading waveform and the timing of the desired user's signal. Single-user-based space-time processing methods are also considered and are compared with the multiuser approach. It is seen that the proposed multiuser space-time processing techniques offer substantial performance gains over the single-user-based methods, especially in a near-far situation     

Genetic-algorithm-assisted multiuser detection in asynchronous CDMA communications

In an asynchronous direct-sequence code-division multiple-access, a specific bit of the reference user is interfered by two asynchronously arriving surrounding bits of all the other users supported by the system. Hence, for optimum multiuser detection, the entire input bit sequence influencing the current bit decisions must be considered, which results in a high detection delay as well as a high receiver complexity. Suboptimal multiuser-detection methods have been proposed based on a truncated observation window, in which the so-called "edge" bits are tentatively estimated by some other means. Using a similar approach, a multiuser detector is developed in this contribution that invokes genetic algorithms (GAs) in order to estimate both the desired bits as well as the edge bits within the truncated observation window. Using computer simulations, we showed that by employing GAs for improving the estimation reliability of the edge bits, our proposed multiuser detector is capable of achieving a near-optimum bit-error-rate performance, while imposing a lower complexity than the optimum multiuser detector.