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.     

On the macroscopic optimization of multicell wireless systems with multiuser detection and multiple antennas - uplink analysis

In this paper, we consider a system with K single-antenna client users, n/sub B/ base stations (each base station has n/sub R/ antennas), as well as a centralized controller. A client user could be associated with a single base station at any time. All the base stations operate at the same frequency and have optimal multiuser detection per base station which cancels intracell interference only. We consider a general problem of uplink macroscopic resource management where the centralized controller dynamically determines an appropriate association mapping of the K users with respect to the n/sub B/ base stations over a macroscopic time scale. We propose a novel analytical framework for the above macroscopic scheduling problems. A simple rule is to associate a user with the strongest base station (camp-on-the-strongest-cell), and this has been widely employed in conventional cellular systems. However, based on the optimization framework, we found that this conventional approach is in fact not optimal when multiuser detection is employed at the base station. We show that the optimal macroscopic scheduling algorithm is of exponential complexity, and we propose a simple greedy algorithm as a feasible solution.     

The optimality of beamforming in uplink multiuser wireless systems

This paper considers the optimal uplink transmission strategy that achieves the sum-capacity in a multiuser multi-antenna wireless system. Assuming an independent identically distributed block-fading model with transmitter channel side information, beamforming for each remote user is shown to be necessary for achieving sum-capacity when there is a large number of users in the system. This result stands even in the case where each user is equipped with a large number of transmit antennas, and it can be readily extended to channels with intersymbol interference if an orthogonal frequency division multiplexing modulation is assumed. This result is obtained by deriving a rank bound on the transmit covariance matrices, and it suggests that all users should cooperate by each user using only a small portion of available dimensions. Based on the result, a suboptimal transmit scheme is proposed for the situation where only partial channel side information is available at each transmitter. Simulations show that the suboptimal scheme is not only able to achieve a sum rate very close to the capacity, but also insensitive to channel estimation error.     

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     

Timing-free blind multiuser detection in differentially encodedDS/CDMA systems

A timing-free blind multiuser detection technique is proposed for differentially encoded direct-sequence/code division multiple access (DS/CDMA) networks. Unlike previously derived blind multiuser detectors, the proposed algorithm does not rely on any information beyond the spreading code of the desired user, namely neither the complex amplitude nor the symbol timing of the signal of interest is assumed to be known to the receiver. The proposed detector structure is immune to cochannel interferers with arbitrarily large powers, and, as computer simulation results show, compares favorably with competing alternatives. Moreover, the proposed detector achieves performance quite close to that of the ideal minimum mean square error (MMSE) multiuser receiver, which requires knowledge of the spreading codes, timing offsets, and received energies for the signals of all active users     

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.     

Spatio-temporal blind adaptive multiuser detection

We propose blind multiuser detection schemes with antenna arrays, which is based on signal subspace estimation. They are a multichannel extension of the decorrelating and minimum mean-square-error detectors, and therefore they share their immunity to near-far effects. The blind scheme may be seen as an extension of the results in of Wang and Poor (see IEEE Trans. Inform. Theory, vol.44, p.677-90, 1998). However, it is seen that compared with the latter results when spatial diversity is considered, the proposed spatio-temporal detectors offer, with little attendant increase in computational complexity, a better performance. A blind adaptive implementation based on a new orthogonal PAST (projection approximation subspace tracking) algorithm, which is shown to be efficient for subspace tracking, is proposed. Also, we develop a blind estimation of the spatial signature based on the orthogonality between noise and signal subspaces. It is seen that the blind adaptive multiuser detection and blind spatio-temporal signature estimation can he integrated jointly     

A theoretical framework of uplink macroscopic optimization for multicell systems with multiuser detection

In this paper, we consider a system with K client users (single antenna), n/sub B/ base stations (each has single antenna), as well as a centralized controller. All the base stations operate at the same frequency and have optimal multiuser detection (MUD) per base station. The MUD at the base station is able to cancel only the intracell interference but not the intercell interference. A client user is associated with a single base station at any time. We consider a general problem of uplink macroscopic optimization (or macroscopic resource management) where the centralized controller dynamically determines an appropriate association mapping of the K users with respect to the n/sub B/ base stations over a macroscopic time scale. We propose a novel multicell capacity region as well as an analytical framework for the above macroscopic optimization problem. A simple conventional rule is to associate a user with the strongest base station (camp-on-the-strongest-cell) and this has been widely employed in conventional cellular systems. However, based on the optimization framework, we found that this conventional approach is in fact not optimal when MUD is employed at the base station. We show that the optimal macroscopic optimization algorithm is of exponential complexity and we propose a simple greedy algorithm as a feasible solution. It is shown that the macroscopic optimization gain over the conventional approach increases with decreasing path loss exponent due to large area of overlapping.     

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     

User selection for SINR-based uplink multiuser MIMO systems

To avoid the exhaustive search, we propose a fast user selection algorithm for Signal-to-Interference-plus-Noise-Ratio (SINR)-based multiuser Multiple-Input Multiple-Output (MIMO) systems with Alamouti Space-Time Block Code (STBC) transmit scheme. A locally optimal selection criterion is proposed at first. Then, the incremental selection approach is applied, which selects one among the residual available users to maximize the minimum user SINR step by step. Simulation results show that the fast algorithm ga...     

Distributed closed-loop spatial multiplexing for uplink multiuser systems

Focusing on the uplink, where mobile users (each with a single transmit antenna) communicate with a base station with multiple antennas, we treat multiple users as antennas to enable spatial multiplexing across users. Introducing distributed closed-loop spatial multiplexing with threshold-based user selection, we propose two uplink channel-assigning strategies with limited feedback. We prove that the proposed system also outperforms the standard greedy scheme with respect to the degree of fairness, measured by the variance of the time averaged throughput. For uplink multi-antenna systems, we show that the proposed scheduling is a better choice than the greedy scheme in terms of the average BER, feedback complexity, and fairness. The numerical results corroborate our findings.     

All-digital impulse radio with multiuser detection for wireless cellular systems

Impulse radio is an ultrawideband system with attractive features for baseband asynchronous multiple-access, multimedia services, and tactical wireless communications. Implemented with analog components, the continuous-time impulse radio multiple-access model utilizes pulse-position modulation and random time-hopping codes to alleviate multipath effects and suppress multiuser interference. We introduce a novel continuous-time impulse radio transmitter model and deduce from it an approximate one with lower complexity. We also develop a time-division duplex access protocol along with orthogonal user codes to enable impulse radio as a radio link for wireless cellular systems. Relying on this protocol, we then derive a multiple-input/multiple-output equivalent model for full continuous-time model and a single-input/single-output model, for the approximate one. Based on these models, we finally develop design composite linear/nonlinear receivers for the downlink. The linear step eliminates multiuser interference deterministically and accounts for frequency-selective multipath while a maximum-likelihood receiver performs symbol detection. Simulations are provided to compare performance of the different receivers.     

ADAPTIVE STEP－SIZE CONSTANT MODULUS ALGORITHM FOR BLIND MULTIUSER DETECTION IN DS－CDMA SYSTEMS

Blind Adaptive Step-size Constant Modulus Algorithm (AS-CMA) for multiuser detection in DS-CDMA systems is presented.It combines the CMA and the concept of variable step-size,uses a second LMS algorithm for the step size.It adjusts the step-size according to the minimum output-energy principle within a specified range,thus overcomes the problems of bad effect of fixed step-size LMS algorithm.Compared with Adaptive Step-size LMS (AS-LMS) algorithm,through simulations,this algorithm can adapt the changes of the environment,suppress multiple access interference in the dynamic environment and the stability of Signal to Interference Ratio (SIR) is superior to that of AS-LMS.     

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.     

Smart antennas for broadband wireless access networks

This article is an overview of smart antenna applications in fixed broadband wireless access networks. Different smart antenna techniques are described including advances such as “spatial multiplexing” that can dramatically increase the performance of BWA networks. The impact of SA techniques on capacity and throughput of BWA networks is discussed     

Blind adaptive receiver for uplink multiuser massive MIMO systems

Herein, we consider uplink multiuser massive multiple‐input multiple‐output systems when multiple users transmit information symbols to a base station (BS) by applying simple space‐time block coding (STBC). At the BS receiver, two detection filters for each user are used to detect the STBC information symbols. One of these filters is for odd‐indexed symbols and the other for even‐indexed symbols. Using constrained output variance metric minimization, we first derive a special relation between the closed‐form optimal solutions for the two detection filters. Then, using the derived special relation, we propose a new blind adaptive algorithm for implementing the minimum output variance‐based optimal filters. In the proposed adaptive algorithm, filter weight vectors are updated only in the region satisfying the special relation. Through a theoretical analysis of the convergence speed and a computer simulation, we demonstrate that the proposed scheme exhibits faster convergence speed and lower steady‐state bit error rate than the conventional scheme.     

On the capacity of multiuser wireless channels with multiple antennas

The advantages of multiuser communication, where many users are allowed to simultaneously transmit or receive in a common bandwidth, are considered for multiple-antenna systems in a high signal-to-noise ratio (SNR) regime. Assuming channel state information at receiver (CSIR) to be available, the ergodic capacity is characterized for both unbiased and biased channels, and the quantitative capacity gain of a multiple-antenna multiuser system is analyzed for multiple-access channels. For highly biased (correlated) channels, a multiuser system is shown to be inherently superior to a single-user system (a time- or frequency-division multiple-access (TDMA or FDMA) based system) due to the underlying multiuser diversity, and the sum capacity is shown to scale linearly with the number of antennas. For unbiased channels, the characteristics of ergodic capacity are shown to transfer to outage capacity when a large degree of space diversity exists, and to deterministic capacity when the number of receive antennas is large. Also, a brief discussion on the multiuser multiple-antenna communication in broadcast channel is provided.     

PARAFAC-based unified tensor modeling for wireless communication systems with application to blind multiuser equalization

In some antenna array-based wireless communication systems the received signal is multidimensional and can be treated as a tensor (3D array) instead of a matrix (2D array). In this paper, we make use of a generalized tensor decomposition known as constrained Block-PARAFAC and propose a tensor (3D) model for the signal received by three types of wireless communication systems. The considered wireless communication systems are multiuser systems subject to frequency-selective multipath and employing multiple receiver antennas together with (i) oversampling or (ii) direct-sequence spreading or (iii) multicarrier modulation. The proposed modeling approach aims at unifying the received signal model of these systems into a single PARAFAC model. We show that the proposed model has a constrained structure, where model constraints and associated dimensions depend on each particular system. The proposed constrained Block-PARAFAC model is demonstrated by expanding the tensor using Kronecker products of canonical vectors. As an application of this model to tensor signal processing, a new tensor-based receiver is proposed for blind multiuser equalization, which combines PARAFAC-based modeling with a subspace method. Simulation results are presented to illustrate the performance of the proposed blind receiver.     

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.     

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 Inde-pendent 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 se-quence 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 subopti-mum blind adaptive multiuser detection algorithm of excellent near-far resistance and low complexity.