Optimum Asymptotic Multiuser Efficiency of Pseudo-Orthogonal Randomly Spread CDMA

A $K$-user pseudo-orthogonal (PO) randomly spread CDMA system, equivalent to transmission over a subset of $K'\leq K$ single-user Gaussian channels, is introduced. The high signal-to-noise ratio performance of the PO-CDMA is analyzed by rigorously deriving its asymptotic multiuser efficiency (AME) in the large system limit. Interestingly, the $K'$-optimized PO-CDMA transceiver scheme yields an AME which is practically equal to 1 for system loads smaller than 0.1 and lower bounded by 1/4 for increasing loads. As opposed to the vanishing efficiency of linear multiuser detectors, the derived efficiency is comparable to the ultimate CDMA efficiency achieved for the intractable optimal multiuser detector.Comment: WIC 27th Symposium on Information Theory in the Benelux, 200

Multiuser detection in CDMA using blind techniques

Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2004Includes bibliographical references (leaves: 63-65)Text in English; Abstract: Turkish and Englishxiv, 69 leavesIn code division multiple access (CDMA) systems, blind multiuser detection (MUD) techniques are of great importance, especially for downlinks, since in practice, it may be unrealistic for a mobile user to know the spreading codes of other active users in the channel. Furthermore, blind methods remove the need for training sequences which leads to a gain in the channel bandwidth. Subspace concept in blind MUD is an alternative process to classical and batch blind MUD techniques based on principle component analysis, or independent component analysis (ICA) and ICA-like algorithms, such as joint approximate diagonalization of eigen-matrices (JADE), blind source separation algorithm with reference system, etc. Briefly, the desired signal is searched in the signal subspace instead of the whole space, in this type of detectors. A variation of the subspace-based MUD is reduced-rank MUD in which a smaller subspace of the signal subspace is tracked where the desired signal is contained in. This latter method leads to a performance gain compared to a standard subspace method. In this thesis, blind signal subspace and reduced-rank MUD techniques are investigated, and applied to minimum mean square error (MMSE) detectors with two different iterative subspace tracking algorithms. The performances of these detectors are compared in different scenarios for additive white Gaussian noise and for multipath fading channels as well. With simulation results the superiority of the reduced-rank detector to the signal subspace detector is shown. Additionally, as a new remark for both detectors, it is shown that, using minimum description length criterion in subspace tracking algorithm results in an increase in rank-tracking ability and correspondingly in the final performance. Finally, the performances of these two detectors are compared with MMSE, adaptive MMSE and JADE detectors

Interference suppression and diversity for CDMA systems

In code-division multiple-access (CDMA) systems, due to non-orthogonality of the spreading codes and multipath channels, the desired signal suffers interference from other users. Signal fading due to multipath propagation is another source of impairment in wireless CDMA systems, often severely impacting performance. In this dissertation, reduced-rank minimum mean square error (MMSE) receiver and reduced-rank minimum variance receiver are investigated to suppress interference; transmit diversity is applied to multicarrier CDMA (MC-CDMA) systems to combat fading; packet combing is studied to provide both interference suppression and diversity for CDMA random access systems. The reduced-rank MMSE receiver that uses a reduced-rank estimated covariance matrix is studied to improve the performance of MMSE receiver in CDMA systems. It is shown that the reduced-rank MMSE receiver has much better performance than the full-rank MMSE receiver when the covariance matrix is estimated by using a finite number of data samples and the desired signal is in a low dimensional subspace. It is also demonstrated that the reduced-rank minimum variance receiver outperforms the full-rank minimum variance receiver. The probability density function of the output SNR of the full-rank and reduced-rank linear MMSE estimators is derived for a general linear signal model under the assumption that the signals and noise are Gaussian distributed. Space-time coding that is originally proposed for narrow band systems is applied to an MC-CDMA system in order to get transmit diversity for such a wideband system. Some techniques to jointly decode the space-time code and suppress interference are developed. The channel estimation using either pilot channels or pilot symbols is studied for MC-CDMA systems with space-time coding. Performance of CDMA random access systems with packet combining in fading channels is analyzed. By combining the current retransmitted packet with all its previous transmitted copies, the receiver obtains a diversity gain plus an increased interference and noise suppression gain. Therefore, the bit error rate dramatically decreases with the number of transmissions increasing, which in turn improves the system throughput and reduces the average delay

Spatial filtering for pilot-aided WCDMA systems: a semi-blind subspace approach

This paper proposes a spatial filtering technique for the reception of pilot-aided multirate multicode direct-sequence code division multiple access (DS/CDMA) systems such as wideband CDMA (WCDMA). These systems introduce a code-multiplexed pilot sequence that can be used for the estimation of the filter weights, but the presence of the traffic signal (transmitted at the same time as the pilot sequence) corrupts that estimation and degrades the performance of the filter significantly. This is caused by the fact that although the traffic and pilot signals are usually designed to be orthogonal, the frequency selectivity of the channel degrades this orthogonality at hte receiving end. Here, we propose a semi-blind technique that eliminates the self-noise caused by the code-multiplexing of the pilot. We derive analytically the asymptotic performance of both the training-only and the semi-blind techniques and compare them with the actual simulated performance. It is shown, both analytically and via simulation, that high gains can be achieved with respect to training-onlybased techniques.Peer Reviewe

Multiuser detection employing recurrent neural networks for DS-CDMA systems.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, 2006.Over the last decade, access to personal wireless communication networks has evolved to a point of necessity. Attached to the phenomenal growth of the telecommunications industry in recent times is an escalating demand for higher data rates and efficient spectrum utilization. This demand is fuelling the advancement of third generation (3G), as well as future, wireless networks. Current 3G technologies are adding a dimension of mobility to services that have become an integral part of modem everyday life. Wideband code division multiple access (WCDMA) is the standardized multiple access scheme for 3G Universal Mobile Telecommunication System (UMTS). As an air interface solution, CDMA has received considerable interest over the past two decades and a great deal of current research is concerned with improving the application of CDMA in 3G systems. A factoring component of CDMA is multiuser detection (MUD), which is aimed at enhancing system capacity and performance, by optimally demodulating multiple interfering signals that overlap in time and frequency. This is a major research problem in multipoint-to-point communications. Due to the complexity associated with optimal maximum likelihood detection, many different sub-optimal solutions have been proposed. This focus of this dissertation is the application of neural networks for MUD, in a direct sequence CDMA (DS-CDMA) system. Specifically, it explores how the Hopfield recurrent neural network (RNN) can be employed to give yet another suboptimal solution to the optimization problem of MUD. There is great scope for neural networks in fields encompassing communications. This is primarily attributed to their non-linearity, adaptivity and key function as data classifiers. In the context of optimum multiuser detection, neural networks have been successfully employed to solve similar combinatorial optimization problems. The concepts of CDMA and MUD are discussed. The use of a vector-valued transmission model for DS-CDMA is illustrated, and common linear sub-optimal MUD schemes, as well as the maximum likelihood criterion, are reviewed. The performance of these sub-optimal MUD schemes is demonstrated. The Hopfield neural network (HNN) for combinatorial optimization is discussed. Basic concepts and techniques related to the field of statistical mechanics are introduced and it is shown how they may be employed to analyze neural classification. Stochastic techniques are considered in the context of improving the performance of the HNN. A neural-based receiver, which employs a stochastic HNN and a simulated annealing technique, is proposed. Its performance is analyzed in a communication channel that is affected by additive white Gaussian noise (AWGN) by way of simulation. The performance of the proposed scheme is compared to that of the single-user matched filter, linear decorrelating and minimum mean-square error detectors, as well as the classical HNN and the stochastic Hopfield network (SHN) detectors. Concluding, the feasibility of neural networks (in this case the HNN) for MUD in a DS-CDMA system is explored by quantifying the relative performance of the proposed model using simulation results and in view of implementation issues

Multi-user detection for multi-rate DS/CDMA systems

Wireless cellular communication is witnessing a rapid growth in market, technology and range of services. Current and future demands for wireless communication services motivate the need for handling multi-media traffic types. In a multimedia communication system, users with different and even time-varying rates and quality of services (QoS) requirements, such as voice, image and data, must be accommodated. The use of Spread Spectrum modulation with Code Division Multiple Access (CDMA) technology is an attractive approach for economical spectrally efficient and high quality cellular and personal communication services. This dissertation explores the technologies of applying different interference cancellation techniques to multi-rate CDMA systems that serve users with different QoS. Multiple Access Interference (MAI) and multipath propagation are the major issues in wireless communication systems. It is also true for multi-rate CDMA systems. Multi-user detection has been shown to be effective in combating the near-far problem and providing superior performance over conventional detection method. In this dissertation, we combine both linear minimum mean squared error (LMMSE) detector, nonlinear decision feedback detector, with other signal processing techniques, such as array processing and multipath combining, to create effective near-far resistant detectors for multi-rate CDMA systems. Firstly, we propose MMSE receivers for synchronous multi-rate CDMA system and compare the performance with the corresponding multi-rate decorrelating detectors. The multi-rate decorrelating detector is optimally near-far resistant and easy to implement. The proposed linear MMSE multi-rate receiver can be adaptively implemented only with the knowledge of the desired user. Due to the fact that MMSE detector offers best trade-off between the MAI cancellation and noise variance enhancement, it is shown that multi-rate MMSE receiver can offer better performance than the multi-rate decorrelator when the interfering users\u27 Signal to Noise Ratio (SNR) is relatively low comparing to the desired user\u27s SNR. Secondly, the asynchronous multi-rate CDMA system, we propose multi-rate multi-shoot decorrelating detectors and multi-rate multi-shot MMSE detectors. The performance of multi-shot detectors can be improved monotonically with increasing the number of stacked bits, but a great computational complexity is going to be introduced in order to get better performance. A debiasing method is introduced to multi-rate multi-shot linear detectors. Debiasing method optimizes multi-rate detectors based on the multi-rate multi-shot model. Debiasing multi-shot MMSE detector for multi-rate signals can offer performance than the corresponding debiasing multi-shot decorrelating detector. Thirdly, we propose linear space-time receivers for multi-rate CDMA systems. The minimum mean-squared error criteria is used. We perform a comparative study on the multi-rate receiver which uses either multipath (temporal) processing or array (spatial) processing, and the one which uses both array and multipath (space-time) processing. The space-time receiver for the multi-rate CDMA signals give us the potential of improving the capacity of multi-rate systems. The space-time processing combined with multiuser detection have the advantages of combating multipath fading through temporal processing, reducing MAI through MMSE method and provide antenna or diversity gain through spatial processing and increasing the capacity of the multi-rate CDMA systems. Lastly, the group-wise interference cancellation methods are proposed for multi-rate CDMA signals. The non-linear decision feedback detection (DFD) schemes are used in the proposed receivers. The proposed interference cancellation schemes benefit from the nature of the unequal received amplitudes for multi-rate CDMA signals. Users with same data rate are grouped together. Users with the highest data-rate are detected first. Interference between the groups is cancelled in a successive order. The results show that the group-wise MMSE DFD yields better performance than multi-rate linear MMSE detector and multi-rate decorrelating detector, especially for highly loaded CDMA systems