Constant modulus based blind adaptive multiuser detection.

Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2004.Signal processing techniques such as multi user detection (MUD) have the capability of greatly enhancing the performance and capacity of future generation wireless communications systems. Blind adaptive MUD's have many favourable qualities and their application to OS-COMA systems has attracted a lot of attention. The constant modulus algorithm is widely deployed in blind channel equalizations applications. The central premise of this thesis is that the constant modulus cost function is very suitable for the purposes of blind adaptive MUD for future generation wireless communications systems. To prove this point, the adaptive performance of blind (and non-blind) adaptive MUD's is derived analytically for all the schemes that can be made to fit the same generic structure as the constant modulus scheme. For the first time, both the relative and absolute performance levels of the different adaptive algorithms are computed, which gives insights into the performance levels of the different blind adaptive MUD schemes, and demonstrates the merit of the constant modulus based schemes. The adaptive performance of the blind adaptive MUD's is quantified using the excess mean square error (EMSE) as a metric, and is derived for the steady-state, tracking, and transient stages of the adaptive algorithms. If constant modulus based MUD's are suitable for future generation wireless communications systems, then they should also be capable of suppressing multi-rate DS-COMA interference and also demonstrate the ability to suppress narrow band interference (NBI) that arises in overlay systems. Multi-rate DS-COMA provides the capability of transmitting at various bit rates and quality of service levels over the same air interface. Limited spectrum availability may lead to the implementation of overlay systems whereby wide-band COMA signal are collocated with existing narrow band services. Both overlay systems and multi-rate DS-COMA are important features of future generation wireless communications systems. The interference patterns generated by both multi-rate OS-COMA and digital NBI are cyclostationary (or periodically time varying) and traditional MUD techniques do not take this into account and are thus suboptimal. Cyclic MUD's, although suboptimal, do however take the cyclostationarity of the interference into account, but to date there have been no cyclic MUD's based on the constant modulus cost function proposed. This thesis thus derives novel, blind adaptive, cyclic MUD's based on the constant modulus cost function, for direct implementation on the FREquency SHift (FRESH) filter architecture. The FRESH architecture provides a modular and thus flexible implementation (in terms of computational complexity) of a periodically time varying filter. The operation of the blind adaptive MUD on these reduced complexity architectures is also explored.· The robustness of the new cyclic MUD is proven via a rigorous mathematical proof. An alternate architecture to the FRESH filter is the filter bank. Using the previously derived analytical framework for the adaptive performance of MUD's, the relative performance of the adaptive algorithms on the FRESH and filter bank architectures is examined. Prior to this thesis, no conclusions could be drawn as to which architecture would yield superior performance. The performance analysis of the adaptive algorithms is also extended in this thesis in order to consider the effects of timing jitrer at the receiver, signature waveform mismatch, and other pertinent issues that arise in realistic implementation scenarios. Thus, through a careful analytical approach, which is verified by computer simulation results, the suitability of constant modulus based MUD's is established in this thesis

Linear MMSE Receivers for Interference Suppression & Multipath Diversity Combining in Long-Code DS-CDMA Systems

This thesis studies the design and implementation of a linear minimum mean-square error (LMMSE) receiver in asynchronous bandlimited direct-sequence code-division multiple-access (DS-CDMA) systems that employ long-code pseudo-noise (PN) sequences and operate in multipath environments. The receiver is shown to be capable of multiple-access interference (MAI) suppression and multipath diversity combining without the knowledge of other users' signature sequences. It outperforms any other linear receiver by maximizing output signal-to-noise ratio (SNR) with the aid of a new chip filter which exploits the cyclostationarity of the received signal and combines all paths of the desired user that fall within its supported time span. This work is motivated by the shortcomings of existing LMMSE receivers which are either incompatible with long-code CDMA or constrained by limitations in the system model. The design methodology is based on the concept of linear/conjugate linear (LCL) filtering and satisfying the orthogonality conditions to achieve the LMMSE filter response. Moreover, the proposed LMMSE receiver addresses two drawbacks of the coherent Rake receiver, the industry's current solution for multipath reception. First, unlike the Rake receiver which uses the chip-matched filter (CMF) and treats interference as additive white Gaussian noise (AWGN), the LMMSE receiver suppresses interference by replacing the CMF with a new chip pulse filter. Second, in contrast to the Rake receiver which only processes a subset of strongest paths of the desired user, the LMMSE receiver harnesses the energy of all paths of the desired user that fall within its time support, at no additional complexity. The performance of the proposed LMMSE receiver is analyzed and compared with that of the coherent Rake receiver with probability of bit error, Pe, as the figure of merit. The analysis is based on the accurate improved Gaussian approximation (IGA) technique. Closed form conditional Pe expressions for both the LMMSE and Rake receivers are derived. Furthermore, it is shown that if quadriphase random spreading, moderate to large spreading factors, and pulses with small excess bandwidth are used, the widely-used standard Gaussian Approximation (SGA) technique becomes accurate even for low regions of Pe. Under the examined scenarios tailored towards current narrowband system settings, the LMMSE receiver achieves 60% gain in capacity (1. 8 dB in output SNR) over the selective Rake receiver. A third of the gain is due to interference suppression capability of the receiver while the rest is credited to its ability to collect the energy of the desired user diversified to many paths. Future wideband systems will yield an ever larger gain. Adaptive implementations of the LMMSE receiver are proposed to rid the receiver from dependence on the knowledge of multipath parameters. The adaptive receiver is based on a fractionally-spaced equalizer (FSE) whose taps are updated by an adaptive algorithm. Training-based, pilot-channel-aided (PCA), and blind algorithms are developed to make the receiver applicable to both forward and reverse links, with or without the presence of pilot signals. The blind algorithms are modified versions of the constant modulus algorithm (CMA) which has not been previously studied for long-code CDMA systems. Extensive simulation results are presented to illustrate the convergence behavior of the proposed algorithms and quantify their performance loss under various levels of MAI. Computational complexities of the algorithms are also discussed. These three criteria (performance loss, convergence rate, and computational complexity) determine the proper choice of an adaptive algorithm with respect to the requirements of the specific application in mind

High Capacity CDMA and Collaborative Techniques

The thesis investigates new approaches to increase the user capacity and improve the error performance of Code Division Multiple Access (CDMA) by employing adaptive interference cancellation and collaborative spreading and space diversity techniques. Collaborative Coding Multiple Access (CCMA) is also investigated as a separate technique and combined with CDMA. The advantages and shortcomings of CDMA and CCMA are analysed and new techniques for both the uplink and downlink are proposed and evaluated. Multiple access interference (MAI) problem in the uplink of CDMA is investigated first. The practical issues of multiuser detection (MUD) techniques are reviewed and a novel blind adaptive approach to interference cancellation (IC) is proposed. It exploits the constant modulus (CM) property of digital signals to blindly suppress interference during the despreading process and obtain amplitude estimation with minimum mean squared error for use in cancellation stages. Two new blind adaptive receiver designs employing successive and parallel interference cancellation architectures using the CM algorithm (CMA) referred to as ‘CMA-SIC’ and ‘BA-PIC’, respectively, are presented. These techniques have shown to offer near single user performance for large number of users. It is shown to increase the user capacity by approximately two fold compared with conventional IC receivers. The spectral efficiency analysis of the techniques based on output signal-to interference-and-noise ratio (SINR) also shows significant gain in data rate. Furthermore, an effective and low complexity blind adaptive subcarrier combining (BASC) technique using a simple gradient descent based algorithm is proposed for Multicarrier-CDMA. It suppresses MAI without any knowledge of channel amplitudes and allows large number of users compared with equal gain and maximum ratio combining techniques normally used in practice. New user collaborative schemes are proposed and analysed theoretically and by simulations in different channel conditions to achieve spatial diversity for uplink of CCMA and CDMA. First, a simple transmitter diversity and its equivalent user collaborative diversity techniques for CCMA are designed and analysed. Next, a new user collaborative scheme with successive interference cancellation for uplink of CDMA referred to as collaborative SIC (C-SIC) is investigated to reduce MAI and achieve improved diversity. To further improve the performance of C-SIC under high system loading conditions, Collaborative Blind Adaptive SIC (C-BASIC) scheme is proposed. It is shown to minimize the residual MAI, leading to improved user capacity and a more robust system. It is known that collaborative diversity schemes incur loss in throughput due to the need of orthogonal time/frequency slots for relaying source’s data. To address this problem, finally a novel near-unity-rate scheme also referred to as bandwidth efficient collaborative diversity (BECD) is proposed and evaluated for CDMA. Under this scheme, pairs of users share a single spreading sequence to exchange and forward their data employing a simple superposition or space-time encoding methods. At the receiver collaborative joint detection is performed to separate each paired users’ data. It is shown that the scheme can achieve full diversity gain at no extra bandwidth as inter-user channel SNR becomes high. A novel approach of ‘User Collaboration’ is introduced to increase the user capacity of CDMA for both the downlink and uplink. First, collaborative group spreading technique for the downlink of overloaded CDMA system is introduced. It allows the sharing of the same single spreading sequence for more than one user belonging to the same group. This technique is referred to as Collaborative Spreading CDMA downlink (CS-CDMA-DL). In this technique T-user collaborative coding is used for each group to form a composite codeword signal of the users and then a single orthogonal sequence is used for the group. At each user’s receiver, decoding of composite codeword is carried out to extract the user’s own information while maintaining a high SINR performance. To improve the bit error performance of CS-CDMA-DL in Rayleigh fading conditions, Collaborative Space-time Spreading (C-STS) technique is proposed by combining the collaborative coding multiple access and space-time coding principles. A new scheme for uplink of CDMA using the ‘User Collaboration’ approach, referred to as CS-CDMA-UL is presented next. When users’ channels are independent (uncorrelated), significantly higher user capacity can be achieved by grouping multiple users to share the same spreading sequence and performing MUD on per group basis followed by a low complexity ML decoding at the receiver. This approach has shown to support much higher number of users than the available sequences while also maintaining the low receiver complexity. For improved performance under highly correlated channel conditions, T-user collaborative coding is also investigated within the CS-CDMA-UL system

Reduced Complexity Sequential Monte Carlo Algorithms for Blind Receivers

Monte Carlo algorithms can be used to estimate the state of a system given relative observations. In this dissertation, these algorithms are applied to physical layer communications system models to estimate channel state information, to obtain soft information about transmitted symbols or multiple access interference, or to obtain estimates of all of these by joint estimation. Initially, we develop and analyze a multiple access technique utilizing mutually orthogonal complementary sets (MOCS) of sequences. These codes deliberately introduce inter-chip interference, which is naturally eliminated during processing at the receiver. However, channel impairments can destroy their orthogonality properties and additional processing becomes necessary. We utilize Monte Carlo algorithms to perform joint channel and symbol estimation for systems utilizing MOCS sequences as spreading codes. We apply Rao-Blackwellization to reduce the required number of particles. However, dense signaling constellations, multiuser environments, and the interchannel interference introduced by the spreading codes all increase the dimensionality of the symbol state space significantly. A full maximum likelihood solution is computationally expensive and generally not practical. However, obtaining the optimum solution is critical, and looking at only a part of the symbol space is generally not a good solution. We have sought algorithms that would guarantee that the correct transmitted symbol is considered, while only sampling a portion of the full symbol space. The performance of the proposed method is comparable to the Maximum Likelihood (ML) algorithm. While the computational complexity of ML increases exponentially with the dimensionality of the problem, the complexity of our approach increases only quadratically. Markovian structures such as the one imposed by MOCS spreading sequences can be seen in other physical layer structures as well. We have applied this partitioning approach with some modification to blind equalization of frequency selective fading channel and to multiple-input multiple output receivers that track channel changes. Additionally, we develop a method that obtains a metric for quantifying the convergence rate of Monte Carlo algorithms. Our approach yields an eigenvalue based method that is useful in identifying sources of slow convergence and estimation inaccuracy.Ph.D.Committee Chair: Douglas B. Williams; Committee Member: Brani Vidakovic; Committee Member: G. Tong zhou; Committee Member: Gordon Stuber; Committee Member: James H. McClella

An Optimization Theoretical Framework for Resource Allocation over Wireless Networks

With the advancement of wireless technologies, wireless networking has become ubiquitous owing to the great demand of pervasive mobile applications. Some fundamental challenges exist for the next generation wireless network design such as time varying nature of wireless channels, co-channel interferences, provisioning of heterogeneous type of services, etc. So how to overcome these difficulties and improve the system performance have become an important research topic. Dynamic resource allocation is a general strategy to control the interferences and enhance the performance of wireless networks. The basic idea behind dynamic resource allocation is to utilize the channel more efficiently by sharing the spectrum and reducing interference through optimizing parameters such as the transmitting power, symbol transmission rate, modulation scheme, coding scheme, bandwidth, etc. Moreover, the network performance can be further improved by introducing diversity, such as multiuser, time, frequency, and space diversity. In addition, cross layer approach for resource allocation can provide advantages such as low overhead, more efficiency, and direct end-to-end QoS provision. The designers for next generation wireless networks face the common problem of how to optimize the system objective under the user Quality of Service (QoS) constraint. There is a need of unified but general optimization framework for resource allocation to allow taking into account a diverse set of objective functions with various QoS requirements, while considering all kinds of diversity and cross layer approach. We propose an optimization theoretical framework for resource allocation and apply these ideas to different network situations such as: 1.Centralized resource allocation with fairness constraint 2.Distributed resource allocation using game theory 3.OFDMA resource allocation 4.Cross layer approach On the whole, we develop a universal view of the whole wireless networks from multiple dimensions: time, frequency, space, user, and layers. We develop some schemes to fully utilize the resources. The success of the proposed research will significantly improve the way how to design and analyze resource allocation over wireless networks. In addition, the cross-layer optimization nature of the problem provides an innovative insight into vertical integration of wireless networks