Code-timing synchronization in DS-CDMA systems using space-time diversity

The synchronization of a desired user transmitting a known training sequence in a direct-sequence (DS) asynchronous code-division multiple-access (CDMA) sys-tem is addressed. It is assumed that the receiver consists of an arbitrary antenna array and works in a near-far, frequency-nonselective, slowly fading channel. The estimator that we propose is derived by applying the maximum likelihood (ML) principle to a signal model in which the contribution of all the interfering compo-nents (e.g., multiple-access interference, external interference and noise) is modeled as a Gaussian term with an unknown and arbitrary space-time correlation matrix. The main contribution of this paper is the fact that the estimator makes eÆcient use of the structure of the signals in both the space and time domains. Its perfor-mance is compared with the Cramer-Rao Bound, and with the performance of other methods proposed recently that also employ an antenna array but only exploit the structure of the signals in one of the two domains, while using the other simply as a means of path diversity. It is shown that the use of the temporal and spatial structures is necessary to achieve synchronization in heavily loaded systems or in the presence of directional external interference.Peer ReviewedPostprint (published version

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 estimation with applications to blind multiple-access communication over fading channels

Includes bibliographical references.We consider the detection of nonorthogonal multipulse signals on multiple-access fading channels. The generalized maximum-likelihood rule is employed to decode users whose complex fading gains are unknown. We develop geometrical interpretations for the resulting detectors and their corresponding asymptotic efficiencies. The generalized maximum-likelihood detection rule is then applied to find a matched subspace detector for the frequency-selective fading channel, under the assumption of a short coherence time (or long coherence time without the computational power to track the fading parameters). We propose blind implementations of these detectors for nonorthogonal multipulse signaling on both frequency-nonselective and frequency-selective multiple-access fading channels. These blind detectors extend the results of Wang and Poor to multipulse modulation and fast frequency selective fading. For comparison, the minimum mean-squared error decision rules for these channels are derived and blind implementations of their corresponding detectors are developed.This work was supported by the National Science Foundation under Contract ECS 9979400 and by the Office of Naval Research under Contracts N00014-89-J-1070 and N0014-00-1-0033

Blind adaptive near-far resistant receivers for DS/CDMA multi-user communication systems

Code-division multiple-access (CDMA) systems have multiple users that simultaneously share a common channel using pre-assigned signature waveforms. The conventional receiver suffers from the near-far problem when the received signal power of the desired user is weaker than those of the other users. Optimum and suboptimum multi-user detectors outperform the conventional receiver at the expense of a significant increase in complexity and need for side-information about interfering users. Complexity of these detectors may not be acceptable for many practical applications and communication security may restrict the distribution of all users\u27 signature waveforms to all the receivers;For a single-user receiver, the multi-user detection problem is viewed as an interference suppression problem. This dissertation presents a cost-constraint strategy to implement adaptive single-user receivers that suppress the multiple-access interference without using training sequences. A constrained LMS algorithm that converges to a near-optimum solution by using the received signal and some known properties of the desired signal is developed. The constrained LMS receiver is useful for static CDMA detection where the channel accessed by the desired user is time-invariant. The dissertation also develops an adaptive space-alternating generalized EM (SAGE) algorithm. This algorithm jointly updates estimates of filter weights and adaptive reference signal in a sequential manner. The SAGE receiver out-performs the existing: blind receiver that employ the constrained output-power-minimizing algorithm while using the same amount of information. The SAGE receiver is applicable to dynamic CDMA detection where the channel accessed by the desired user is time-varying. The dissertation further generalizes the adaptive SAGE algorithm to an adaptive space-alternating generalized projection (SAGP) algorithm that uses the same amount of information as in the conventional receiver;Proposed receivers are tested by simulations and compared with the existing receivers that use the same amount of information. Throughout the analytical analysis and simulations of the proposed receivers, the dissertation shows that, for realistic CDMA communications, achieving both the near-far resistance and the near-optimum performance is possible with the same or similar information required by the conventional receiver

Blind source separation for interference cancellation in CDMA systems

Communication is the science of "reliable" transfer of information between two parties, in the sense that the information reaches the intended party with as few errors as possible. Modern wireless systems have many interfering sources that hinder reliable communication. The performance of receivers severely deteriorates in the presence of unknown or unaccounted interference. The goal of a receiver is then to combat these sources of interference in a robust manner while trying to optimize the trade-off between gain and computational complexity. Conventional methods mitigate these sources of interference by taking into account all available information and at times seeking additional information e.g., channel characteristics, direction of arrival, etc. This usually costs bandwidth. This thesis examines the issue of developing mitigating algorithms that utilize as little as possible or no prior information about the nature of the interference. These methods are either semi-blind, in the former case, or blind in the latter case. Blind source separation (BSS) involves solving a source separation problem with very little prior information. A popular framework for solving the BSS problem is independent component analysis (ICA). This thesis combines techniques of ICA with conventional signal detection to cancel out unaccounted sources of interference. Combining an ICA element to standard techniques enables a robust and computationally efficient structure. This thesis proposes switching techniques based on BSS/ICA effectively to combat interference. Additionally, a structure based on a generalized framework termed as denoising source separation (DSS) is presented. In cases where more information is known about the nature of interference, it is natural to incorporate this knowledge in the separation process, so finally this thesis looks at the issue of using some prior knowledge in these techniques. In the simple case, the advantage of using priors should at least lead to faster algorithms.reviewe

Proceedings of the Fifth International Mobile Satellite Conference 1997

Satellite-based mobile communications systems provide voice and data communications to users over a vast geographic area. The users may communicate via mobile or hand-held terminals, which may also provide access to terrestrial communications services. While previous International Mobile Satellite Conferences have concentrated on technical advances and the increasing worldwide commercial activities, this conference focuses on the next generation of mobile satellite services. The approximately 80 papers included here cover sessions in the following areas: networking and protocols; code division multiple access technologies; demand, economics and technology issues; current and planned systems; propagation; terminal technology; modulation and coding advances; spacecraft technology; advanced systems; and applications and experiments

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

MIMO signal processing in offset-QAM based filter bank multicarrier systems

Next-generation communication systems have to comply with very strict requirements for increased flexibility in heterogeneous environments, high spectral efficiency, and agility of carrier aggregation. This fact motivates research in advanced multicarrier modulation (MCM) schemes, such as filter bank-based multicarrier (FBMC) modulation. This paper focuses on the offset quadrature amplitude modulation (OQAM)-based FBMC variant, known as FBMC/OQAM, which presents outstanding spectral efficiency and confinement in a number of channels and applications. Its special nature, however, generates a number of new signal processing challenges that are not present in other MCM schemes, notably, in orthogonal-frequency-division multiplexing (OFDM). In multiple-input multiple-output (MIMO) architectures, which are expected to play a primary role in future communication systems, these challenges are intensified, creating new interesting research problems and calling for new ideas and methods that are adapted to the particularities of the MIMO-FBMC/OQAM system. The goal of this paper is to focus on these signal processing problems and provide a concise yet comprehensive overview of the recent advances in this area. Open problems and associated directions for future research are also discussed.Peer ReviewedPostprint (author's final draft

Cognitive MAC protocols for mobile Ad-Hoc networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The term of Cognitive Radio (CR) used to indicate that spectrum radio could be accessed dynamically and opportunistically by unlicensed users. In CR Networks, Interference between nodes, hidden terminal problem, and spectrum sensing errors are big issues to be widely discussed in the research field nowadays. To improve the performance of such kind of networks, this thesis proposes Cognitive Medium Access Control (MAC) protocols for Mobile Ad-Hoc Networks (MANETs). From the concept of CR, this thesis has been able to develop a cognitive MAC framework in which a cognitive process consisting of cognitive elements is considered, which can make efficient decisions to optimise the CR network. In this context, three different scenarios to maximize the secondary user's throughput have been proposed. We found that the throughput improvement depends on the transition probabilities. However, considering the past information state of the spectrum can dramatically increases the secondary user's throughput by up to 40%. Moreover, by increasing the number of channels, the throughput of the network can be improved about 25%. Furthermore, to study the impact of Physical (PHY) Layer errors on cognitive MAC layer in MANETs, in this thesis, a Sensing Error-Aware MAC protocols for MANETs has been proposed. The developed model has been able to improve the MAC layer performance under the challenge of sensing errors. In this context, the proposed model examined two sensing error probabilities: the false alarm probability and the missed detection probability. The simulation results have shown that both probabilities could be adapted to maintain the false alarm probability at certain values to achieve good results. Finally, in this thesis, a cooperative sensing scheme with interference mitigation for Cognitive Wireless Mesh Networks (CogMesh) has been proposed. Moreover, a prioritybased traffic scenario to analyze the problem of packet delay and a novel technique for dynamic channel allocation in CogMesh is presented. Considering each channel in the system as a sub-server, the average delay of the users' packets is reduced and the cooperative sensing scenario dramatically increases the network throughput 50% more as the number of arrival rate is increased