QoS-Based Resource Allocation and Transceiver Optimization derives a comprehensive theoretical framework for SIR balancing, with and without noise. The theory considers the possible use of receive strategies (e.g. interference filtering or channel assignment), which can be included in the model in an abstract way. Power allocation and receiver design are mutually interdependent, thus joint optimization strategies are derived. QoS-Based Resource Allocation and Transceiver Optimization provides a better understanding of interference balancing and the characterization of the QoS feasible region. It also provides a generic algorithmic framework, which may serve as a basis for the development of new resource allocation algorithms. QoS-Based Resource Allocation and Transceiver Optimization is an invaluable resource for every engineer and researcher working on multiuser interference problems in wireless communications.

This book offers means to handle interference as a central problem of operating wireless networks. It investigates centralized and decentralized methods to avoid and handle interference as well as approaches that resolve interference constructively. The latter type of approach tries to solve the joint detection and estimation problem of several data streams that share a common medium. In fact, an exciting insight into the operation of networks is that it may be beneficial, in terms of an overall throughput, to actively create and manage interference. Thus, when handled properly, "mixing" of data in networks becomes a useful tool of operation rather than the nuisance as which it has been treated traditionally. With the development of mobile, robust, ubiquitous, reliable and instantaneous communication being a driving and enabling factor of an information centric economy, the understanding, mitigation and exploitation of interference in networks must be seen as a centrally important task.

MIMO Transceiver Design via Majorization Theory presents an up-to-date unified mathematical framework for the design of point-to-point MIMO transceivers with channel state information (CSI) at both sides of the link according to an arbitrary cost function as a measure of the system performance.

The rapid growth in mobile communications has led to an increasing demand for wideband high data rate communications services. In recent years, the Distributed Antenna System (DAS) has emerged as a promising candidate beyond 3G and 4G mobile communications. Distributed Antenna Systems: Open Architecture for Future Wireless Communications is

Majorization Theory and Matrix-Monotone Functions in Wireless Communications, reviews the basic definitions of Majorization Theory and Matrix-Monotone Functions, describing their concepts clearly with many illustrative examples. In addition to this tutorial, new results are presented with respect to Schur-convex functions and regarding the properties of matrix-monotone functions. The approach taken by the authors provides a valuable overview of the basic techniques for readers who are new to the subject. They then proceed to show in separate chapters the cutting edge applications of the two basic theories in wireless communications. Majorization Theory and Matrix-Monotone Functions in Wireless Communications is an invaluable resource for students, researchers and practitioners involved in the state-of-the-art design of wireless communication systems.

Mathematics as a production factor or driving force for innovation? Those, who want to know and understand why mathematics is deeply involved in the design of products, the layout of production processes and supply chains will find this book an indispensable and rich source. Describing the interplay between mathematical and engineering sciences the book focusses on questions like How can mathematics improve to the improvement of technological processes and products? What is happening already? Where are the deficits? What can we expect for the future? 19 articles written by mixed teams of authors of engineering, industry and mathematics offer a fascinating insight of the interaction between mathematics and engineering.

This book will be a comprehensive collection of advanced concepts related to 4th generation wireless communication systems. It will be divided into two main parts: resource allocation and transceiver architectures. These two research areas are at the core of the recent advances experimented by wireless communication systems. Each chapter will cover a relevant, timely, topic with two focuses: a first part which is of tutorial and survey nature, reviews the state of the art in that topic, followed by a more deep treatment including current research topics, case studies and performance analysis.

This book describes, analyzes, and recommends traffic engineering (TE) and quality of service (QoS) optimization methods for integrated voice/data dynamic routing networks. These functions control a network's response to traffic demands and other stimuli, such as link failures or node failures. TE and QoS optimization is concerned with measurement, modeling, characterization, and control of network traffic, and the application of techniques to achieve specific performance objectives. The scope of the analysis and recommendations include dimensioning, call/flow and connection routing, QoS resource management, routing table management, dynamic transport routing, and operational requirements. Case studies are included which provide the reader with a concrete way into the technical details and highlight why and how to use the techniques described in the book. - Includes Case Studies of MPLS and GMPLS Network Optimization - Presents state-of-the-art traffic engineering and quality of service optimization methods and illustrates the tradeoffs between the various methods discussed - Contains practical Case Studies based on large-scale service provider implementations and architecture plans - Written by a highly respected and well known active expert in traffic engineering and quality of service

Due to the highly-varying wireless channels over time, frequency, and space domains, statistical QoS provisioning, instead of deterministic QoS guarantees, has become a recognized feature in the next-generation wireless networks. In this dissertation, we study the adaptive wireless resource allocation problems for statistical QoS provisioning, such as guaranteeing the specified delay-bound violation probability, upper-bounding the average loss-rate, optimizing the average goodput/throughput, etc., in several typical types of mobile wireless networks. In the first part of this dissertation, we study the statistical QoS provisioning for mobile multicast through the adaptive resource allocations, where different multicast receivers attempt to receive the common messages from a single base-station sender over broadcast fading channels. Because of the heterogeneous fading across different multicast receivers, both instantaneously and statistically, how to design the efficient adaptive rate control and resource allocation for wireless multicast is a widely cited open problem. We first study the time-sharing based goodput-optimization problem for non-realtime multicast services. Then, to more comprehensively characterize the QoS provisioning problems for mobile multicast with diverse QoS requirements, we further integrate the statistical delay-QoS control techniques -- effective capacity theory, statistical loss-rate control, and information theory to propose a QoS-driven optimization framework. Applying this framework and solving for the corresponding optimization problem, we identify the optimal tradeoff among statistical delay-QoS requirements, sustainable traffic load, and the average loss rate through the adaptive resource allocations and queue management. Furthermore, we study the adaptive resource allocation problems for multi-layer video multicast to satisfy diverse statistical delay and loss QoS requirements over different video layers. In addition, we derive the efficient adaptive erasure-correction coding scheme for the packet-level multicast, where the erasure-correction code is dynamically constructed based on multicast receivers̕ packet-loss statuses, to achieve high error-control efficiency in mobile multicast networks. In the second part of this dissertation, we design the adaptive resource allocation schemes for QoS provisioning in unicast based wireless networks, with emphasis on statistical delay-QoS guarantees. First, we develop the QoS-driven time-slot and power allocation schemes for multi-user downlink transmissions (with independent messages) in cellular networks to maximize the delay-QoS-constrained sum system throughput. Second, we propose the delay-QoS-aware base-station selection schemes in distributed multiple-input-multiple-output systems. Third, we study the queueaware spectrum sensing in cognitive radio networks for statistical delay-QoS provisioning. Analyses and simulations are presented to show the advantages of our proposed schemes and the impact of delay-QoS requirements on adaptive resource allocations in various environments.

This book deals with the optimization-based joint design of the transmit and receive filters in MIMO broadcast channel in which the user terminals may be equipped with several antenna elements. Furthermore, the maximum performance of the system in the high power regime as well as the set of all feasible quality-of-service requirements is analyzed. First, a fundamental duality is derived that holds between the MIMO broadcast channel and virtual MIMO multiple access channel. This duality construct allows for the efficient solution of problems originally posed in the broadcast channel in the dual domain where a possibly hidden convexity can often be revealed. On the basis of the established duality result, the gradient-projection algorithm is introduced as a tool to solve constrained optimization problems to global optimality under certain conditions. The gradient-projection tool is then applied to solving the weighted sum rate maximization problem which is a central optimization that arises in any network utility maximization. In the high power regime, a simple characterization of the obtained performance becomes possible due to the fact that the weighted sum rate utility converges to an affine asymptote in the logarithmic power domain. We find closed form expressions for these asymptotes which allows for a quantification of the asymptotic rate loss that linear transceivers have to face with respect to dirty paper coding. In the last part, we answer the fundamental question of feasibility in quality-of-service based optimizations with inelastic traffic that features strict delay constraints. Under the assumption of linear transceivers, not every set of quality-of-service requirements might be feasible making the power minimization problem with given lower bound constraints on the rate for example infeasible in these cases. We derive a complete description of the quality-of-service feasibility region for arbitrary channel matrices.