Resource Allocation And Optimization For Multiple User Legacy And Cognitive Radio Systems

The rapid transition towards user mobility and the increased demand it carries for bandwidth and data rates has been the driver for significant advancements in research and development in wireless communications in the last decade. These advancements materialized through enhancements to the well established legacy systems and conceptual innovations with great potential. Not far from that, in this thesis, we consider a diverse set of tools and techniques that facilitate efficient utilization of system resources in legacy and Cognitive Radio (CR) systems without hindering the integrity and robustness of the system design. First, we introduce the concept of service differentiation at the receiver, which can be realized by means of a new multiple-user Multiple-Input Multiple-Output (MIMO) detector based on the well known V-BLAST algorithm. We devise the DiffSIC algorithm that is able to differentiate between users in service based on their priorities or imminent needs. DiffSIC achieves its goal by determining the optimal order of detection, at the receiver, that best fits the users' profiles. Second, we propose a channel allocation technique for the transmitter of MIMO multiple-user access systems which enhances the system capacity without aggravating the complexity of the receiver. In particular, we allow users to share resources to take full advantage of the degrees of freedom available in the system. Moreover, we show how to realize these enhancements using simple, yet powerful, modulation and detection techniques. Next, we propose new robust system designs for MIMO CR systems under the inevitable reality of imperfect channel state information at the CR transmitter. We apply innovative tools from optimization theory to efficiently and effectively solve design problems that involve multiple secondary users operating over multiple frequency carriers. At last, we observe the effect of primary users' activity on the stability of, and quality of service provided by, CR sy.

This book focuses on the issue of optimizing radio resource allocation (RRA) and user admission control (AC) for multiple multicasting sessions on a single high altitude platform (HAP) with multiple antennas on-board. HAPs are quasi-stationary aerial platforms that carry a wireless communications payload to provide wireless communications and broadband services. They are meant to be located in the stratosphere layer of the atmosphere at altitudes in the range 17-22 km and have the ability to fly on demand to temporarily or permanently serve regions with unavailable telecommunications infrastructure. An important requirement that the book focusses on is the development of an efficient and effective method for resource allocation and user admissions for HAPs, especially when it comes to multicasting. Power, frequency, space (antennas selection) and time (scheduling) are the resources considered in the problem over an orthogonal frequency division multiple access (OFDMA) HAP system. Due to the strong dependence of the total number of users that could join different multicast groups, on the possible ways we may allocate resources to these groups, it is of significant importance to consider a joint user to session assignments and RRA across the groups. From the service provider's point of view, it would be in its best interest to be able to admit as many higher priority users as possible, while satisfying their quality of service requirements. High priority users could be users subscribed in and paying higher for a service plan that gives them preference of admittance to receive more multicast transmissions, compared to those paying for a lower service plan. Also, the user who tries to join multiple multicast groups (i.e. receive more than one multicast transmission), would have preferences for which one he would favor to receive if resources are not enough to satisfy the QoS requirements. Technical topics discussed in the book include: Overview on High Altitude Platforms, their different types and the recent works in this areaRadio Resource Allocation and User Admission Control in HAPsMulticasting in a Single HAP System: System Model and Mathematical FormulationOptimization schemes that are designed to enhance the performance of a branch and bound technique by taking into account special mathematical structure in the problem formulation

In this thesis, resource allocation and multiple access in cognitive radio (CR) and compressed sensing (CS)-based wireless networks are studied. Energy-efficiency oriented design becomes more and more important in wireless systems, which motivates us to propose a location-aware power strategy for single user and multiple users in CR systems and a CS-based processing in wireless sensor networks (WSNs) which reduces the number of data transmissions and energy consumption by utilizing sparsity of the transmitted data due to spatial correlation and temporal correlation. In particular, the work on location-aware power allocation in CR system gives a brief overview of the existing power allocation design in the literature and unifies them into a general power allocation framework. The impact of the network topology on the system performance is highlighted, which motivates us to propose a novel location-aware strategy that intelligently utilizes frequency and space opportunities and minimizes the overall power consumption while maintaining the quality of service (QoS) of the primary system. This work shows that in addition to exploring the spectrum holes in time and frequency domains, spatial opportunities can be utilized to further enhance energy efficiency for CR systems. Then the work of resource allocation is extended to finding the power strategy and channel allocation optimization for multiple secondary users in an orthogonal frequency division multiplexing (OFDM) based cognitive radio network.

Cognitive radio is an interesting concept for solving the problem of spectrum availability by allowing non-licensed users to exploit underutilized licensed frequency bands. We note that a combination of the cognitive radio with cooperative communication and/or MIMO technology can possibly enhance the system performance significantly. In this research, a number of resource allocation problems are examined for cognitive radio systems (CRS) that have relaying and/or MIMO capabilities, and computationally efficient resource allocation schemes are proposed. The general objective is to devise resource allocation schemes in the cognitive radio that maximize the resource utilization under the constraint of acceptable interference to the primary (licensed) users. In particular, in this thesis we present efficient schemes for jointly deciding the assignment of multiple relays to users and their power levels. Fairness is also considered in assigning multiple relays to multiple secondary users. We also propose low-complexity distributed schemes for joint subcarrier and relay assignment in cooperative multi-carrier multi-cast CRS. Another class of resource allocation problems addressed this thesis regards selecting and scheduling users in multiuser systems. In multiuser cognitive MIMO systems, user selection and scheduling significantly affects the system performance. This thesis addresses joint user scheduling and power allocation in the CRS equipped with multiple antennas. Optimization of such user scheduling and power allocation has combinatorial aspects, and the exhaustive search for an exactly optimal solution is impractical due to its computational complexity. This thesis presents low-complexity suboptimal algorithms to maximize the sum-rate capacity of the uplink communication in cognitive MIMO systems under the constraint that the interference to the primary users is below a specified level.

A comprehensive treatment of cognitive radio networks and the specialized techniques used to improve wireless communications The human brain, as exemplified by cognitive radar, cognitive radio, and cognitive computing, inspires the field of Cognitive Dynamic Systems. In particular, cognitive radio is growing at an exponential rate. Fundamentals of Cognitive Radio details different aspects of the human brain and provides examples of how it can be mimicked by cognitive dynamic systems. The text offers a communication-theoretic background, including information on resource allocation in wireless networks and the concept of robustness. The authors provide a thorough mathematical background with data on game theory, variational inequalities, and projected dynamic systems. They then delve more deeply into resource allocation in cognitive radio networks. The text investigates the dynamics of cognitive radio networks from the perspectives of information theory, optimization, and control theory. It also provides a vision for the new world of wireless communications by integration of cellular and cognitive radio networks. This groundbreaking book: Shows how wireless communication systems increasingly use cognition to enhance their networks Explores how cognitive radio networks can be viewed as spectrum supply chain networks Derives analytic models for two complementary regimes for spectrum sharing (open-access and market-driven) to study both equilibrium and disequilibrium behaviors of networks Studies cognitive heterogeneous networks with emphasis on economic provisioning for resource sharing Introduces a framework that addresses the issue of spectrum sharing across licensed and unlicensed bands aimed for Pareto optimality Written for students of cognition, communication engineers, telecommunications professionals, and others, Fundamentals of Cognitive Radio offers a new generation of ideas and provides a fresh way of thinking about cognitive techniques in order to improve radio networks.

As wireless services rapidly expand, the inefficient use of limited spectrum resources poses a critical challenge. The conventional approach to spectrum allocation, based on fixed assignments, could be more effective in meeting the escalating demand for wireless devices and systems. Cognitive radio technology offers a transformative solution by reimagining the spectrum as a multidimensional space, enabling opportunistic access to underutilized bands. However, the field of cognitive radio is still in its early stages, needing more in-depth analyses and descriptions of crucial processes. Spectrum and Power Allocation in Cognitive Radio Systems addresses this pressing need by offering a comprehensive guide for academic scholars, researchers, and industry professionals. This book delves into cognitive radio technology's foundations, organization, and challenges, providing insights into dynamic spectrum access, networking protocols, hardware architecture, and emerging applications. It presents advanced topics such as spectrum sensing algorithms, cooperative spectrum sensing, and multi-user access, offering practical solutions to enhance spectrum efficiency.

With the explosive growth of wireless systems and services, bandwidth has become a treasured commodity. Traditionally, licensed frequency bands were exclusively reserved for use by the primary license holders (primary users), whereas, unlicensed frequency bands allow spectrum sharing. Recent spectrum measurements indicate that many licensed bands remain relatively unused for most of the time. Therefore, allowing secondary users (users without a license to operate in the band) to operate with minimal or no interference to primary users is one way of sharing spectrum to increase efficiency. Recently, Federal Communications Commission (FCC) has opened up licensed bands for opportunistic use by secondary users. A cognitive radio (CR) is one enabling technology for systems supporting opportunistic use. A cognitive radio adapts to the environment it operates in by sensing the spectrum and quickly decides on appropriate frequency bands and transmission parameters to use in order to achieve certain performance goals. A cognitive radio network (CRN) refers to a network of cognitive radios/secondary users. In this dissertation, we consider a competitive CRN with multiple channels available for opportunistic use by multiple secondary users. We also assume that multiple secondary users may coexist in a channel and each secondary user (SU) can use multiple channels to satisfy their rate requirements. In this context, firstly, we introduce an integrated modeling and forecasting tool that provides an upper bound estimate of the number of secondary users that may be demanding access to each of the channels at the next instant. Assuming a continuous time Markov chain model for both primary and secondary users activities, we propose a Kalman filter based approach for estimating the number of primary and secondary users. These estimates are in turn used to predict the number of primary and secondary users in a future time instant. We extend the modeling and forecasting framework to the case when SU traffic is governed by Erlangian process. Secondly, assuming that scheduling is complete and SUs have identified the channels to use, we propose two quality of service (QoS) constrained resource allocation frameworks. Our measures for QoS include signal to interference plus noise ratio (SINR) /bit error rate (BER) and total rate requirement. In the first framework, we determine the minimum transmit power that SUs should employ in order to maintain a certain SINR and use that result to calculate the optimal rate allocation strategy across channels. The rate allocation problem is formulated as a maximum flow problem in graph theory. We also propose a simple heuristic to determine the rate allocation. In the second framework, both transmit power and rate per channel are simultaneously optimized with the help of a bi-objective optimization problem formulation. Unlike prior efforts, we transform the BER requirement constraint into a convex constraint in order to guarantee optimality of resulting solutions. Thirdly, we borrow ideas from social behavioral models such as Homo Egualis (HE), Homo Parochius (HP) and Homo Reciprocan (HR) models and apply it to the resource management solutions to maintain fairness among SUs in a competitive CRN setting. Finally, we develop distributed user-based approaches based on ``Dual Decomposition Theory" and ``Game Theory" to solve the proposed resource allocation frameworks. In summary, our body of work represents significant ground breaking advances in the analysis of competitive CRNs.

We are currently witnessing an increase in telecommunications norms and standards given the recent advances in this field. The increasing number of normalized standards paves the way for an increase in the range of services available for each consumer. Moreover, the majority of available radio frequencies have already been allocated. This explains the emergence of cognitive radio (CR) – the sharing of the spectrum between a primary user and a secondary user. In this book, we will present the state of the art of the different techniques for spectrum access using cooperation and competition to solve the problem of spectrum allocation and ensure better management of radio resources in a radio cognitive context. The different aspects of research explored up until now on the applications of multi-agent systems (MAS) in the field of cognitive radio are analyzed in this book. The first chapter begins with an insight into wireless networks and mobiles, with special focus on the IEEE 802.22 norm, which is a norm dedicated to CR. Chapter 2 goes into detail about CR, which is a technical field at the boundary between telecommunications and Artificial Intelligence (AI). In Chapter 3, the concept of the “agent” from AI is expanded to MAS and associated applications. Finally, Chapter 4 establishes an overview of the use of AI techniques, in particular MAS, for its allocation of radio resources and dynamic access to the spectrum in CR. Contents 1. Wireless and Mobile Networks. 2. Cognitive Radio. 3. Multi-agent Systems. 4. Dynamic Spectrum Access. About the Authors Badr Benmammar has been Associate Professor at UABT (University Abou Bekr Belkaïd Tlemcen), Algeria since 2010 and was a research fellow at CNRS LaBRI Laboratory of the University of Bordeaux 1 until 2007. He is currently carrying out research at the Laboratory of Telecommunications of Tlemcen (LTT), UABT, Algeria. His main research activities concern the cognitive radio network, Quality of Service on mobile and wireless networks, end-to-end signaling protocols and agent technology. His work on Quality of Service has led to many publications in journals and conference proceedings. Asma Amraoui is currently a PhD candidate; she is preparing a doctoral thesis on a topic of research that explores the use of artificial intelligence techniques in cognitive radio networks. She is attached to the Laboratory of Telecommunications of Tlemcen (LTT) in Algeria.

With the increase in wireless technology devices and mobile users, wireless radio spectrum is coming under strain. Networks are becoming more and more congested and free usable spectrum is running out. This creates a resource allocation problem. The resource, wireless spectrum, needs to be allocated to users in a manner such that it is utilised efficiently and fairly. The objective of this research is to find a solution to the resource allocation problem in radio networks, i.e to increase the efficiency of spectrum utilisation by making maximum use of the spectrum that is currently available through taking advantage of co-existence and exploiting interference limits. The solution proposed entails adding more secondary users (SU) on a cognitive radio network (CRN) and having them transmit simultaneously with the primary user. A typical network layout was defined for the scenario. The interference temperature limit (ITL) was exploited to allow multiple SUs to share capacity. Weighting was applied to the SUs and was based on allowable transmission power under the ITL. Thus a more highly weighted SU will be allowed to transmit at more power. The weighting can be determined by some network-defined rule. Specific models that define the behaviour of the network were then developed using queuing theory, specifically weighted processor sharing techniques. Optimisation was finally applied to the models to maximize system performance. Convex optimization was deployed to minimize the length of the queue through the power allocation ratio. The system was simulated and results for the system performance obtained. Firstly, the performance of the proposed models under the processor-sharing techniques was determined and discussed, with explanations given. Then optimisation was applied to the processor-sharing results and the performance was measured. In addition, the system performance was compared to other existing solutions that were deemed closest to the proposed models.

Cognitive radio (CR) technology has been considered one of the most promising solutions to make the best potential use of the scarce spectrum resources in next generation wireless communication. Because of the stringent limitations on the utilization of the radio resources in a cognitive radio network (CRN), the available resources are usually scarce and dynamic. Developing appropriate mechanism to construct allocation protocols for CRN that can assign the resources in a fair and efficient manner to diverse users with different features is essential to achieve the promise of the CR technology in reality and worth studying. aÌ22́Ơ¿3The mechanism for resource allocation protocol design in CRNaÌ22́Ơ℗+ describes the topic of this research work and the contents of this thesis are organized around it. Before investigating how to design appropriate mechanism for CR resource allocation (RA) protocols, the model of the radio resource and the model of how a CR system utilizes the resource have to be clarified. In this thesis, by a comprehensive study of the relevant literatures, the modeling of critical components of a CR system and the theory behind it are identified and investigated. The existing protocols are also analyzed to address the limitations and gaps in the design of allocation protocols. An important feature, if not the most, that the allocation protocol for the CRN should possess is the ability to adjust the strategy of RA when the circumstances that affect the data transmission of the CR system varies, such as the activity of the license users or the variety of CR usersaÌ22́Ơ4́Ø demands. According to such considerations, the mechanism, namely distribution probability matrix (DPM), is designed to guide and describe the channel allocation protocol quantitatively. To testify how this mechanism works, the protocols based on the DPM, together with reference protocols in a multichannel CRN, are analyzed by a queuing model. The numerical results shows the flexibility and adaptability that the protocols based on the DPM can achieve. Another important function of the DPM mechanism is the potential to describe complex protocols with specific principles and to help design protocols aimed at specific objectives. To demonstrate this, a maximum throughput (MT) protocol that is aimed at maximizing the overall throughput of the CR system in a multi-user multi-channel scenario is structured using the DPM mechanism. The existing reference protocols, including maximum rate and random allocation, are described under the DPM mechanism as well as the MT protocol. All the protocols are implemented in a multiuser multichannel CRN and analyzed by a queueing analytical framework proposed by the author that is capable of acquiring the performance metrics of each CR user independently with efficiency. Numerical results show that the MT protocol is able to outperform the existing protocol in terms of the overall throughput of the CRN. The last problem identified and addressed in this thesis is to investigate the potential of specific performance metrics that a CR system can achieve under certain conditions with the help of the DPM mechanism. An optimization problem that is aimed at maximizing the overall weighted throughput of a multi-user multi-channel CRN under the delay constraint is formulated and solved using the DPM mechanism. The key factors that affect the optimal weighted throughput and the optimal allocations are investigated through the numerical results obtained by the proposed queueing analytical framework. The advantages of the DPM mechanism in optimizing the performance of CRN is also revealed by the formulation and solution of the optimization problem. The RA protocol is the essential kernel to address the RA problem in the CRN context. This thesis, by providing an objective and effective mechanism that works as a universal tool to describe and evaluate the RA protocols, succeeds in making effective contribution to addressing the RA problem in the CRN and further, helping the CR technology realize its meaningful promises.