Queueing Based Resource Allocation In Cognitive Radio Networks

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.

Resource allocation is an important issue in wireless communication networks. In recent decades, cognitive radio-based networks have garnered increased attention and have been well studied to overcome the problem of spectrum scarcity in future wireless communication systems. Many new challenges in resource allocation appear in cognitive radio-based networks. This book focuses on effective resource allocation solutions in several important cognitive radio-based networks, including opportunistic spectrum access networks, cooperative sensing networks, cellular networks, high-speed vehicle networks, and smart grids.

This book is about cognitive radio (CR), a revolution in radio technology and an enabling technology for dynamic spectrum access. Due to the unique characteristics of the wireless networks, it is essential to address the approach of multiple layers (e.g., physical, link, and network) to maximize the network performance. The formulation of this cross-layer problem is usually complicated and challenging, while wireless resource allocation is a vital way to handle the race condition of the limited wireless resources. However, given the intrinsic characteristics of cognitive radio networks (CRN), none of the existing analytical approach could be a direct fit. Therefore, innovative theoretical results, along with the corresponding mathematical techniques, are necessary. In this book, we aim to develop some novel algorithmic design and optimization techniques that provide optimal or near-optimal solutions. Although cross-layer design has been introduced to CRN for many years, there are rarely any books for researchers, engineers, and students, from the engineering perspective. From one hand, most of the existing books primarily focus on the mathematical and economic aspects, which are considerably different from the engineering. On the other hand, all of the books mainly aim to system optimization or control techniques, while the cross-layer algorithm design in the distributed environment is usually ignored. As the result, there is an urgent demand for a reference source, which can provide complete information on how to fully adopt cross-layer resource allocation to the CRN. In this regard, this book not only focuses on the description of the main aspects of cross-layer resource allocation over CRN, but also provides a review of the application solutions. In a nutshell, it provides a specific treatment of cross-layer design in CRN. The topics range from the basic concepts of cross-layer resource allocation, to the state-of-the-art analyses, modelings, and optimizations for CRN.

This SpringerBrief presents a survey of dynamic resource allocation schemes in Cognitive Radio (CR) Systems, focusing on the spectral-efficiency and energy-efficiency in wireless networks. It also introduces a variety of dynamic resource allocation schemes for CR networks and provides a concise introduction of the landscape of CR technology. The author covers in detail the dynamic resource allocation problem for the motivations and challenges in CR systems. The Spectral- and Energy-Efficient resource allocation schemes are comprehensively investigated, including new insights into the trade-offs for operating strategies. Promising research directions on dynamic resource management for CR and the applications in other wireless communication systems are also discussed. Cognitive Radio Networks: Dynamic Resource Allocation Schemes targets computer scientists and engineers working in wireless communications. Advanced-level students in computer science and electrical engineering will also find this brief useful reading about the next generation of wireless communication.

This book provides holistic yet concise information on what modern cognitive radio networks are, how they work, and the possible future directions for them. The authors first present the most generic models of modern cognitive radio networks, taking into consideration their different architectural designs and classifications. While the spectrum resource is shown to be the most important resource for the cognitive radio networks, the book exposes the importance of the other resources that are needed to help drive the technology. The book then discusses in-depth the key tools (such as optimization and queuing theory) and techniques (such as cooperative diversity and relaying) that are being employed to formulate resource problems, investigate solutions, and interpret such solutions for useful and practical modern cognitive radio networks realization. Further, the book studies the impact of modern cognitive radio networks on other emerging technologies -- such as 5G, Internet of Things, and advanced wireless sensor networks -- and discusses the role that cognitive radio networks play in the evolution of smart cities and in the realization of a highly interconnected world. In discussing the future of the cognitive radio networks, the book emphasizes the need to advance new or improved tools, techniques, and solutions to address lingering problems in the aspects of resource realization and utilization, network complexity, network security, etc., which can potentially limit the cognitive radio networks in their stride to becoming one of the most promising technologies for the immediate and near future.

This book covers the important aspects involved in making cognitive radio devices portable, mobile and green, while also extending their service life. At the same time, it presents a variety of established theories and practices concerning cognitive radio from academia and industry. Cognitive radio can be utilized as a backbone communication medium for wireless devices. To effectively achieve its commercial application, various aspects of quality of service and energy management need to be addressed. The topics covered in the book include energy management and quality of service provisioning at Layer 2 of the protocol stack from the perspectives of medium access control, spectrum selection, and self-coexistence for cognitive radio networks.

Resource allocation is an important issue in wireless communication networks. In recent decades, cognitive radio-based networks have garnered increased attention and have been well studied to overcome the problem of spectrum scarcity in future wireless communications systems. Many new challenges in resource allocation appear in cognitive radio-based networks. This book focuses on effective resource allocation solutions in several important cognitive radio-based networks, including opportunistic spectrum access networks, cooperative sensing networks, cellular networks, high-speed vehicle networks, and smart grids. Cognitive radio networks are composed of cognitive, spectrum-agile devices capable of changing their configuration on the fly based on the spectral environment. This capability makes it possible to design flexible and dynamic spectrum access strategies with the purpose of opportunistically reusing portions of the spectrum temporarily vacated by licensed primary users. Different cognitive radio-based networks focus on different network resources, such as transmission slots, sensing nodes, transmission power, white space, and sensing channels. This book introduces several innovative resource allocation schemes for different cognitive radio-based networks according to their network characteristics: Opportunistic spectrum access networks - Introduces a probabilistic slot allocation scheme to effectively allocate the transmission slots to secondary users to maximize throughput Cooperative sensing networks - Introduces a new adaptive collaboration sensing scheme in which the resources of secondary users are effectively utilized to sense the channels for efficient acquisition of spectrum opportunities Cellular networks - Introduces a framework of cognitive radio-assisted cooperation for downlink transmissions to allocate transmission modes, relay stations, and transmission power/sub-channels to secondary users to maximize throughput High-speed vehicle networks - Introduces schemes to maximize the utilized TV white space through effective allocation of white space resources to secondary users Smart grids - Introduces effective sensing channel allocation strategies for acquiring enough available spectrum channels for communications between utility and electricity consumers.