Cognitive Radio Resource Management Using Multi-Agent Systems

International Journal of Computer Applications, 2014

In this paper, resource allocation models for cognitive radio networks (CRN) using game theory are presented. The study includes the concept of cognitive radio (CR) networks, cooperative and non-cooperative game theory, and modeling of strategic interaction process for CR enabled secondary users. The prime objective of the present study is to compare existing game models for CR networks in terms of concept, approach, system model, and issues associated with each model. At last, conclusion for implementing game models in the cognitive radio networks for effective management of available radio resources is given to provide direction to researchers for future work.

IEEE Transactions on Vehicular Technology, 2011

This paper presents new design formulations that aim at optimizing the performance of an orthogonal frequency-division multiple-access (OFDMA) ad hoc cognitive radio network through joint subcarrier assignment and power allocation. Aside from an important constraint on the tolerable interference induced to primary networks, to efficiently implement spectrum-sharing control within the unlicensed network, the optimization problems considered here strictly enforce upper and lower bounds on the total amount of temporarily available bandwidth that is granted to individual secondary users. These new requirements are of particular relevance in cognitive radio settings, where the spectral activities of primary users are highly dynamic, leaving little opportunity for secondary access. A dual decomposition framework is then developed for two criteria (throughput maximization and power minimization), which gives rise to the realization of distributed solutions. Because the proposed distributed protocols require very limited cooperation among the participating network elements, they are particularly applicable to ad hoc cognitive networks, where centralized processing and control are certainly inaccessible. In this paper, we recommend that the network collaboration is made possible through the implementation of virtual timers at individual secondary users and through the exchange of pertinent information over a common reserved channel. It is shown that not only is the computational complexity of the devised algorithms affordable but that the performance of these algorithms in practical scenarios attains the actual global optimum as well. The potential of the proposed approaches is thoroughly verified by asymptotic complexity analysis and numerical results.

International Journal on Advances in Telecommunications, 2011

In modern day wireless networks, spectrum utilization and allocation are static. Generally, static spectrum allocation is not a feasible solution considering the distributed and dynamic nature of wireless devices, thus some alternatives must be ensured in order to allocate spectrum dynamically and to mitigate the current spectrum scarcity. An effective technology to ensure dynamic spectrum usage is cognitive radio, which seeks the unutilized spectrum holes opportunistically and shares them with the neighboring devices. Using cognitive radio capabilities, the nodes are not restrained to static spectrum utilization, rather they can choose it on demand. However, dynamic spectrum usage raises several challenges, which need to be addressed in detail. These challenges include efficient allocation of spectrum between licensed (or primary) and cognitive radio (or secondary) users in order to maximize spectrum utilization and to avoid device level interferences. To this extend, we develop a novel solution for spectrum allocation using multiagent system cooperation that enables secondary user devices to utilize the amount of available spectrum, dynamically and cooperatively. The key aspect of our design is the deployment of agents on each of the primary and secondary user devices that cooperate in order to have a better use of the spectrum. For cooperation, contract net protocol is used, allowing spectrum to be dynamically allocated by having a series of message exchanges amongst the devices. Simulation results show that our solution achieves up to 80% of the whole utility within the span of few messages, and provides an effective mechanism for dynamic spectrum allocation.

Pervasive and Mobile Computing, 2017

Due to advancements in the wireless networking technologies, a lot of new wireless services are demanding the radio spectrum for their usage. The radio spectrum is considered as a limited natural resource for radio communications, and it became crowded. In fact, this resource is not limited, rather the scarcity of the radio spectrum arises because of inefficient and fixed utilization of this valuable resource. This inefficient and under-utilization of radio spectrum has diverted the attentions of the researchers towards the different techniques in order to access the spectrum dynamically and adaptively. The concept of Cognitive Radio (CR) can be implemented by making the communication devices intelligent, in order to use the available radio spectrum efficiently. The efficient implementation of cognitive radios into the wireless networks gives rise to a tremendous number of optimization problems with multiple objectives. In most of the cases, these objectives are conflicting with each other and need to be addressed carefully. In this article, we will present the importance of multi-objective optimization (MOO) in cognitive radio networks (CRNs). We will discuss about the fundamental differences in single objective optimization (SOO) and MOO techniques, in order to solve MOO problems associated with CRNs. We will differentiate between the possible relations such as, conflicting, supporting and design dependent, among these objectives. A comparative discussion will also be provided about optimization types, solution approaches/algorithms and different combining techniques to combine multiple objectives in order to address MOO problems those comes with CRNs.

2013

In this book chapter, joint radio resource management (JRRM) issues in cognitive networks are discussed presenting the TV White Spaces (TVWS) spectrum exploitation use case. TVWS are portions of UHF spectrum, which will be released and interleaved according to the geographical region due to the gradual switch-off of analogue TV and the adoption of digital TV. With the availability of TVWS and their temporary lease, traditional network planning and RRM design rationale points need to be enhanced. This book chapter initially provides a state-of-the-art work for existing cognitive radio network architectures, while a reference architecture for commons and secondary TVWS trading is proposed. Subsequently, JRRM concepts for heterogeneous Radio Access Technologies' extension over TVWS aiming to continuously guarantee the QoS, the network key performance indicators and at the same time targeting the overall highest system capacity, are presented. Finally, a thorough classification of existing admission control and scheduling techniques is provided, outlining the need for including continuously more cognitive and context-aware features in JRRM algorithms being applicable in advanced heterogeneous networking (HetNet) environments.

Wireless Personal Communications, 2009

ABSTRACT Cognitive Radio (CR) approach can be considered as a promising and suitable solution to solve in an efficient and flexible way the increasing and continuous demand of services and radio resources. This paper shows the potential benefits of the adoption of a cognitive radio strategy to the coexistence problem. Two different approaches have been considered: the first one is based on the Game Theory while the second one is formalized as a constrained maximum search and represent the optimum solution. The Game theory approach, suitable for a distributed implementation, provides performances comparable to the heuristic one which is a centralized optimization problem. The paper analyzes the performances of both approaches in terms of secondary rates and spectral efficiency provided by the secondary system.

2007 IEEE International Conference on Communications, 2007

Cognitive radio is generally understood as an intelligent wireless communication system aiming at the efficient utilization of radio resources. We argue for the extension of its scope to also address the management of computing resources, including processing and bandwidth capacities of SDR platforms, and present a cooperative resource management framework: The joint radio resource management (JRRM) and the computing resources management (CRM) entities interchange information to cooperatively decide if and what kind of terminal reconfiguration would be the most appropriate in each situation. Therefore, the cognitive radio system continuously observes the radio and the computing environments. We discuss a realistic case study and present a simple CRM algorithm. Simulation results show that such a cooperative resource management approach can achieve important improvements over the JRRM by itself. In particular, our proposal considerably reduces the number of lost user sessions due to inappropriate reconfiguration decisions and, thus, serves more wireless users.

2011 IEEE Consumer Communications and Networking Conference (CCNC), 2011

2011

This paper describes a novel self-optimized approach for resource management based on the cognitive radio in the cellular networks. The cognitive radio techniques offer several features like autonomy, sensing and negotiation. The use of cognitive radio approach gives greater autonomy to the base stations in the cellular networks. This autonomy allows an increase in flexibility to deal with new situations in the traffic load. The negotiation strategy is used to avoid conflicts in the resource allocation. The goal of the cognitive radio scheme is to achieve a high degree of resource usage and a low rate of call blocking in the cellular systems.