Improved Spectrum Mobility using Virtual Reservation in Collaborative Cognitive Radio Networks

Cognitive radio technology would enable a set of secondary users (SU) to opportunistically use the spectrum licensed to a primary user (PU). On the appearance of this PU on a specific frequency band, any SU occupying this band should free it for PUs. Typically, SUs may collaborate to reduce the impact of cognitive users on the primary network and to improve the performance of the SUs. In this paper, we propose and analyze the performance of virtual reservation in collaborative cognitive networks. Virtual reservation is a novel link maintenance strategy that aims to maximize the throughput of the cognitive network through full spectrum utilization. Our performance evaluation shows significant improvements not only in the SUs blocking and forced termination probabilities but also in the throughput of cognitive users.Comment: 7 pages, 10 figures, IEEE ISCC 201

Stochastic models for cognitive radio networks

During the last decade we have seen an explosive development of wireless technologies. Consequently the demand for electromagnetic spectrum has been growing dramatically resulting in the spectrum scarcity problem. In spite of this, spectrum utilization measurements have shown that licensed bands are vastly underutilized while unlicensed bands are too crowded. In this context, Cognitive Radio emerges as an auspicious paradigm in order to solve those problems. Even more, this concept is envisaged as one of the main components of future wireless technologies, such as the fifth-generation of mobile networks. In this regard, this thesis is founded on cognitive radio networks. We start considering a paid spectrum sharing approach where secondary users (SUs) pay to primary ones for the spectrum utilization. In particular, the first part of the thesis bears on the design and analysis of an optimal SU admission control policy, i.e. that maximizes the long-run profit of the primary service provider. We model the optimal revenue problem as a Markov Decision Process and we use dynamic programming (and other techniques such as sample-path analysis) to characterize properties of the optimal admission control policy. We introduce different changes to one of the best known dynamic programming algorithms incorporating the knowledge of the characterization. In particular, those proposals accelerate the rate of convergence of the algorithm when is applied in the considered context. We complement the analysis of the paid spectrum sharing approach using fluid approximations. That is to say, we obtain a description of the asymptotic behavior of the Markov process as the solution of an ordinary differential equation system. By means of the fluid approximation of the problem, we propose a methodology to estimate the optimal admission control boundary of the maximization profit problem mentioned before. In addition, we use the deterministic model in order to propose some tools and criteria that can be used to improve the mean spectrum utilization with the commitment of providing to secondary users certain quality of service levels. In wireless networks, a cognitive user can take advantage of either the time, the frequency, or the space. In the first part of the thesis we have been concentrated on timefrequency holes, in the second part we address the complete problem incorporating the space variable. In particular, we first introduce a probabilistic model based on a stochastic geometry approach. We focus our study in two of the main performance metrics: medium access probability and coverage probability. Finally, in the last part of the thesis we propose a novel methodology based on configuration models for random graphs. With our proposal, we show that it is possible to calculate an analytic approximation of the medium access probability (both for PUs and, most importantly, SUs) in an arbitrary large heterogeneous random network. This performance metric gives an idea of the possibilities offered by cognitive radio to improve the spectrum utilization. The introduced robust method, as well as all the results of the thesis, are evaluated by several simulations for different network topologies, including real scenarios of primary network deployments. Keywords: Markov decision process, fluid limit, stochastic geometry, random graphs,dynamic spectrum assignment, cognitive radi

Performance Analysis and Modelling of Spectrum Handoff Schemes in Cognitive Radio Networks. Modelling and Analysis of Spectrum Handoff Decision Schemes in Cognitive Radio Networks using the Queuing Theory and Simulation for Licensed and Unlicensed Spectrum Bands.

Recently, wireless access has become an essential part of modern society. Consequently, the demand for new wireless applications and services, as well as the number of wireless users, are gradually increasing. Given that this amount of expansion is eventually controlled by the available radio frequency spectrum, government regulatory agencies have recently adopted a strict approach to the licensing of limited amounts of spectrum to different entities (e.g., public safety, military, service providers, unlicensed devices, and TV). All of them possess exclusive transmissions to their assigned frequency channels. A new study on spectrum efficiency revealed big geographic and temporal variations in spectrum utilisation, ranging from 15-85% in the bands below 3GHz. These variations were less at frequencies above this figure. Recently, the Cognitive Radio (CR) has risen as an encouraging piece of technology to improve spectrum efficiency and to solve the problem of spectrum scarcity. This is because CR allows the secondary (unlicensed) users to occupy unused licensed spectrum bands temporarily, given that the interference of the primary (licensed) users is prohibited or minimised. In this thesis, various spectrum handoff management schemes have been proposed in order to improve the performance evaluation for CR networks. The proposed spectrum handoff schemes use the Opportunistic Spectrum Access (OSA) concept to utilise available spectrum bands. The handoff Secondary Users (SUs) have a higher priority to occupy available spectrum channels in the licensed and unlicensed spectrum bands without interfering with the legacy spectrum owner, i.e. primary users (PUs). However, existing spectrum handoff management schemes in CR networks do not provide high transmission opportunities for handoff secondary users to utilise the available radio spectrum resources. The first part of this thesis addresses the issue of spectrum handoff management in a licensed spectrum band environment. In this case, both reactive and proactive spectrum handoff schemes are proposed. Queuing theory or/and simulation experiments have been used to evaluate the performance of the proposed schemes and compare them with other existing schemes. Handoff delay has mainly been used to investigate the impact of successive handoff operations on the performance of the proposed CR networks. Implemented models have shown an improvement in the adopted performance measures. According to the achieved results, the improvement of the proposed, prioritised handoff schemes in some cases is approximately 75% when compared with existing schemes. On the other hand, the second part of this research proposed a prioritised spectrum handoff scheme in a heterogeneous spectrum environment, which is composed of a pool of licensed and unlicensed spectrum channels. In general, the availability of substantial numbers of the licensed spectrum channels is the key benefit of using this type of radio spectrum channel. Whereas, accessing with equal rights for all types of users is the main advantage of using unlicensed spectrum channels. In this respect, no transmission interruptions occur once a user obtains a channel. In addition, the proposed schemes use only the unlicensed spectrum channels as their backup channels. This enables the user to resume interrupted transmission in the case of the spectrum handoff operation (mainly; due to the appearance of the primary users), and thus facilitates a SUs communication. The proposed principle is investigated using a retrial queuing theory as well as extensive simulation experiments, and is compared with another non-prioritised scheme which do not give any preference to handoff SUs over new SUs. The results indicate that the proposed model has improved on current average handoff delay. This thesis contributes to knowledge by further enhancing the efficient utilisation of available radio spectrum resources and therefore subsequently provides an improvement in the spectrum capacity for wireless cognitive radio networks

Resource Allocation using Genetic Algorithm in Multimedia Wireless Networks

Resource allocations in wireless networks is a very challenging task, at one hand wireless networks have scarce resources and suffers from many limitations. At the other hand, typical resource allocation problems requires extensive amount of computations and are usually NP-hard problems. Hence, there is dire need for effective and feasible solutions. Resource allocation problems are concerned in distributing the available network’s resources to all active users in a fair way. Although fairness is hard to define, this work considers the fairness aspects for both, the users and the network operator (service provider). Bio-inspired algorithm are used in many context to provide simple and effective solution tochallenging problems. This works employs Genetic Algorithm to provide effective solution to resource allocation problem for multimedia allocation in wireless networks. The performance of the proposed solution is evaluated using simulation. The obtained simulation results show that the proposed solutionachieved better performance

Optimization of Access Threshold for Cognitive Radio Networks with Prioritized Secondary Users

We propose an access control scheme in cognitive radio networks with prioritized Secondary Users (SUs). Considering the different types of data in the networks, the SU packets in the system are divided into SU1 packets with higher priority and SU2 packets with lower priority. In order to control the access of the SU2 packets (including the new arrival SU2 packets and the interrupted SU2 packets), a dynamic access threshold is set. By building a discrete-time queueing model and constructing a three-dimensional Markov chain with the number of the three types of packets in the system, we derive some performance measures of the two types of the SU packets. Then, with numerical results, we show the change trends for the different performance measures. At last, considering the tradeoff between the throughput and the average delay of the SU2 packets, we build a net benefit function to make optimization for the access threshold