Medium access control design for distributed opportunistic radio networks

Existing wireless networks are characterized by a fixed spectrum assignment policy. However, the scarcity of available spectrum and its inefficient usage demands for a new communication paradigm to exploit the existing spectrum opportunistically. Future Cognitive Radio (CR) devices should be able to sense unoccupied spectrum and will allow the deployment of real opportunistic networks. Still, traditional Physical (PHY) and Medium Access Control (MAC) protocols are not suitable for this new type of networks because they are optimized to operate over fixed assigned frequency bands. Therefore, novel PHY-MAC cross-layer protocols should be developed to cope with the specific features of opportunistic networks. This thesis is mainly focused on the design and evaluation of MAC protocols for Decentralized Cognitive Radio Networks (DCRNs). It starts with a characterization of the spectrum sensing framework based on the Energy-Based Sensing (EBS) technique considering multiple scenarios. Then, guided by the sensing results obtained by the aforementioned technique, we present two novel decentralized CR MAC schemes: the first one designed to operate in single-channel scenarios and the second one to be used in multichannel scenarios. Analytical models for the network goodput, packet service time and individual transmission probability are derived and used to compute the performance of both protocols. Simulation results assess the accuracy of the analytical models as well as the benefits of the proposed CR MAC schemes

A Survey on the Communication Protocols and Security in Cognitive Radio Networks

A cognitive radio (CR) is a radio that can change its transmission parameters based on the perceived availability of the spectrum bands in its operating environment. CRs support dynamic spectrum access and can facilitate a secondary unlicensed user to efficiently utilize the available underutilized spectrum allocated to the primary licensed users. A cognitive radio network (CRN) is composed of both the secondary users with CR-enabled radios and the primary users whose radios need not be CR-enabled. Most of the active research conducted in the area of CRNs has been so far focused on spectrum sensing, allocation and sharing. There is no comprehensive review paper available on the strategies for medium access control (MAC), routing and transport layer protocols, and the appropriate representative solutions for CRNs. In this paper, we provide an exhaustive analysis of the various techniques/mechanisms that have been proposed in the literature for communication protocols (at the MAC, routing and transport layers), in the context of a CRN, as well as discuss in detail several security attacks that could be launched on CRNs and the countermeasure solutions that have been proposed to avoid or mitigate them. This paper would serve as a good comprehensive review and analysis of the strategies for MAC, routing and transport protocols and security issues for CRNs as well as would lay a strong foundation for someone to further delve onto any particular aspect in greater depth

D5.2 - Evaluation of Selected Measurement-based Techniques

Deliverable D5.2 del projecte FARAMIRPreprin

On Random Sampling for Compliance Monitoring in Opportunistic Spectrum Access Networks

In the expanding spectrum marketplace, there has been a long term evolution towards more market€“oriented mechanisms, such as Opportunistic Spectrum Access (OSA), enabled through Cognitive Radio (CR) technology. However, the potential of CR technologies to revolutionize wireless communications, also introduces challenges based upon the potentially non€“deterministic CR behaviour in the Electrospace. While establishing and enforcing compliance to spectrum etiquette rules are essential to realization of successful OSA networks in the future, there has only been recent increased research activity into enforcement. This dissertation presents novel work on the spectrum monitoring aspect, which is crucial to effective enforcement of OSA. An overview of the challenges faced by current compliance monitoring methods is first presented. A framework is then proposed for the use of random spectral sampling techniques to reduce data collection complexity in wideband sensing scenarios. This approach is recommended as an alternative to Compressed Sensing (CS) techniques for wideband spectral occupancy estimation, which may be difficult to utilize in many practical congested scenarios where compliance monitoring is required. Next, a low€“cost computational approach to online randomized temporal sensing deployment is presented for characterization of temporal spectrum occupancy in cognitive radio scenarios. The random sensing approach is demonstrated and its performance is compared to CS€“based approach for occupancy estimation. A novel frame€“based sampling inversion technique is then presented for cases when it is necessary to track the temporal behaviour of individual CRs or CR networks. Parameters from randomly sampled Physical Layer Convergence Protocol (PLCP) data frames are used to reconstruct occupancy statistics, taking account of missed frames due to sampling design, sensor limitations and frame errors. Finally, investigations into the use of distributed and mobile spectrum sensing to collect spatial diversity to improve the above techniques are presented, for several common monitoring tasks in spectrum enforcement. Specifically, focus is upon techniques for achieving consensus in dynamic topologies such as in mobile sensing scenarios

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

Using hypergraph theory to model coexistence management and coordinated spectrum allocation for heterogeneous wireless networks operating in shared spectrum

Electromagnetic waves in the Radio Frequency (RF) spectrum are used to convey wireless transmissions from one radio antenna to another. Spectrum utilisation factor, which refers to how readily a given spectrum can be reused across space and time while maintaining an acceptable level of transmission errors, is used to measure how efficiently a unit of frequency spectrum can be allocated to a specified number of users. The demand for wireless applications is increasing exponentially, hence there is a need for efficient management of the RF spectrum. However, spectrum usage studies have shown that the spectrum is under-utilised in space and time. A regulatory shift from static spectrum assignment to DSA is one way of addressing this. Licence exemption policy has also been advanced in Dynamic Spectrum Access (DSA) systems to spur wireless innovation and universal access to the internet. Furthermore, there is a shift from homogeneous to heterogeneous radio access and usage of the same spectrum band. These three shifts from traditional spectrum management have led to the challenge of coexistence among heterogeneous wireless networks which access the spectrum using DSA techniques. Cognitive radios have the ability for spectrum agility based on spectrum conditions. However, in the presence of multiple heterogeneous networks and without spectrum coordination, there is a challenge related to switching between available channels to minimise interference and maximise spectrum allocation. This thesis therefore focuses on the design of a framework for coexistence management and spectrum coordination, with the objective of maximising spectrum utilisation across geographical space and across time. The amount of geographical coverage in which a frequency can be used is optimised through frequency reuse while ensuring that harmful interference is minimised. The time during which spectrum is occupied is increased through time-sharing of the same spectrum by two or more networks, while ensuring that spectrum is shared by networks that can coexist in the same spectrum and that the total channel load is not excessive to prevent spectrum starvation. Conventionally, a graph is used to model relationships between entities such as interference relationships among networks. However, the concept of an edge in a graph is not sufficient to model relationships that involve more than two entities, such as more than two networks that are able to share the same channel in the time domain, because an edge can only connect two entities. On the other hand, a hypergraph is a generalisation of an undirected graph in which a hyperedge can connect more than two entities. Therefore, this thesis investigates the use of hypergraph theory to model the RF environment and the spectrum allocation scheme. The hypergraph model was applied to an algorithm for spectrum sharing among 100 heterogeneous wireless networks, whose geo-locations were randomly and independently generated in a 50 km by 50 km area. Simulation results for spectrum utilisation performance have shown that the hypergraph-based model allocated channels, on average, to 8% more networks than the graph-based model. The results also show that, for the same RF environment, the hypergraph model requires up to 36% fewer channels to achieve, on average, 100% operational networks, than the graph model. The rate of growth of the running time of the hypergraph-based algorithm with respect to the input size is equal to the square of the input size, like the graph-based algorithm. Thus, the model achieved better performance at no additional time complexity.Electromagnetic waves in the Radio Frequency (RF) spectrum are used to convey wireless transmissions from one radio antenna to another. Spectrum utilisation factor, which refers to how readily a given spectrum can be reused across space and time while maintaining an acceptable level of transmission errors, is used to measure how efficiently a unit of frequency spectrum can be allocated to a specified number of users. The demand for wireless applications is increasing exponentially, hence there is a need for efficient management of the RF spectrum. However, spectrum usage studies have shown that the spectrum is under-utilised in space and time. A regulatory shift from static spectrum assignment to DSA is one way of addressing this. Licence exemption policy has also been advanced in Dynamic Spectrum Access (DSA) systems to spur wireless innovation and universal access to the internet. Furthermore, there is a shift from homogeneous to heterogeneous radio access and usage of the same spectrum band. These three shifts from traditional spectrum management have led to the challenge of coexistence among heterogeneous wireless networks which access the spectrum using DSA techniques. Cognitive radios have the ability for spectrum agility based on spectrum conditions. However, in the presence of multiple heterogeneous networks and without spectrum coordination, there is a challenge related to switching between available channels to minimise interference and maximise spectrum allocation. This thesis therefore focuses on the design of a framework for coexistence management and spectrum coordination, with the objective of maximising spectrum utilisation across geographical space and across time. The amount of geographical coverage in which a frequency can be used is optimised through frequency reuse while ensuring that harmful interference is minimised. The time during which spectrum is occupied is increased through time-sharing of the same spectrum by two or more networks, while ensuring that spectrum is shared by networks that can coexist in the same spectrum and that the total channel load is not excessive to prevent spectrum starvation. Conventionally, a graph is used to model relationships between entities such as interference relationships among networks. However, the concept of an edge in a graph is not sufficient to model relationships that involve more than two entities, such as more than two networks that are able to share the same channel in the time domain, because an edge can only connect two entities. On the other hand, a hypergraph is a generalisation of an undirected graph in which a hyperedge can connect more than two entities. Therefore, this thesis investigates the use of hypergraph theory to model the RF environment and the spectrum allocation scheme. The hypergraph model was applied to an algorithm for spectrum sharing among 100 heterogeneous wireless networks, whose geo-locations were randomly and independently generated in a 50 km by 50 km area. Simulation results for spectrum utilisation performance have shown that the hypergraph-based model allocated channels, on average, to 8% more networks than the graph-based model. The results also show that, for the same RF environment, the hypergraph model requires up to 36% fewer channels to achieve, on average, 100% operational networks, than the graph model. The rate of growth of the running time of the hypergraph-based algorithm with respect to the input size is equal to the square of the input size, like the graph-based algorithm. Thus, the model achieved better performance at no additional time complexity

Spectrum utilization using game theory

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.Spectrum utilization is the most recent communications issue which takes great deal of attention from communication researchers where most of the efforts have been dedicated for spectral efficient utilization. Spectrum sharing is one of the solutions considered in the problem of lack of available frequency for new communication services which are unlicensed. In this work we propose an optimal method for spectrum utilization to increase spectral efficiency. It considers the problem of spectrum holes found in Primary User's (PU) band and detected using one of the spectral sensing methods. The solution is formulated with the help of Game theory approach in such a way that the primary user who has unoccupied frequency can share it with a group of secondary users (SU) in a competitive way. One of the SUs will be a secondary primary user (SPU), share available frequency from PU then offer his sharing to serve other SUs in different rate of sharing. Each user in the group of secondary users has a chance to be secondary primary user depending on reputation of each SU. Enhancing reputation is the only way for any SU to assure a share in the spectrum where it considered the factor of increasing or decreasing rate of sharing as well as factor of being SPU or an ordinary SU. A theoretical non-cooperative game model is introduced in a comparison with a proposed non-dynamic technique which depends on number of subscribers who occupy frequency in each time period. Multi-users compete on sharing the frequency from one of the users who offers sharing at a time when he has low number of subscribers that occupy his band. It is found that non-dynamic sharing results in inefficient spectrum utilization which is one of the reasons of spectrum scarcity where this resource is allocated in fixed way. Spectrum sharing using game theory solves this problem by its ability to make users compete to gain highest rate of spectrum allocation according to the real requirement of each user at each time interval. The problem of urgent case is also discussed when the primary user comes back to using his band which is the specific band of sharing with the secondary users group. SPU makes it easy to unload the required band from multi-users because PU does not need to request his band from each SU in the group

When Channel Bonding is Beneficial for Opportunistic Spectrum Access Networks

Transmission over multiple frequency bands combined into one logical channel speeds up data transfer for wireless networks. On the other hand, the allocation of multiple channels to a single user decreases the probability of finding a free logical channel for new connections, which may result in a network-wide throughput loss. While this relationship has been studied experimentally, especially in the WLAN configuration, little is known on how to analytically model such phenomena. With the advent of Opportunistic Spectrum Access (OSA) networks, it is even more important to understand the circumstances in which it is beneficial to bond channels occupied by primary users with dynamic duty cycle patterns. In this paper we propose an analytical framework which allows the investigation of the average channel throughput at the medium access control layer for OSA networks with channel bonding enabled. We show that channel bonding is generally beneficial, though the extent of the benefits depend on the features of the OSA network, including OSA network size and the total number of channels available for bonding. In addition, we show that performance benefits can be realized by adaptively changing the number of bonded channels depending on network conditions. Finally, we evaluate channel bonding considering physical layer constraints, i.e. throughput reduction compared to the theoretical throughput of a single virtual channel due to a transmission power limit for any bonding size.Comment: accepted to IEEE Transactions on Wireless Communication