Analysis Framework for Opportunistic Spectrum OFDMA and its Application to the IEEE 802.22 Standard

We present an analytical model that enables throughput evaluation of Opportunistic Spectrum Orthogonal Frequency Division Multiple Access (OS-OFDMA) networks. The core feature of the model, based on a discrete time Markov chain, is the consideration of different channel and subchannel allocation strategies under different Primary and Secondary user types, traffic and priority levels. The analytical model also assesses the impact of different spectrum sensing strategies on the throughput of OS-OFDMA network. The analysis applies to the IEEE 802.22 standard, to evaluate the impact of two-stage spectrum sensing strategy and varying temporal activity of wireless microphones on the IEEE 802.22 throughput. Our study suggests that OS-OFDMA with subchannel notching and channel bonding could provide almost ten times higher throughput compared with the design without those options, when the activity and density of wireless microphones is very high. Furthermore, we confirm that OS-OFDMA implementation without subchannel notching, used in the IEEE 802.22, is able to support real-time and non-real-time quality of service classes, provided that wireless microphones temporal activity is moderate (with approximately one wireless microphone per 3,000 inhabitants with light urban population density and short duty cycles). Finally, two-stage spectrum sensing option improves OS-OFDMA throughput, provided that the length of spectrum sensing at every stage is optimized using our model

Contributions to the security of cognitive radio networks

The increasing emergence of wireless applications along with the static spectrum allocation followed by regulatory bodies has led to a high inefficiency in spectrum usage, and the lack of spectrum for new services. In this context, Cognitive Radio (CR) technology has been proposed as a possible solution to reuse the spectrum being underutilized by licensed services. CRs are intelligent devices capable of sensing the medium and identifying those portions of the spectrum being unused. Based on their current perception of the environment and on that learned from past experiences, they can optimally tune themselves with regard to parameters such as frequency, coding and modulation, among others. Due to such properties, Cognitive Radio Networks (CRNs) can act as secondary users of the spectrum left unused by their legal owners or primary users, under the requirement of not interfering primary communications. The successful deployment of these networks relies on the proper design of mechanisms in order to efficiently detect spectrum holes, adapt to changing environment conditions and manage the available spectrum. Furthermore, the need for addressing security issues is evidenced by two facts. First, as for any other type of wireless network, the air is used as communications medium and can easily be accessed by attackers. On the other hand, the particular attributes of CRNs offer new opportunities to malicious users, ranging from providing wrong information on the radio environment to disrupting the cognitive mechanisms, which could severely undermine the operation of these networks. In this Ph.D thesis we have approached the challenge of securing Cognitive Radio Networks. Because CR technology is still evolving, to achieve this goal involves not only providing countermeasures for existing attacks but also to identify new potential threats and evaluate their impact on CRNs performance. The main contributions of this thesis can be summarized as follows. First, a critical study on the State of the Art in this area is presented. A qualitative analysis of those threats to CRNs already identified in the literature is provided, and the efficacy of existing countermeasures is discussed. Based on this work, a set of guidelines are designed in order to design a detection system for the main threats to CRNs. Besides, a high level description of the components of this system is provided, being it the second contribution of this thesis. The third contribution is the proposal of a new cross-layer attack to the Transmission Control Protocol (TCP) in CRNs. An analytical model of the impact of this attack on the throughput of TCP connections is derived, and a set of countermeasures in order to detect and mitigate the effect of such attack are proposed. One of the main threats to CRNs is the Primary User Emulation (PUE) attack. This attack prevents CRNs from using available portions of the spectrum and can even lead to a Denial of Service (DoS). In the fourth contribution of this the method is proposed in order to deal with such attack. The method relies on a set of time measures provided by the members of the network and allows estimating the position of an emitter. This estimation is then used to determine the legitimacy of a given transmission and detect PUE attacks. Cooperative methods are prone to be disrupted by malicious nodes reporting false data. This problem is addressed, in the context of cooperative location, in the fifth and last contribution of this thesis. A method based on Least Median Squares (LMS) fitting is proposed in order to detect forged measures and make the location process robust to them. The efficiency and accuracy of the proposed methodologies are demonstrated by means of simulation

A new cross-layer dynamic spectrum access architecture for TV White Space cognitive radio applications

As evermore applications and services are developed for wireless devices, the dramatic growth in user data traffic has led to the legacy channels becoming congested with the corresponding imperative of requiring more spectra. This has motivated both regulatory bodies and commercial companies to investigate strategies to increase the efficiency of the existing spectrum. With the emergence of cognitive radio technology, and the transference of TV channels from analogue to digital platforms, a unique opportunity to exploit spectrum by mobile digital service providers has emerged, commonly referred to as TV White Space (TVWS). One of the challenges in utilising TVWS spectrum is reliable primary user (PU) detection which is essential as any unlicensed secondary user has no knowledge of the PU and thereby can generate interference. This paper addresses the issue of PU detection by introducing a new dynamic spectrum access algorithm that exploits the unique properties of how digital TV (DTV) frequencies are deployed. A fuzzy logic inference model based on an enhanced detection algorithm (EDA) is used to resolve the inherent uncertain nature of DTV signals. Simulation results confirm EDA significantly improves the detection probability of a TVWS channel compared to existing PU detection techniques, while providing consistently low false positive detections. The paper also analyses the impact of the hidden node problem on EDA by modelling representative buildings and proposes a novel solution

A Review of TV White Space Technology and its Deployments in Africa

The emergence of bandwidth-driven applications in the current wireless communication environment is driving a paradigm shift from the conventional fixed spectrum assignment policy to intelligent and dynamic spectrum access. Practical demands for efficient spectrum utilization have continued to drive the development of TV white space technology to provide affordable and reliable wireless connectivity. It is envisaged that transition from analogue transmission to Digital Terrestrial Television (DTT) creates more spectrum opportunity for TV white space access and regulatory agencies of many countries had begun to explore this opportunity to address spectrum scarcity. To convey the evolutionary trends in the development of TV white space technology, this paper presents a comprehensive review on the contemporary approaches to TV white space technology and practical deployments of pilot projects in Africa. The paper outlines the activities in TV white space technology, which include regulations and standardization, commercial trials, research challenges, open issues and future research directions. Furthermore, it also provides an overview of the current industrial trends in TV white space technology which demonstrates that cognitive radio as an enabling technology for TV white space technology

Spectrum sensing in cognitive radio:use of cyclo-stationary detector

Cognitive radio allows unlicensed users to access licensed frequency bands through dynamic spectrum access so as to reduce spectrum scarcity. This requires intelligent spectrum sensing techniques like co-operative sensing which makes use of information from number of users. This thesis investigates the use of cyclo-stationary detector and its simulation in MATLAB for licensed user detection. Cyclo-stationary detector enables operation under low SNR conditions and thus saves the need for consulting more number of users. Simulation results show that implementing co-operative spectrum sensing help in better performance in terms of detection. The cyclo-stationary detector is used for performance evaluation for Digital Video Broadcast-Terrestrial (DVB-T) signals. Generally, DVB-T is specified in IEEE 802.22 standard (first standard based on cognitive radio) in VHF and UHF TV broadcasting spectrum. The thesis is further extended to find the number of optimal users in a scenario to optimize the detection probability and reduce overhead leading to better utilization of resources. The gradient descent algorithm and the particle swarm optimization (PSO) technique are put to use to find an optimum value of threshold. The performance for both these schemes is evaluated to find out which fares better

Evaluation of blind sensing techniques in multiple wireless microphones environments

This work focuses on the evaluation of blind sensing techniques for the detection of multiple wireless microphones in the UHF band, by means of simulation. The metrics used for the comparisons include probability of detection, probability of false alarm and minimum SNR detected for a given observation time. As an example, simulation results showed that blind detection algorithms can sense multiple wireless microphone signals with SNR = -19 dB, in a Rayleigh channel environment, considering 100 ms sensing time, 90 % probability of detection and 10 % probability of false alarm. In these conditions, blind detection techniques suffer maximum SNR degradation of 3.5 dB, as compared with single wireless microphone scenarios.info:eu-repo/semantics/publishedVersio

Cognitive Radio and TV White Space (TVWS) Applications

As more user applications emerge for wireless devices, the corresponding amount of traffic is rapidly expanding, with the corollary that ever-greater spectrum capacity is required. Service providers are experiencing deployment blockages due to insufficient bandwidth being available to accommodate such devices. TV White Space (TVWS) represents an opportunity to supplement existing licensed spectrum by exploiting unlicensed resources. TVWS spectrum has materialised from the unused TV channels in the switchover from analogue to digital platforms. The main obstacles to TVWS adoption are reliable detection of primary users (PU) i.e., TV operators and consumers, allied with specifically, the hidden node problem. This chapter presents a new Generalised Enhanced Detection Algorithm (GEDA) that exploits the unique way Digital Terrestrial TV (DTT) channels are deployed in different geographical areas. GEDA effectively transforms an energy detector into a feature sensor to achieve significant improvements in detection probability of a DTT PU. Furthermore, by framing a novel margin strategy utilising a keep out contour, the hidden node issue is resolved, and a viable secondary user sensing solution formulated. Experimental results for a cognitive radio TVWS model have formalised both the bandwidth and throughput gains secured by TVWS users with this new paradigm

Cognitive Radio Networks: Realistic or Not?

A large volume of research has been conducted in the cognitive radio (CR) area the last decade. However, the deployment of a commercial CR network is yet to emerge. A large portion of the existing literature does not build on real world scenarios, hence, neglecting various important interactions of the research with commercial telecommunication networks. For instance, a lot of attention has been paid to spectrum sensing as the front line functionality that needs to be completed in an efficient and accurate manner to enable an opportunistic CR network architecture. This is necessary to detect the existence of spectrum holes without which no other procedure can be fulfilled. However, simply sensing (cooperatively or not) the energy received from a primary transmitter cannot enable correct dynamic spectrum access. For example, the low strength of a primary transmitter's signal does not assure that there will be no interference to a nearby primary receiver. In addition, the presence of a primary transmitter's signal does not mean that CR network users cannot access the spectrum since there might not be any primary receiver in the vicinity. Despite the existing elegant and clever solutions to the DSA problem no robust, implementable scheme has emerged. In this paper, we challenge the basic premises of the proposed schemes. We further argue that addressing the technical challenges we face in deploying robust CR networks can only be achieved if we radically change the way we design their basic functionalities. In support of our argument, we present a set of real-world scenarios, inspired by realistic settings in commercial telecommunications networks, focusing on spectrum sensing as a basic and critical functionality in the deployment of CRs. We use these scenarios to show why existing DSA paradigms are not amenable to realistic deployment in complex wireless environments.Comment: Work in progres