From Sensing to Predictions and Database Technique: A Review of TV White Space Information Acquisition in Cognitive Radio Networks

Strategies to acquire white space information is the single most significant functionality in cognitive radio networks (CRNs) and as such, it has gone some evolution to enhance information accuracy. The evolution trends are spectrum sensing, prediction algorithm and recently, geo‐location database technique. Previously, spectrum sensing was the main technique for detecting the presence/absence of a primary user (PU) signal in a given radio frequency (RF) spectrum. However, this expectation could not materialized as a result of numerous technical challenges ranging from hardware imperfections to RF signal impairments. To convey the evolutionary trends in the development of white space information, we present a survey of the contemporary advancements in PU detection with emphasis on the practical deployment of CRNs i.e. Television white space (TVWS) networks. It is found that geo‐location database is the most reliable technique to acquire TVWS information although, it is financially driven. Finally, using financially driven database model, this study compared the data‐rate and spectral efficiency of FCC and Ofcom TV channelization. It was discovered that Ofcom TV channelization outperforms FCC TV channelization as a result of having higher spectrum bandwidth. We proposed the adoption of an allinclusive TVWS information acquisition model as the future research direction for TVWS information acquisition techniques

Spectrum sensing and occupancy prediction for cognitive machine-to-machine wireless networks

A thesis submitted to the University of Bedfordshire, in partial fulfil ment of the requirements for the degree of Doctor of Philosophy (PhD)The rapid growth of the Internet of Things (IoT) introduces an additional challenge to the existing spectrum under-utilisation problem as large scale deployments of thousands devices are expected to require wireless connectivity. Dynamic Spectrum Access (DSA) has been proposed as a means of improving the spectrum utilisation of wireless systems. Based on the Cognitive Radio (CR) paradigm, DSA enables unlicensed spectrum users to sense their spectral environment and adapt their operational parameters to opportunistically access any temporally unoccupied bands without causing interference to the primary spectrum users. In the same context, CR inspired Machine-to-Machine (M2M) communications have recently been proposed as a potential solution to the spectrum utilisation problem, which has been driven by the ever increasing number of interconnected devices. M2M communications introduce new challenges for CR in terms of operational environments and design requirements. With spectrum sensing being the key function for CR, this thesis investigates the performance of spectrum sensing and proposes novel sensing approaches and models to address the sensing problem for cognitive M2M deployments. In this thesis, the behaviour of Energy Detection (ED) spectrum sensing for cognitive M2M nodes is modelled using the two-wave with dffi use power fading model. This channel model can describe a variety of realistic fading conditions including worse than Rayleigh scenarios that are expected to occur within the operational environments of cognitive M2M communication systems. The results suggest that ED based spectrum sensing fails to meet the sensing requirements over worse than Rayleigh conditions and consequently requires the signal-to-noise ratio (SNR) to be increased by up to 137%. However, by employing appropriate diversity and node cooperation techniques, the sensing performance can be improved by up to 11.5dB in terms of the required SNR. These results are particularly useful in analysing the eff ects of severe fading in cognitive M2M systems and thus they can be used to design effi cient CR transceivers and to quantify the trade-o s between detection performance and energy e fficiency. A novel predictive spectrum sensing scheme that exploits historical data of past sensing events to predict channel occupancy is proposed and analysed. This approach allows CR terminals to sense only the channels that are predicted to be unoccupied rather than the whole band of interest. Based on this approach, a spectrum occupancy predictor is developed and experimentally validated. The proposed scheme achieves a prediction accuracy of up to 93% which in turn can lead to up to 84% reduction of the spectrum sensing cost. Furthermore, a novel probabilistic model for describing the channel availability in both the vertical and horizontal polarisations is developed. The proposed model is validated based on a measurement campaign for operational scenarios where CR terminals may change their polarisation during their operation. A Gaussian approximation is used to model the empirical channel availability data with more than 95% confi dence bounds. The proposed model can be used as a means of improving spectrum sensing performance by using statistical knowledge on the primary users occupancy pattern

Empirical Study on Performance Evaluation Between Long Term Evolution (LTE), Third Generation (3G) and TV White Space Availability for Wireless Campus Network

Abstract—University campuses are increasingly relying on wireless communication as the preferred media to access the web. Hence, there is a need to conduct on site performance evaluation on the existing wireless standards with the view of analyzing their expected and actual performance. In this paper, a drive-test was performed on three (3) wireless standards of LTE Release 8, 3G and Television White Space (TVWS). The drive-test was performed in both in-building and outdoor environments in a sub-urban campus settings. Results from LTE Release 8, 3G indicate that user mobility affects the received user throughput and Reference Signal Strength Indicator (RSSI). The test cases are executed by using a real LTE user equipment, equipped with ASCOM’s TEMS software on a live 3G and 4G mobile networks for the both Malaysian mobile service providers; Maxis and Celcom. The results showed sufficient coverage within the campus area from both operators. On the other hand, results from field experiment indicate that TVWS is available on the campus. TVWS presents significant new opportunities within the context of emerging 4G networks for deploying new wireless access technology capable of meeting students expectation in terms of throughput and increasing broadband access for the fraction when the legacy 4G networks experience coverage blackout

A survey of measurement-based spectrum occupancy modeling for cognitive radios

Spectrum occupancy models are very useful in cognitive radio designs. They can be used to increase spectrum sensing accuracy for more reliable operation, to remove spectrum sensing for higher resource usage efficiency, or to select channels for better opportunistic access, among other applications. In this survey, various spectrum occupancy models from measurement campaigns taken around the world are investigated. These models extract different statistical properties of the spectrum occupancy from the measured data. In addition to these models, spectrum occupancy prediction is also discussed, where autoregressive and/or moving-average models are used to predict the channel status at future time instants. After comparing these different methods and models, several challenges are also summarized based on this survey

From Sensing to Predictions and Database Technique: A Review of TV White Space Information Acquisition in Cognitive Radio Networks

Strategies to acquire white space information is the single most significant functionality in cognitive radio networks (CRNs) and as such, it has gone some evolution to enhance information accuracy. The evolution trends are spectrum sensing, prediction algorithm and recently, geo-location database technique. Previously, spectrum sensing was the main technique for detecting the presence/absence of a primary user (PU) signal in a given radio frequency (RF) spectrum. However, this expectation could not materialized as a result of numerous technical challenges ranging from hardware imperfections to RF signal impairments. To convey the evolutionary trends in the development of white space information, we present a survey of the contemporary advancements in PU detection with emphasis on the practical deployment of CRNs i.e. Television white space (TVWS) networks. It is found that geo-location database is the most reliable technique to acquire TVWS information although, it is financially driven. Finally, using financially driven database model, this study compared the data-rate and spectral efficiency of FCC and Ofcom TV channelization. It was discovered that Ofcom TV channelization outperforms FCC TV channelization as a result of having higher spectrum bandwidth. We proposed the adoption of an all-inclusive TVWS information acquisition model as the future research direction for TVWS information acquisition techniques

Channel Selection Algorithms for Cognitive Radio Systems

The Spectrum of Radio Frequency plays a key/central role in supporting the operation of the whole range of mobile wireless devices. Such centrality derives from the fact it is necessary when operating different technologies, such as TV, cellular networks, and satellite transmissions, among others. Hence, the urgent need to design a better management of these technologies as a means of minimizing the amount spectrum that is used. This study was developed in two different stages. During a preliminary stage we came up with a modelling method of the service time duration in cognitive radio networks, which fosters a better management of the spectrum through its opportunistic use. In a second stage, we propose four algorithms to manage these cognitive radio networks, using the modelling method that was defined in the first stage, as a basis. After implementing all the simulations, it was possible to verify the feasibility of this modelling methodology and also to confirm the expected results. It should also be pointed out that the four suggested algorithms were tested by carrying out simulations, being effective solutions for difference operational scenarios

DISTRIBUTED INTELLIGENT SPECTRUM MANAGEMENT IN COGNITIVE RADIO AD HOC NETWORKS

The rapid growth of the number of wireless devices has brought an exponential increase in the demand of the radio spectrum. However, according to the Federal Communications Commission (FCC), almost all the radio spectrum for wireless com- munications has already been allocated. In addition, according to FCC, up to 85% of the allocated spectrum is underutilized due to the current fixed spectrum alloca- tion policy. To alleviate the spectrum scarcity problem, FCC has suggested a new paradigm for dynamically accessing the allocated spectrum. Cognitive radio (CR) technology has emerged as a promising solution to realize dynamic spectrum access (DSA). With the capability of sensing the frequency bands in a time and location- varying spectrum environment and adjusting the operating parameters based on the sensing outcome, CR technology allows an unlicensed user to exploit the licensed channels which are not used by licensed users in an opportunistic manner. In this dissertation, distributed intelligent spectrum management in CR ad hoc networks is explored. In particular, four spectrum management issues in CR ad hoc networks are investigated: 1) distributed broadcasting in CR ad hoc networks; 2) distributed optimal HELLO message exchange in CR ad hoc networks; 3) distributed protocol to defend a particular network security attack in CR ad hoc networks; and 4) distributed spectrum handoff protocol in CR ad hoc networks. The research in this dissertation has fundamental impact on CR ad hoc network establishment, net- work functionality, network security, and network performance. In addition, many of the unique challenges of distributed intelligent spectrum management in CR ad hoc networks are addressed for the first time in this dissertation. These challenges are extremely difficult to solve due to the dynamic spectrum environment and they have significant effects on network functionality and performance. This dissertation is essential for establishing a CR ad hoc network and realizing networking protocols for seamless communications in CR ad hoc networks. Furthermore, this dissertation provides critical theoretical insights for future designs in CR ad hoc networks