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

Spectrum measurement, sensing, analysis and simulation in the context of cognitive radio

The radio frequency (RF) spectrum is a scarce natural resource, currently regulated locally by national agencies. Spectrum has been assigned to different services and it is very difficult for emerging wireless technologies to gain access due to rigid spectmm policy and heavy opportunity cost. Current spectrum management by licensing causes artificial spectrum scarcity. Spectrum monitoring shows that many frequencies and times are unused. Dynamic spectrum access (DSA) is a potential solution to low spectrum efficiency. In DSA, an unlicensed user opportunistically uses vacant licensed spectrum with the help of cognitive radio. Cognitive radio is a key enabling technology for DSA. In a cognitive radio system, an unlicensed Secondary User (SU) identifies vacant licensed spectrum allocated to a Primary User (PU) and uses it without harmful interference to the PU. Cognitive radio increases spectrum usage efficiency while protecting legacy-licensed systems. The purpose of this thesis is to bring together a group of CR concepts and explore how we can make the transition from conventional radio to cognitive radio. Specific goals of the thesis are firstly the measurement of the radio spectrum to understand the current spectrum usage in the Humber region, UK in the context of cognitive radio. Secondly, to characterise the performance of cyclostationary feature detectors through theoretical analysis, hardware implementation, and real-time performance measurements. Thirdly, to mitigate the effect of degradation due to multipath fading and shadowing, the use of -wideband cooperative sensing techniques using adaptive sensing technique and multi-bit soft decision is proposed, which it is believed will introduce more spectral opportunities over wider frequency ranges and achieve higher opportunistic aggregate throughput.Understanding spectrum usage is the first step toward the future deployment of cognitive radio systems. Several spectrum usage measurement campaigns have been performed, mainly in the USA and Europe. These studies show locality and time dependence. In the first part of this thesis a spectrum usage measurement campaign in the Humber region, is reported. Spectrum usage patterns are identified and noise is characterised. A significant amount of spectrum was shown to be underutilized and available for the secondary use. The second part addresses the question: how can you tell if a spectrum channel is being used? Two spectrum sensing techniques are evaluated: Energy Detection and Cyclostationary Feature Detection. The performance of these techniques is compared using the measurements performed in the second part of the thesis. Cyclostationary feature detection is shown to be more robust to noise. The final part of the thesis considers the identification of vacant channels by combining spectrum measurements from multiple locations, known as cooperative sensing. Wideband cooperative sensing is proposed using multi resolution spectrum sensing (MRSS) with a multi-bit decision technique. Next, a two-stage adaptive system with cooperative wideband sensing is proposed based on the combination of energy detection and cyclostationary feature detection. Simulations using the system above indicate that the two-stage adaptive sensing cooperative wideband outperforms single site detection in terms of detection success and mean detection time in the context of wideband cooperative sensing

EVALUATION OF SPECTRUM OCCUPANCY AND COMPARISON FOR THREE DIFFERENT REGIONS

Radio spectrum is a scarce source and very significant to measure and monitor. The present spectrum must be exploited efficiently since every new application must be allocated to spectrum. With purpose of using the spectrum efficiently, there are worldwide research efforts on dynamic spectrum access. Among these methods, cognitive radio mostly draws attention. In order to carry out dynamic spectrum access studies successfully, available spectrum must be meticulously analyzed. In this paper, spectrum occupancy measurements between 25-3000 MHz frequency bands were made in three different regions (Selçuklu, Karatay, Meram) of Konya, Turkey in outdoors during six months. Obtained data is presented with graphics. The occupancy ratios are %5.12, %4.46 and %4.19 for Selçuklu, Karatay and Meram, respectively

Statistical spectrum occupancy prediction for dynamic spectrum access: a classification

Spectrum scarcity due to inefficient utilisation has ignited a plethora of dynamic spectrum access solutions to accommodate the expanding demand for future wireless networks. Dynamic spectrum access systems allow secondary users to utilise spectrum bands owned by primary users if the resulting interference is kept below a pre-designated threshold. Primary and secondary user spectrum occupancy patterns determine if minimum interference and seamless communications can be guaranteed. Thus, spectrum occupancy prediction is a key component of an optimised dynamic spectrum access system. Spectrum occupancy prediction recently received significant attention in the wireless communications literature. Nevertheless, a single consolidated literature source on statistical spectrum occupancy prediction is not yet available in the open literature. Our main contribution in this paper is to provide a statistical prediction classification framework to categorise and assess current spectrum occupancy models. An overview of statistical sequential prediction is presented first. This statistical background is used to analyse current techniques for spectrum occupancy prediction. This review also extends spectrum occupancy prediction to include cooperative prediction. Finally, theoretical and implementation challenges are discussed

SPECTRUM OCCUPANCY MEASUREMENTS IN NIGERIA: RESULTS AND ANALYSIS

ABSTRACT Cognitive radio paradigm has been identified as the solution to spectrum underutilization. It promises to change the face of spectrum management from planning, allocation and subsequently and most importantly utilization. The present command and control approach in allocating spectrum has been found to be ineffective. This inefficiency has lead to a perceived spectrum scarcity. Spectrum occupancy measurements have disputed this fact; through these measurements it has been found that the spectrum is actually underutilized. Thorough understanding of the allocated spectrum will go a long way towards the successful deployment of cognitive radio paradigm. Currently, several spectrum occupancy measurements have been performed all over the world to ascertain the true behaviour of the allocated spectrum. In this paper, a spectrum occupancy measurement performed in Nigeria is presented. This has become necessary because spectrum occupancy measurement performed in a certain location cannot be extended to other locations. From the results obtained, it has been found there is ample spectrum available. Correlation analyses performed also indicate that spectrum occupancy depends on both time and location. This work will go a long way in the deployment of cognitive radio technology in Nigeria