Spectrum Adaptation in Cognitive Radio Systems with Operating Constraints

The explosion of high-data-rate-demanding wireless applications such as smart-phones and wireless Internet access devices, together with growth of existing wireless services, are creating a shortage of the scarce Radio Frequency (RF) spectrum. However, several spectrum measurement campaigns revealed that current spectrum usage across time and frequency is inefficient, creating the artificial shortage of the spectrum because of the traditional exclusive command-and-control model of using the spectrum. Therefore, a new concept of Cognitive Radio (CR) has been emerging recently in which unlicensed users temporarily borrow spectrum from the licensed Primary Users (PU) based on the Dynamic Spectrum Access (DSA) technique that is also known as the spectrum sharing concept. A CR is an intelligent radio system based on the Software Defined Radio platform with artificial intelligence capability which can learn, adapt, and reconfigure through interaction with the operating environment. A CR system will revolutionize the way people share the RF spectrum, lowering harmful interference to the licensed PU of the spectrum, fostering innovative DSA technology and giving people more choices when it comes to using the wireless-communication-dependent applications without having any spectrum congestion problems. A key technical challenge for enabling secondary access to the licensed spectrum adaptation is to ensure that the CR does not interfere with the licensed incumbent users. However, incumbent user behavior is dynamic and requires CR systems to adapt this behavior in order to maintain smooth information transmission. In this context, the objective of this dissertation is to explore design issues for CR systems focusing on adaptation of physical layer parameters related to spectrum sensing, spectrum shaping, and rate/power control. Specifically, this dissertation discusses dynamic threshold adaptation for energy detector spectrum sensing, spectrum allocation and power control in Orthogonal Frequency Division Multiplexing-(OFDM-)based CR with operating constraints, and adjacent band interference suppression techniques in turbo-coded OFDM-based CR systems

Market Mechanisms Towards Secondary Spectrum Usage

Widespread adoption of smartphones, tablets and other smart devices has resulted in mobile operators (MOs) making a transition from voice to data centric business model. As a consequence there has been an increase in demand for radio spectrum. Spectrum availability in the future can be a cause of concern, the main reason of which is being attributed to the traditional and inflexible approach towards spectrum management. Hence it is required to overhaul the existing spectrum management techniques and adopt those models which aim at higher spectrum utilization. As part of our research methodology we first perform a state-of-the-art review on secondary usage of radio spectrum. We observe that most research assumes a clean slate approach towards the emergence of secondary spectrum markets which are typically designed with an underlying assumption of participating actors being of homogeneous type. In contrast with above we take an evolutionary approach while designing market mechanisms towards heterogeneous secondary usage of spectrum. The evolution of trading markets is reflected in the incremental steps used in our research, i.e. starting from Wireless Fidelity (Wi-Fi IEEE 802.11) capacity markets, followed by super Wi-Fi (IEEE 802.11af) capacity markets and finally TV White Spaces (TVWS) spectrum leasing markets. We make use of Value Network Configuration (VNC) methodology for illustrating the design of market mechanism and further evaluate the designed mechanism using Agent Based Modeling (ABM). Based on our simulation results we observe that a generic trade-off exist between the length of lease time, trade facilitation cost and the extent of trading activity within the markets. We also observe that there exists an optimal range of lease time for which all the market players find themselves in economically favourable situation. We compare super Wi-Fi capacity markets and TVWS spectrum leasing markets over performance of MOs and TV broadcasters and according to our evaluation local area strategy seems to offer more benefits for TVWS spectrum usage

A DYNAMIC SPECTRUM ACCESS OPTIMIZATION MODEL FOR COGNITIVE RADIO WIRELESS SENSOR NETWORK

The availability of low cost and tiny sensor devices have resulted in increased adoption of wireless sensor network (WSN) in various industries and organization. The WSN is expected to play a significant role in future internet based application services. WSN has been adopted in healthcare, disaster management, environment monitoring and so on. The low-cost availability of smart devices has led to increased use of wireless devices such as Bluetooth, Wi-Fi etc. Therefore, cognitive radio network plays a significant role in handling spectrum efficiently. The emerging internet access technology such as 4G and 5G network which is expected to come in near future is going to make cognitive spectrum access more challenging. The existing cognitive radio based WSN is not efficient in utilizing spectrum. They induce high collision due to interference and improper channel state information. To address, this work present an efficient distributed opportunistic spectrum access for wireless sensor network. The channel availability of likelihood distribution is computed using continuous-time Markov chain considering primary transmitting users temporal channel usage channel pattern and spatial distribution. The simulation outcome shows the proposed model achieves significant performance improvement over existing model. The proposed model improves the overall spectrum efficiency of cognitive radio wireless sensor network in terms of throughput, packet transmission and collision

Information reuse in dynamic spectrum access

Dynamic spectrum access (DSA), where the permission to use slices of radio spectrum is dynamically shifted (in time an in different geographical areas) across various communications services and applications, has been an area of interest from technical and public policy perspectives over the last decade. The underlying belief is that this will increase spectrum utilization, especially since many spectrum bands are relatively unused, ultimately leading to the creation of new and innovative services that exploit the increase in spectrum availability. Determining whether a slice of spectrum, allocated or licensed to a primary user, is available for use by a secondary user at a certain time and in a certain geographic area is a challenging task. This requires 'context information' which is critical to the operation of DSA. Such context information can be obtained in several ways, with different costs, and different quality/usefulness of the information. In this paper, we describe the challenges in obtaining this context information, the potential for the integration of various sources of context information, and the potential for reuse of such information for related and unrelated purposes such as localization and enforcement of spectrum sharing. Since some of the infrastructure for obtaining finegrained context information is likely to be expensive, the reuse of this infrastructure/information and integration of information from less expensive sources are likely to be essential for the economical and technological viability of DSA. © 2013 IEEE