Due to the rapid development of wireless communications together with the inflexibility of the current spectrum allocation policy, radio spectrum becomes more and more exhausted. One of the critical challenges of wireless communication systems is to efficiently utilize the limited frequency resources to be able to support the growing demand of high data rate wireless services. As a promising solution, cognitive radios have been suggested to deal with the scarcity and under-utilization of radio spectrum. The basic idea behind cognitive radios is to allow unlicensed users, also called secondary users (SUs), to access the licensed spectrum of primary users (PUs) which improves spectrum utilization. In order to not degrade the performance of the primary networks, SUs have to deploy interference control, interference mitigating, or interference avoidance techniques to minimize the interference incurred at the PUs. Cognitive radio networks (CRNs) have stimulated a variety of studies on improving spectrum utilization. In this context, this thesis has two main objectives. Firstly, it investigates the performance of single hop CRNs with spectrum sharing and opportunistic spectrum access. Secondly, the thesis analyzes the performance improvements of two hop cognitive radio networks when incorporating advanced radio transmission techniques. The thesis is divided into three parts consisting of an introduction part and two research parts based on peer-reviewed publications. Fundamental background on radio propagation channels, cognitive radios, and advanced radio transmission techniques are discussed in the introduction. In the first research part, the performance of single hop CRNs is analyzed. Specifically, underlay spectrum access using M/G/1/K queueing approaches is presented in Part I-A while dynamic spectrum access with prioritized traffics is studied in Part I-B. In the second research part, the performance benefits of integrating advanced radio transmission techniques into cognitive cooperative radio networks (CCRNs) are investigated. In particular, opportunistic spectrum access for amplify-and-forward CCRNs is presented in Part II-A where collaborative spectrum sensing is deployed among the SUs to enhance the accuracy of spectrum sensing. In Part II-B, the effect of channel estimation error and feedback delay on the outage probability and symbol error rate (SER) of multiple-input multiple-output CCRNs is investigated. In Part II-C, adaptive modulation and coding is employed for decode-and-forward CCRNs to improve the spectrum efficiency and to avoid buffer overflow at the relay. Finally, a hybrid interweave-underlay spectrum access scheme for a CCRN is proposed in Part II-D. In this work, the dynamic spectrum access of the PUs and SUs is modeled as a Markov chain which then is utilized to evaluate the outage probability, SER, and outage capacity of the CCRN.

Cognitive radio technology that enables dynamic spectrum access has been a promising solution for the spectrum scarcity problem. Cognitive radio networks enable the communication on both licensed and unlicensed channels, having the potential to better solve the interference and collision issues. Channel assignment is of great importance in cognitive radio networks. When operating on licensed channels, the objective is to exploit spectrum holes through cognitive communication, giving priority to the primary users. In this dissertation, we focus on the development of efficient channel assignment algorithms and protocols to improve network performance for cognitive radio wireless networks. The first contribution is on channel assignment for cognitive radio wireless sensor networks aiming to provide robust topology control, as well as to increase network throughput and data delivery rate. The approach is then extended to specific cognitive radio network applications achieving improved performances. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

Thesis (MSc.) -- University of Limpopo, 2018 / A Major concern in the past years was the traditional static spectrum allocation which gave rise to spectrum underutilization and scarcity in wireless networks. In an attempt to solve this problem, cognitive radios technology was proposed and this allows a spectrum to be accessed dynamically by Cognitive radio users or secondary users (SUs). Dynamic access can efficiently be achieved by making necessary adjustment to some MAC layer functionalities such as sensing and channel allocation. MAC protocols play a central role in scheduling sensing periods and channel allocation which ensure that the interference is reduced to a tolerable level. In order to improve the accuracy of sensing algorithm, necessary adjustments should be made at MAC layer. Sensing delays and errors are major challenges in the design of a more accurate spectrum sensing algorithm or MAC protocol. Proposed in this study, is a scheme (EXGPCSA) which incorporate sensing at the MAC layer and physical layer. Energy detector was used to detect the presence of primary users (SU). A choice of how long and how often to sense the spectrum was addressed at the MAC layer. The focal point of this study was on minimizing delays in finding available channels for transmission. EXGPCSA used channel grouping technique to reduce delays. Channels were divided into two groups and arranged in descending order of their idling probabilities. Channels with higher probabilities were selected for sensing. Three network scenarios were considered wherein a group of SUs participated in sensing and sharing their spectral observations. EXGPCSA was designed such that only SUs with higher SNR were allowed to share their observations with other neighbouring SUs. This rule greatly minimized errors in sensing. The efficiency of EXGPCSA was evaluated by comparing it to another scheme called generalized predictive CSA. A statistical t-test was used to test if there is significant difference between EXGPCSA and generalized predictive CSA in terms of average throughput. A test has shown that EXGPCSA significantly performed better than generalized predictive CSA. Both schemes were simulated using MATLAB R2015a in three different network scenarios.

We develop efficient coordination techniques that support inelastic traffic in large-scale distributed dynamic spectrum access DSA networks. By means of any learning algorithm, the proposed techniques enable DSA users to locate and exploit spectrum opportunities effectively, thereby increasing their achieved throughput (or "rewards" to be more general). Basically, learning algorithms allow DSA users to learn by interacting with the environment, and use their acquired knowledge to select the proper actions that maximize their own objectives, thereby "hopefully" maximizing their long-term cumulative received reward/throughput. However, when DSA users' objectives are not carefully coordinated, learning algorithms can lead to poor overall system performance, resulting in lesser per-user average achieved rewards. In this thesis, we derive efficient objective functions that DSA users an aim to maximize, and that by doing so, users' collective behavior also leads to good overall system performance, thus maximizing each user's long-term cumulative received rewards. We show that the proposed techniques are: (i) efficient by enabling users to achieve high rewards, (ii) scalable by performing well in systems with a small as well as a large number of users, (iii) learnable by allowing users to reach up high rewards very quickly, and (iv) distributive by being implementable in a decentralized manner. / Graduation date: 2013

In the last decade, the world has witnessed rapid increasing applications of wireless networks. However, with the fixed spectrum allocation policy that has been used since the beginning of the spectrum regulation to assign different spectrum bands to different wireless applications, it has been observed that most of the allocated spectrum bands are underutilized. Therefore, if these bands can be opportunistically used by new emerging wireless networks, the spectrum scarcity can be resolved. Cognitive Radio (CR) is a revolutionary and promising technology that can identify and then exploit the spectrum opportunities. In Cognitive Radio Networks (CRNs), the spectrum can be utilized by two kinds of users: Primary Users (PUs) having exclusive licenses to use certain spectrum bands for specific wireless applications, and Secondary Users (SUs) having no spectrum licenses but seeking for any spectrum opportunities. The SUs can make use of the licensed unused spectrum if they do not make any harmful interference to the PUs. However, the variation of the spectrum availability over the time and locations, due to the coexistence with the PUs, and the spread of the spectrum opportunities over wide spectrum bands create a unique trait of the CRNs. This key trait poses great challenges in different aspects of the radio resource management in CRNs such as the spectrum sensing, spectrum access, admission control, channel allocation, Quality-of-Service (QoS) provisioning, etc. In this thesis, we study the resource management of both single-hop and multi-hop CRNs. Since most of the new challenges in CRNs can be tackled by designing an efficient Medium Access Control (MAC) framework, where the solutions of these challenges can be integrated for efficient resource management, we firstly propose a novel MAC framework that integrates a kind of cooperative spectrum sensing method at the physical layer into a cooperative MAC protocol considering the requirements of both the SUs and PUs. For spectrum identification, a computationally simple but efficient sensing algorithm is developed, based on an innovative deterministic sensing policy, to assist each sensing user for identifying the optimum number of channels to sense and the optimum sensing duration. We then develop an admission control scheme and channel allocation policy that can be integrated in the proposed MAC framework to regulate the number of sensing users and number of access users; therefore, the spectrum identification and exploitation can be efficiently balanced. Moreover, we propose a QoS-based spectrum allocation framework that jointly considers the QoS provisioning for heterogeneous secondary Real-Time (RT) and Non-Real Time (NRT) users with the spectrum sensing, spectrum access decision, and call admission control. We analyze the proposed QoS-based spectrum allocation framework and find the optimum numbers of the RT and NRT users that the network can support. Finally, we introduce an innovative user clustering scheme to efficiently manage the spectrum identification and exploitation in multi-hop ad hoc CRNs. We group the SUs into clusters based on their geographical locations and occurring times and use spread spectrum techniques to facilitate using one frequency for the Common Control Channels (CCCs) of the whole secondary network and to reduce the co-channel interference between adjacent clusters by assigning different spreading codes for different clusters. The research results presented in this thesis contribute to realize the concept of the CRNs by developing a practical MAC framework, spectrum sensing, spectrum allocation, user admission control, and QoS provisioning for efficient resource management in these promising networks.

The objective of the research is to develop analog spectrum processing techniques for cognitive radio (CR) applications in CMOS technology. CR systems aim to use the unoccupied spectrum allocations without any license when the primary users are not present. Therefore, the successful deployment of CR systems relies on their ability to accurately sense the spectrum usage status over a wide frequency range serving various wireless communication standards. Meanwhile, to maximize the utilization of the available spectrum segments, the bandwidth of the signal has to be highly flexible, so that even a small fraction of spectrum resources can be fully utilized by CR users. One of the key enabling technologies of variable bandwidth communication is a tunable baseband filter. In this research, a reconfigurable CR testbed system is presented as groundwork for the researches related with CR systems. With the feasibility study on the multi-resolution spectrum sensing (MRSS) functionality, a method for determining sensing threshold for MRSS functionality is presented, and a fully integrated MRSS receiver in CMOS technology is demonstrated. On the other hand, a reconfigurable CMOS analog baseband filter which can change its bandwidth, type and order with high resolution for CR applications is presented. In sum, an analog spectrum sensing method as well as a highly flexible analog baseband filter architecture is established and implemented in CMOS technology. Both designs are targeting the utilization of the analog signal processing capability with the aid of the digital circuits.

Cognitive radio (CR) technology has recently been introduced to opportunistically exploit the spectrum. We present a robust and cost-effective design to ensure the improvement of spectrum efficiency with CR. We first propose probability-based spectrum sensing by utilizing the statistical characteristics of licensed channel occupancy, which achieves nearly optimal performance with relatively low complexity. Based on the statistical model, we then propose periodic spectrum sensing scheduling to determine the optimal inter-sensing duration and vary the transmit power at each data sample to enhance throughput and reduce interference. We further develop a probability-based scheme for combination of local sensing information collected from cooperative CR users, which enables combination of both synchronous and asynchronous sensing information. To satisfy the stringent bandwidth constraint for reporting, we also propose to simultaneously send local sensing data to a combining node through the same narrowband channel. With proper preprocessing at individual users, such a design maintains reasonable detection performance while the bandwidth required for reporting does not change with the number of cooperative users. To better utilize the spectrum and avoid possible interference, we propose spectrum shaping schemes based on spectral precoding, which enable efficient spectrum sharing between CR and licensed users and exhibit the advantages of both simplicity and flexibility. We also propose a novel resource allocation approach based on the probabilities of licensed channel availability obtained from spectrum sensing. Different from conventional approaches, the probabilistic approach exploits the flexibility of CR to ensure efficient spectrum usage and protect licensed users from unacceptable interference.

In this thesis we have considered a cognitive radio network (CRN) with a pair of primary user (PU) and secondary user (SU) in spectrum sharing networks in path-loss and without path-loss propagation environments under identically distributed m-Nakagami fading channel. The thesis consists of three parts. In the first part we propose an optimized Takagi-Sugeno Fuzzy Inference System (FIS) based power control strategy in cognitive radio networks (CRN) in spectrum sharing network in without path-loss propagation environment. The second part proposes an optimized Takagi-Sugeno FIS based power control strategy in cognitive radio networks in spectrum sharing network in path-loss propagation environment. For without path-loss propagation environment the proposed FIS takes the interference channel gain ratio between SU transmitter (CUtx) and PU receiver (PUrx) and Signal to Noise Ratio (SNR) towards PU transmitter (PUtx) as antecedents and outputs the power scaling factor for SU. For path-loss propagation environment the proposed FIS takes the relative distance ratio between CUtx and PUrx and SNR towards PUtx as antecedents and outputs the power scaling factor for SU. The output power scaling factor is used to vary the transmit power of SU such that it does not degrade the quality of service (QoS) of PU link. The third part presents an implementation of orthogonal frequency division multiplexing (OFDM) transmission technique in CRN. The OFDM technique has intellectual attractive features like coping with the inter symbol interference (ISI), while providing increasing spectral efficiency and improved performance. This can be used in emergency conditions where transmission requires reliability and high data rate. The OFDM transmission technique is applied towards SU transmitter in CRN, which enables SU to utilize the spectrum efficiently under various fading environments. Spectrum sharing networks in with and without path-loss propagation environments and OFDM transmission were tested for bit error rate (BER) performance after fading effects from m-Nakagami fading channel. We conclude that by applying Takagi-Sugeno Fuzzy Inference System (FIS) based power control strategy we can improve the BER performance of PU when compared with no power control strategy and with other fuzzy based power control technique. OFDM transmission technique gives us better data rate and slightly improved BER in CRN hence making it suitable for use in emergency conditions. / mobile: 0735032048 (Muneeb Goraya)

In the last decade, the world has witnessed rapid increasing applications of wireless networks. However, with the fixed spectrum allocation policy that has been used since the beginning of the spectrum regulation to assign different spectrum bands to different wireless applications, it has been observed that most of the allocated spectrum bands are underutilized. Therefore, if these bands can be opportunistically used by new emerging wireless networks, the spectrum scarcity can be resolved. Cognitive Radio (CR) is a revolutionary and promising technology that can identify and then exploit the spectrum opportunities. In Cognitive Radio Networks (CRNs), the spectrum can be utilized by two kinds of users: Primary Users (PUs) having exclusive licenses to use certain spectrum bands for specific wireless applications, and Secondary Users (SUs) having no spectrum licenses but seeking for any spectrum opportunities. The SUs can make use of the licensed unused spectrum if they do not make any harmful interference to the PUs. However, the variation of the spectrum availability over the time and locations, due to the coexistence with the PUs, and the spread of the spectrum opportunities over wide spectrum bands create a unique trait of the CRNs. This key trait poses great challenges in different aspects of the radio resource management in CRNs such as the spectrum sensing, spectrum access, admission control, channel allocation, Quality-of-Service (QoS) provisioning, etc. In this thesis, we study the resource management of both single-hop and multi-hop CRNs. Since most of the new challenges in CRNs can be tackled by designing an efficient Medium Access Control (MAC) framework, where the solutions of these challenges can be integrated for efficient resource management, we firstly propose a novel MAC framework that integrates a kind of cooperative spectrum sensing method at the physical layer into a cooperative MAC protocol considering the requirements of both the SUs and PUs. For spectrum identification, a computationally simple but efficient sensing algorithm is developed, based on an innovative deterministic sensing policy, to assist each sensing user for identifying the optimum number of channels to sense and the optimum sensing duration. We then develop an admission control scheme and channel allocation policy that can be integrated in the proposed MAC framework to regulate the number of sensing users and number of access users; therefore, the spectrum identification and exploitation can be efficiently balanced. Moreover, we propose a QoS-based spectrum allocation framework that jointly considers the QoS provisioning for heterogeneous secondary Real-Time (RT) and Non-Real Time (NRT) users with the spectrum sensing, spectrum access decision, and call admission control. We analyze the proposed QoS-based spectrum allocation framework and find the optimum numbers of the RT and NRT users that the network can support. Finally, we introduce an innovative user clustering scheme to efficiently manage the spectrum identification and exploitation in multi-hop ad hoc CRNs. We group the SUs into clusters based on their geographical locations and occurring times and use spread spectrum techniques to facilitate using one frequency for the Common Control Channels (CCCs) of the whole secondary network and to reduce the co-channel interference between adjacent clusters by assigning different spreading codes for different clusters. The research results presented in this thesis contribute to realize the concept of the CRNs by developing a practical MAC framework, spectrum sensing, spectrum allocation, user admission control, and QoS provisioning for efficient resource management in these promising networks.

Cognitive Radio technologies have been touted to be instrumental in solving resource-allocation problems in resource-constrained radio environments. The adaptive computational intelligence of these radios facilitates the dynamic allocation of network resources--particularly, the spectrum, a scarce physical asset. In addition to consumer-driven innovation that is governing the wireless communication ecosystem, its associated infrastructure is being increasingly viewed by governments around the world as critical national security interests--the US Military instituted the DARPA Spectrum Collaboration Challenge which requires competitors to design intelligent radios that leverage optimization, A.I., and game-theoretic strategies in order to efficiently access the RF spectrum in an environment wherein every other competitor is vying for the same limited resources. In this work, we detail the design of our radio, i.e., the design choices made in each layer of the network protocol stack, strategies rigorously derived from convex optimization, the collaboration API, and heuristics tailor-made to tackle the unique scenarios emulated in this DARPA Grand Challenge. We present performance evaluations of key components of our radio in a variety of military and disaster-relief deployment scenarios that mimic similar real-world situations. Furthermore, specifically focusing on channel access in the MAC, we formulate the spectrum sensing and access problem as a POMDP; derive an optimal policy using approximate value iteration methods; prove that our strategy outperforms the state-of-the-art, and facilitates means to control the trade-off between secondary network throughput and incumbent interference; and evaluate this policy on an ad-hoc distributed wireless platform constituting ESP32 radios, in order to study its implementation feasibility.