Cognitive radio networks (CRN) have been tipped as one of the most promising paradigms for next generation wireless communication, due primarily to its huge promise of mitigating the spectrum scarcity challenge. To help achieve this promise, CRN develop mechanisms that permit spectrum spaces to be allocated to, and used by more than one user, either simultaneously or opportunistically, under certain preconditions. However, because of various limitations associated with CRN, spectrum and other resources available for use in CRN are usually very scarce. Developing appropriate models that can efficiently utilise the scarce resources in a manner that is fair, among its numerous and diverse users, is required in order to achieve the utmost for CRN. 'Resource allocation (RA) in CRN' describes how such models can be developed and analysed. In developing appropriate RA models for CRN, factors that can limit the realisation of optimal solutions have to be identified and addressed; otherwise, the promised improvement in spectrum/resource utilisation would be seriously undermined. In this thesis, by a careful examination of relevant literature, the most critical limitations to RA optimisation in CRN are identified and studied, and appropriate solution models that address such limitations are investigated and proffered. One such problem, identified as a potential limitation to achieving optimality in its RA solutions, is the problem of heterogeneity in CRN. Although it is indeed the more realistic consideration, introducing heterogeneity into RA in CRN exacerbates the complex nature of RA problems. In the study, three broad classifications of heterogeneity, applicable to CRN, are identified; heterogeneous networks, channels and users. RA models that incorporate these heterogeneous considerations are then developed and analysed. By studying their structures, the complex RA problems are smartly reformulated as integer linear programming problems and solved using classical optimisation. This smart move makes it possible to achieve optimality in the RA solutions for heterogeneous CRN. Another serious limitation to achieving optimality in RA for CRN is the strictness in the level of permissible interference to the primary users (PUs) due to the activities of the secondary users (SUs). To mitigate this problem, the concept of cooperative diversity is investigated and employed. In the cooperative model, the SUs, by assisting each other in relaying their data, reduce their level of interference to PUs significantly, thus achieving greater results in the RA solutions. Furthermore, an iterative-based heuristic is developed that solves the RA optimisation problem timeously and efficiently, thereby minimising network complexity. Although results obtained from the heuristic are only suboptimal, the gains in terms of reduction in computations and time make the idea worthwhile, especially when considering large networks. The final problem identified and addressed is the limiting effect of long waiting time (delay) on the RA and overall productivity of CRN. To address this problem, queueing theory is investigated and employed. The queueing model developed and analysed helps to improve both the blocking probability as well as the system throughput, thus achieving significant improvement in the RA solutions for CRN. Since RA is an essential pivot on which the CRN's productivity revolves, this thesis, by providing viable solutions to the most debilitating problems in RA for CRN, stands out as an indispensable contribution to helping CRN realise its much-proclaimed promises. / Thesis (PhD)--University of Pretoria, 2017. / Electrical, Electronic and Computer Engineering / PhD / Unrestricted

Cognitive radio technology provides a solution for the spectrum scarcity issue by allowing the unlicensed users which are the cognitive radio devices to share the licensed band with the licensed (primary) users. The abilities of cognitive radio device help the secondary (unlicensed) nodes to observe the licensed band and to adjust their transmission parameters for maintaining the primary communication since in cognitive radio networks, it is essential that the existence of the unlicensed users must not harm the licensed network. Under these circumstances, we consider vertical cooperative transmission where primary transmission is not severely damaged by the secondary interference since each primary pair (transmitter and receiver) selects a neighbor secondary user as a cooperative relay to assist their transmission. Cooperation provides an increase in the signal-tointerference-ratio (SIR) of the primary network which can be harnessed by the secondary network as an additional bandwidth for their communication. We propose three relay selection rules so the influence of the relay’s position over the temporal and spatial correlations can be evaluated for different network conditions. Additionally, we implement primary exclusive region (PER) for each primary pair in the network which covers primary nodes, and all secondary users locate inside the zone become inactive. According to the outage model proposed in paper [2], temporal and spatial correlations are assumed to be 1 and 0 respectively; however it is estimated that regarding the environmental factors and the relay’s location, these correlation values may vary. This thesis work is based on the validation of the assumptions provided in paper [2] and our results demonstrate that the temporal and spatial correlation values changes under different circumstances and with different relay selection rules. The simulation results also show that PER significantly stimulates the cooperation performance thereby increases the transmission quality of the primary network.

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A Cognitive Radio Network (CRN) is a technology that allows unlicensed users to utilise licensed spectrum by detecting an idle band through sensing. How- ever, most research studies on CRNs have been carried out without considering the impact of sensing on the performance and security of CRNs. Sensing is essential for secondary users (SUs) to get hold of free band without interfering with the signal generated by primary users (PUs). However, excessive sensing time for the detection of free spectrum for SUs as well as extended periods of CRNs in an insecure state have adverse effects on network performance. Moreover, a CRN is very vulnerable to attacks as a result of its wireless nature and other unique characteristics such as spectrum sensing and sharing. These attacks may attempt to eavesdrop or modify the contents of packets being transmitted and they could also deny legitimate users the opportunity to use the band, leading to underutilization of the spectrum space. In this context, it is often challenging to differentiate between networks under Denial of Service (DoS) attacks from those networks experiencing congestion. This thesis employs a novel Stochastic Activity Network (SAN) model as an effective analytic tool to represent and study sensing vs performance vs security trade-offs in CRNs. Specifically, an investigation is carried out focusing on sensing vs security vs performance trade-offs, leading to the optimization of the spectrum band’s usage. Moreover, consideration is given either when a CRN experiencing congestion and or it is under attack. Consequently, the data delivery ratio (PDR) is employed to determine if the network is under DoS attack or experiencing congestion. In this context, packet loss probability, queue length and throughput of the transmitter are often used to measure the PDR with reference to interarrival times of PUs. Furthermore, this thesis takes into consideration the impact of scalability on the performance of the CRN. Due to the unpredictable nature of PUsactivities on the spectrum, it is imperative for SUs to swiftly utilize the band as soon as it becomes available. Unfortunately, the CRN models proposed in literature are static and unable to respond effectively to changes in service demands. To this end, a numerical simulation experiment is carried out to determine the impact of scalability towards the enhancement of nodal CRN sensing, security and performance. Atthe instant the band becomes idle and there are requests by SUs waiting for encryption and transmission, additional resources are dynamically released in order to largely utilize the spectrum space before the reappearance of PUs. These additional resources make the same service provision, such as encryption and intrusion detection, as the initial resources. To this end,SAN model is proposed in order to investigate the impact of scalability on the performance of CRN. Typical numerical simulation experiments are carried out, based on the application of the Mobius Petri Net Package to determine the performance of scalable CRNs (SCRNs) in comparison with unscalable CRNs (UCRNs) and associated interpretations are made.

<p>In this thesis we study radio resource management (RRM) in two types of CDMA-based wireless networks, cognitive radio networks (CRNs) and cooperative communication networks. In the networks, all simultaneous transmissions share the same spectrum and interfere with one another. Therefore, managing the transmission power is very important as it determines other aspects of the network resource allocations, such as transmission time and rate allocations. The main objective of the RRM is to efficiently utilize the available network resources for providing the mobile users with satisfactory quality of service (QoS).</p> / Doctor of Philosophy (PhD)

Thesis ( M.Sc. (Computer Science)) -- University of Limpopo, 2019 / Cognitive radio network, which enables dynamic spectrum access, addresses the shortage of radio spectrum caused by ever-increasing wireless technology. This allows efficient utilisation of underutilised licenced spectrum by allowing cognitive radios to opportunistically make use of available licenced spectrum. Cognitive radios (CR), also known as secondary users, must constantly sense the spectrum band to avoid interfering with the transmission of the licenced users, known as primary users. Cognitive radios must cooperate in sensing the spectrum environment to avoid environmental issues that can affect the spectrum sensing. However, cooperative spectrum sensing is vulnerable to Byzantine attacks where selfish CR falsify the spectrum reports. Hence, there is a need to design and implement a defence mechanism that will thwart the Byzantine attacks and guarantee correct available spectrum access decisions. The use of extreme studentized deviate (ESD) test together with consensus algorithms are proposed in this study to combat the results of the availability of Byzantine attack in a cognitive radio network. The ESD test was used to detect and isolate falsified reports from selfish cognitive radios during the information sharing phase. The consensus algorithm was used to combine sensing reports at each time k to arrive at a consensus value which will be used to decide the spectrum availability. The proposed scheme, known extreme studentized cooperative consensus spectrum sensing (ESCCSS), was implemented in an ad hoc cognitive radio networks environment where the use of a data fusion centre (DFC) is not required. Cognitive radios make their own data fusion and make the final decision about the availability of the spectrum on their sensed reports and reports from their neighbouring nodes without any assistance from the fusion centre. MATLAB was used to implement and simulate the proposed scheme. We compared our scheme with Attack-Proof Cooperative Spectrum Sensing to check its effectiveness in combating the effect of byzantine attack.

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Thesis( M. A. (Computer Science)) -- University of Limpopo , 2021 / In Software Defined Cognitive Radio Network (SDCRN), network security is a significant issue. This issue arises when Software Defined Network (SDN) architecture integrates with the Cognitive Radio Network (CRN) technology. SDN is designed to improve network resource management, while CRN technology is meant at improving spectrum management. These technologies are vulnerable to several malicious attacks. These attacks include Distributed Denial of Service (DDoS) and Primary User Emulation (PUE). Both the DDoS and PUE can be disrupt services in the SDCRN. To curb these attacks, schemes which hardens the security of SDCRN need to be designed. Thus, in this study we propose a security mechanism called Extreme_Controller_Mechanism (XCM) that reduce the effects of DDoS and PUE. The proposed XCM scheme was designed and evaluated in three simulation environment, the OMNeT++, Octave, and MATLAB simulators. The SDCRN data set was generated using the Neural Network back propagation algorithms. The data set was then used in Matlab to evaluate the effectiveness of the prosed XCM scheme. XCM proved to be effective and efficient at detection and prevention of DDoS and PUE attacks in SDCRN. In terms of memory and processor utilisation, XCM proved to the best when compared to other schemes such as the Advanced Support Vector Machine (ASVM) and deep learning convolution network (CDLN). But in terms of detection time, the ASVM was found to be the best performing scheme. Regarding our test for detection rate, false positive and false negative, the XCM, ASVM and CDLM performed the same. The results of the XCM were therefore the best and superior to the ASVM and CDLM. This can be attributed to the fact that the XCM scheme is optimised for DDoS and PUE attacks. We can therefore conclude that our XCM scheme is the best performing scheme compared to the ASVM and CDLN schemes.

No / Cognitive Radio (CR) is an emerging technology used to significantly improve the efficiency of spectrum utilization. Although some spectrum bands in the primary user's licensed spectrum are intensively used, most of the spectrum bands remain underutilized. The introduction of open spectrum and dynamic spectrum access lets the secondary (unlicensed) users, supported by cognitive radios; opportunistically utilize the unused spectrum bands. However, if a primary user returns to a band occupied by a secondary user, the occupied spectrum band is vacated immediately by handing off the secondary user's call to another idle spectrum band. Multiple spectrum handoffs can severely degrade quality of service (QoS) for the interrupted users. To avoid multiple handoffs, when a licensed primary user appears at the engaged licensed band utilized by a secondary user, an effective spectrum handoff procedure should be initiated to maintain a required level of QoS for secondary users. In other words, it enables the channel clearing while searching for target vacant channel(s) for completing unfinished transmission. This paper proposes prioritized proactive spectrum handoff decision schemes to reduce the handoff delay and the total service time. The proposed schemes have been modeled using a preemptive resume priority (PRP) M/G/1 queue to give a high priority to interrupted users to resume their transmission ahead of any other uninterrupted secondary user. The performance of proposed handoff schemes has been evaluated and compared against the existing spectrum handoff schemes. Experimental results show that the schemes developed here outperform the existing schemes in terms of average handoff delay and total service time under various traffic arrival rates as well as service rates.

In modern communication systems, it’s important to detect and use available radio frequencies effectively. However, current methods face challenges with complexity and noise interference. We’ve developed a new approach using advanced artificial intelligence (AI) based computing techniques to improve efficiency and accuracy in this process. Our method shows promising results, requiring only minimal additional resources in exchange of improved performance compared to older techniques. / Master of Science / In modern communication systems, it’s important to detect and use available radio frequencies effectively. However, current methods face challenges with complexity and noise interference. We’ve developed a new approach using advanced artificial intelligence (AI) based computing techniques to improve efficiency and accuracy in this process. Our method shows promising results, requiring only minimal additional resources in exchange of improved performance compared to older techniques.