Age of information and success probability analysis in hybrid spectrum access-based massive cognitive radio networks

In this paper, we investigate users’ performance under the hybrid spectrum access model in the massive cognitive radio network (CRN), where multiple primary users (PUs) and secondary users (SUs) transmit on the same channel simultaneously. SUs first detect the state of the channel via channel sensing and select an appropriate channel access scheme (either underlay or overlay) for their transmissions based on the outcome of the channel sensing. When at least one PU is active, SUs transmit under the underlay channel access scheme by employing the power control technique to ensure that the interference generated in the primary network is below the pre-defined interference threshold. In the absence of PU, SUs transmit with full transmit power under the overlay channel access scheme, thereby maximizing their throughput. Using the tool of stochastic geometry, we obtained tractable analyses for important metrics such as success probability, throughput, and the average age of information (AoI) in both primary and secondary networks, while capturing the interference between the two networks. The obtained analyses offer an efficient way to understand the metrics of AoI, throughput and success probability in the hybrid spectrum access-based CRN. We further compared users’ performance under the hybrid spectrum access scheme with performances under overlay and underlay spectrum access schemes. The outcome of the numerical simulations shows that the hybrid spectrum access scheme can significantly improve the performance of users in the network, while also capturing more key features of real-life systems.The SENTECH Chair in Broadband Wireless Multimedia Communications (BWMC), Department of Electrical, Electronics, and Computer Engineering, University of Pretoria, South Africa.http://www.mdpi.com/journal/applscipm2021Electrical, Electronic and Computer Engineerin

A multi-user tasks offloading scheme for integrated edge-fog-cloud computing environments

This paper presents a multi-user, multi-class and multi-layer edge computing-based framework for effective task offloading and computation processes. Important system requirements that were not captured in the existing multi-layer solutions such as offloading, computations and deadline requirements were captured in the system modeling, while both wireless communications and task computation constraints were considered. We considered three layers system, where each device offloads its generated tasks in each time slot to any selected layer for computation. On its arrival at such a selected layer, the task is only accepted if the queue size is below the pre-defined threshold, otherwise, such a task is offloaded to the next layer. Tasks were classified into class 1 and class 2 tasks following tasks’ quality of service requirements. We adopted stochastic geometry, parallel computing and queueing theory techniques to model the performance of the considered integrated edge-fog-cloud computing environment and obtained analysis for various performance metrics of interest. The obtained analyses demonstrate the importance of multi-layer and multi-class edge computing systems towards improving the experience of both delay-sensitive and mission-critical applications in any task offloading environment.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25hj2023Electrical, Electronic and Computer Engineerin

Stochastic geometry approach towards interference management and control in cognitive radio network : a survey

Interference management and control in the cognitive radio network (CRN) is a necessity if the activities of primary users must be protected from excessive interference resulting from the activities of neighboring users. Hence, interference experienced in wireless communication networks has earlier been characterized using the traditional grid model. Such models, however, lead to non-tractable analyses, which often require unrealistic assumptions, leading to inaccurate results. These limitations of the traditional grid models mean that the adoption of stochastic geometry (SG) continues to receive a lot of attention owing to its ability to capture the distribution of users properly, while producing scalable and tractable analyses for various performance metrics of interest. Despite the importance of CRN to next-generation networks, no survey of the existing literature has been done when it comes to SG-based interference management and control in the domain of CRN. Such a survey is, however, necessary to provide the current state of the art as well as future directions. This paper hence presents a comprehensive survey related to the use of SG to effect interference management and control in CRN. We show that most of the existing approaches in CRN failed to capture the relationship between the spatial location of users and temporal traffic dynamics and are only restricted to interference modeling among non-mobile users with full buffers. This survey hence encourages further research in this area. Finally, this paper provides open problems and future directions to aid in finding more solutions to achieve efficient and effective usage of the scarce spectral resources for wireless communications.The SENTECH Chair in Broadband Wireless Multimedia Communications (BWMC), Department of Electrical, Electronic and Computer Engineering, University of Pretoria, South Africa.http://www.elsevier.com/locate/comcomhj2022Electrical, Electronic and Computer Engineerin

Spatiotemporal characterization of users' experience in massive cognitive radio networks

The need to capture the actual network traf c condition and fundamental queueing dynamics in a massive cognitive radio network (CRN) is important for proper analysis of the intrinsic effects of spatial distribution while capturing the essential temporal distribution properties of the network. In massive CRN, many users, including primary and secondary users, transmit on scarce spectrum resources. While primary users (PUs) are delay-sensitive users that require prioritized access over secondary users (SUs), carrying out analysis that captures this property becomes imperative if users' service experience is to be satisfactory. This paper presents priority conscious spatiotemporal analysis capable of characterizing users' experience in massive CRN. Users in the primary priority queue were considered to have pre-emptive priory over users in the virtual and secondary priority queues. A Geo/G/1 discrete-time Markov chain queueing system was adopted to characterize both primary and secondary priority queues, while the virtual priority queue was analyzed as part of the secondary priority queue. Using the tools of stochastic geometry and queueing theory, the user's coverage probability was determined while the delay experienced by each class of users in the network was obtained using existing results. Through the obtained delay for each class of users in the network, the corresponding quality of service was also obtained. The results obtained show that the proposed framework is capable of accurately characterizing users' service experience in massive CRN.The SENTECH Chair in Broadband Wireless Multimedia Communications (BWMC), Department of Electrical, Electronics, and Computer Engineering, University of Pretoria, South Africa.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639am2020Electrical, Electronic and Computer Engineerin

A multi-class channel access scheme for cognitive edge computing-based Internet of Things networks

Edge computing-based framework is capable of improving users’ quality of experience in cognitive Internet of Things (IoT) networks. To explore the advantages of this edge computing-based framework, possible offloading and processing delay resulting from computation bottlenecks, and the offloading latency caused due to inter-cell interference must be properly considered. This paper thus considered a multi-class channel access mechanism for cognitive edge computing-based IoT networks where IoT users were categorized based on their quality of experience requirements. Essential IoT devices are permitted to offload to the edge server at any time following the hybrid channel access model, while delay-tolerant IoT devices are only permitted to offload to the server when the channel is idle following the overlay channel access model. Analyses were obtained for transmission rate and offloading delay to demonstrate the performance of the proposed mechanism, while important metrics such as total offloading latency and total offloading cost were investigated. The total offloading costs were formulated through the mixed strategy Nash equilibrium method. The proposed mechanism achieves lower offloading latencies and costs for both type 1 and type 2 CUs when compared with existing methods. The obtained results showed that multi-class channel access mechanisms can reduce packet offloading delay in cognitive edge computing-based IoT networks.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25hj2023Electrical, Electronic and Computer Engineerin

Users emulation attack management in the massive Internet of Things enabled environment

Users’ emulation attacks are a prominent denial of service attack capable of degrading the entire performance of the network. In this paper, the detection and control of users’ emulation attacks in the massive internet of things networks were considered. An efficient power-based signal to interference ratio (SIR) approach was proposed to characterize the attackers’ behavior in the system. The trust list table was also adopted to further improve the detection of malicious nodes (MNs). The proposed approach shows an improved performance when compared with the conventional energy detection based approach which did not capture the channel interference in the system modeling. Through the received SIR, MNs can be identified owing to the higher transmission power required to disrupt the network.http://www.elsevier.com/locate/ictepm2021Electrical, Electronic and Computer Engineerin

Outage and throughput analysis of cognitive users in underlay cognitive radio networks with handover

Interference characterization in cognitive networks with handover has received less attention in stochastic geometry-based interference management and control, especially in cognitive radio networks, because of the possibility of complicating the analysis of various performance metrics of interest, such as outage probability and throughput. However, because of the possible mobility that is observed in real practical systems, some of the receivers may be located outside the coverage regions of their paired transmitters. In order to ensure that any receiver located outside the coverage region of its paired transmitter continues to receive its required service from its paired transmitter while still achieving tractable analysis for various performance metrics of interest, we adopted multiuser diversity via packet relaying. With this approach, any secondary nodes waiting to transmit can be used to sustain coverage between any typical active transmitter and receiver pair, while reducing their own waiting period in the process. We obtained tractable analysis for outage probability, spectral efficiency and throughput and showed the effect of handover rate over the network performance. The outcomes of the numerical results show that the proposed approach is capable of improving the overall network performance by improving coverage and throughput among network users in the cognitive radio networks.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639pm2021Electrical, Electronic and Computer Engineerin

Interference characterization in underlay cognitive networks with intra-network and inter-network dependence

Interference modeling in cognitive radio network is important to ensure adequate coverage in the network. A reliable interference model, however, depends on accurately characterizing the distribution of users. In this paper, the dependence between primary and secondary networks is examined in order to capture more system parameters related to system characterization. Hence, two cases are considered - primary user (PU) interference control and PU with secondary user (SU) interference control mechanisms. Under PU interference control, distributions of PUs follow the Matern hard core process while the distribution of SUs follow the Poisson hole process (PHP). However, under PU with SU interference control, the distribution of active SUs follow a modified PHP. Bound and approximate expressions were derived for coverage probability at both primary and secondary networks, while simple yet accurate expressions were obtained to depict the number of simultaneous active users supported for the two cases. The tight closeness between the bound and the approximate expressions shows the reliability of the presented theoretical analysis. Furthermore, the bipolar network model assumption was relaxed while the case of independence assumption among users was also considered. Numerical result showed close tightness when the bipolar network model assumption was relaxed while the independence assumption was shown to overestimate users' coverage probability.The SENTECH Chair in Broadband Wireless Multimedia Communications (BWMC), Department of Electrical, Electronics and Computer Engineering, University of Pretoria, South Africa.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp/?punumber=7755hj2022Electrical, Electronic and Computer Engineerin

Malicious users control and management in cognitive radio networks with priority queues

Malicious users (MUs) have the tendency to disrupt the activities of honest users in the network if not properly controlled. In a massive cognitive radio network (CRN) with priority queues, malicious secondary users (SUs) can manipulate their priority queue requirements and mislead legitimate SUs to vacate the channels. In this paper, a game theoretic based signal detection approach is proposed to control the presence of MUs in CRN. If the received signal strength is less than the predefined threshold for primary transmissions in the presence of interference and noise, such a user is marked to be malicious and its payoff table is updated. Through the mixed strategy Nash equilibrium method, the payoff table of each user can be updated to aid removal of MUs from the network. The outcome of the simulation results shows that such an approach can reduce the impact of malicious activities in the massive CRN where SUs are expected to be low-power energy-efficient devices.https://ieeexplore.ieee.org/xpl/conhome/8738891/proceedinghj2021Electrical, Electronic and Computer Engineerin