Throughput Analysis of Primary and Secondary Networks in a Shared IEEE 802.11 System

In this paper, we analyze the coexistence of a primary and a secondary (cognitive) network when both networks use the IEEE 802.11 based distributed coordination function for medium access control. Specifically, we consider the problem of channel capture by a secondary network that uses spectrum sensing to determine the availability of the channel, and its impact on the primary throughput. We integrate the notion of transmission slots in Bianchi's Markov model with the physical time slots, to derive the transmission probability of the secondary network as a function of its scan duration. This is used to obtain analytical expressions for the throughput achievable by the primary and secondary networks. Our analysis considers both saturated and unsaturated networks. By performing a numerical search, the secondary network parameters are selected to maximize its throughput for a given level of protection of the primary network throughput. The theoretical expressions are validated using extensive simulations carried out in the Network Simulator 2. Our results provide critical insights into the performance and robustness of different schemes for medium access by the secondary network. In particular, we find that the channel captures by the secondary network does not significantly impact the primary throughput, and that simply increasing the secondary contention window size is only marginally inferior to silent-period based methods in terms of its throughput performance.Comment: To appear in IEEE Transactions on Wireless Communication

Analysis and improvement of medium access control protocols in wireless networks. Performance modelling and Quality-of-Service enhancement of IEEE 802.11e MAC in wireless local area networks under heterogeneous multimedia traffic.

In order to efficiently utilize the scarce wireless resource as well as keep up with the ever-increasing demand for Quality-of-Service (QoS) of multimedia applications, wireless networks are undergoing rapid development and dramatic changes in the underlying technologies and protocols. The Medium Access Control (MAC) protocol, which coordinates the channel access and data transmission of wireless stations, plays a pivotal role in wireless networks. Performance modelling and analysis has been and continues to be of great theoretical and practical importance in the design and development of wireless networks. This research is devoted to developing efficient and cost-effective analytical tools for the performance analysis and enhancement of MAC protocols in Wireless Local Area Networks (WLANs) under heterogeneous multimedia traffic. To support the MAC-layer QoS in WLANs, the IEEE 802.11e Enhanced Distributed Channel Access (EDCA) protocol has proposed three QoS differentiation schemes in terms of Arbitrary Inter-Frame Space (AIFS), Contention Window (CW), and Transmission Opportunity (TXOP). This research starts with the development of new analytical models for the TXOP scheme specified in the EDCA protocol under Poisson traffic. A dynamic TXOP scheme is then proposed to adjust the TXOP limits according to the status of the transmission queue. Theoretical analysis and simulation experiments show that the proposed dynamic scheme largely improves the performance of TXOP. To evaluate the TXOP scheme in the presence of ii heterogeneous traffic, a versatile analytical model is developed to capture the traffic heterogeneity and model the features of burst transmission. The performance results highlight the importance of taking into account the heterogeneous traffic for the accurate evaluation of the TXOP scheme in wireless multimedia networks. To obtain a thorough and deep understanding of the performance attributes of the EDCA protocol, a comprehensive analytical model is then proposed to accommodate the integration of the three QoS schemes of EDCA in terms of AIFS, CW, and TXOP under Poisson traffic. The performance results show that the TXOP scheme can not only support service differentiation but also improve the network performance, whereas the AIFS and CW schemes provide QoS differentiation only. Moreover, the results demonstrate that the MAC buffer size has considerable impact on the QoS performance of EDCA under Poisson traffic. To investigate the performance of EDCA in wireless multimedia networks, an analytical model is further developed for EDCA under heterogeneous traffic. The performance results demonstrate the significant effects of heterogeneous traffic on the total delay and frame losses of EDCA with different buffer sizes. Finally, an efficient admission control scheme is presented for the IEEE 802.11e WLANs based on analytical modelling and a game-theoretical approach. The admission control scheme can maintain the system operation at an optimal point where the utility of the Access Point (AP) is maximized with the QoS constraints of various users

Resource Management and Backhaul Routing in Millimeter-Wave IAB Networks Using Deep Reinforcement Learning

Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023..The increased densification of wireless networks has led to the development of integrated access and backhaul (IAB) networks. In this thesis, deep reinforcement learning was applied to solve resource management and backhaul routing problems in millimeter-wave IAB networks. In the research work, a resource management solution that aims to avoid congestion for access users in an IAB network was proposed and implemented. The proposed solution applies deep reinforcement learning to learn an optimized policy that aims to achieve effective resource allocation whilst minimizing congestion and satisfying the user requirements. In addition, a deep reinforcement learning-based backhaul adaptation strategy that leverages a recursive discrete choice model was implemented in simulation. Simulation results where the proposed algorithms were compared with two baseline methods showed that the proposed scheme provides better throughput and delay performance.Sentech Chair in Broadband Wireless Multimedia Communications.Electrical, Electronic and Computer EngineeringPhD (Electronic Engineering)Unrestricte

AI meets CRNs : a prospective review on the application of deep architectures in spectrum management

The spectrum low utilization and high demand conundrum created a bottleneck towards ful lling the requirements of next-generation networks. The cognitive radio (CR) technology was advocated as a de facto technology to alleviate the scarcity and under-utilization of spectrum resources by exploiting temporarily vacant spectrum holes of the licensed spectrum bands. As a result, the CR technology became the rst step towards the intelligentization of mobile and wireless networks, and in order to strengthen its intelligent operation, the cognitive engine needs to be enhanced through the exploitation of arti cial intelligence (AI) strategies. Since comprehensive literature reviews covering the integration and application of deep architectures in cognitive radio networks (CRNs) are still lacking, this article aims at lling the gap by presenting a detailed review that addresses the integration of deep architectures into the intricacies of spectrum management. This is a prospective review whose primary objective is to provide an in-depth exploration of the recent trends in AI strategies employed in mobile and wireless communication networks. The existing reviews in this area have not considered the relevance of incorporating the mathematical fundamentals of each AI strategy and how to tailor them to speci c mobile and wireless networking problems. Therefore, this reviewaddresses that problem by detailing howdeep architectures can be integrated into spectrum management problems. Beyond reviewing different ways in which deep architectures can be integrated into spectrum management, model selection strategies and how different deep architectures can be tailored into the CR space to achieve better performance in complex environments are then reported in the context of future research directions.The Sentech Chair in Broadband Wireless Multimedia Communications (BWMC) at the University of Pretoria.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639am2022Electrical, Electronic and Computer Engineerin

Performance Prediction and Tuning for Symmetric Coexistence of WiFi and ZigBee Networks

Due to the explosive deployment of WiFi and ZigBee wireless networks, 2.4GHz ISM bands (2.4GHz-2.5GHz) are becoming increasingly crowded, and the co-channel coexistence of these two networks is inevitable. For coexistence networks, people always want to predict their performance (e.g. throughput, energy consumption, etc.) before deployment, or even want to tune parameters to compensate unnecessary performance degradation (owing to the huge differences between these two MAC protocols) or to satisfy some performance requirements (e.g., priority, delay constraint, etc.) of them. However, predicting and tuning performance of coexisting WiFi and ZigBee networks has been a challenging task, primarily due to the lack of corresponding simulators and analytical models. In this dissertation, we addressed the aforementioned problems by presenting simulators and models for the coexistence of WiFi and ZigBee devices. Specifically, based on the energy efficiency and traffic pattern of three practical coexistence scenarios: disaster rescue site, smart hospital and home automation. We first of all classify them into three classes, which are non-sleeping devices with saturated traffic (SAT), non-sleeping devices with unsaturated traffic (UNSAT) and duty-cycling devices with unsaturated traffic (DC-UNSAT). Then a simulator and an analytical model are proposed for each class, where each simulator is verified by simple hardware based experiment. Next, we derive the expressions for performance metrics like throughput, delay etc., and predict them using both the proposed simulator and the model. Due to the higher accuracy of the simulator, the results from them are used as the ground truth to validate the accuracy of the model. Last, according to some common performance tuning requirements for each class, we formulate them into optimization problems and propose the corresponding solving methods. The results show that the proposed simulators have high accuracy in performance prediction, while the models, although are less accurate than the former, can be used in fast prediction. In particular, the models can also be easily used in optimization problems for performance tuning, and the results prove its high efficiency

Improving the Performance of Wireless LANs

This book quantifies the key factors of WLAN performance and describes methods for improvement. It provides theoretical background and empirical results for the optimum planning and deployment of indoor WLAN systems, explaining the fundamentals while supplying guidelines for design, modeling, and performance evaluation. It discusses environmental effects on WLAN systems, protocol redesign for routing and MAC, and traffic distribution; examines emerging and future network technologies; and includes radio propagation and site measurements, simulations for various network design scenarios, numerous illustrations, practical examples, and learning aids

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

IoT security and privacy assessment using software-defined radios

The Internet of Things (IoT) has seen exceptional adoption in recent years, resulting in an unprecedented level of connectivity in personal and industrial domains. In parallel, software-defined radio (SDR) technology has become increasingly powerful, making it a compelling tool for wireless security research across multiple communication protocols. Specifically, SDRs are capable of manipulating the physical layer of protocols in software, which would otherwise be implemented statically in hardware. This flexibility enables research that goes beyond the boundaries of protocol specifications. This dissertation pursues four research directions that are either enabled by software-defined radio technology, or advance its utility for security research. First, we investigate the anti-tracking mechanisms defined by the Bluetooth Low Energy (BLE) wireless protocol. This protocol, present in virtually all wearable smart devices, implements address randomization in order to prevent unwanted tracking of its users. By analyzing raw advertising data from BLE devices using SDRs, we identify a vulnerability that allows an attacker to track a BLE device beyond the address randomization defined by the protocol. Second, we implement a compact, SDR-based testbed for physical layer benchmarking of wireless devices. The testbed is capable of emulating multiple data transmissions and produce intentional signal corruption in very precisely defined ways in order to investigate receiver robustness and undefined device behavior in the presence of malformed packets. We subject a range of Wi-Fi and Zigbee devices to specifically crafted packet collisions and "truncated packets" as a way to fingerprinting wireless device chipsets. Third, we introduce a middleware framework, coined "Snout", to improves accessibility and usability of SDRs. The architecture provides standardized data pipelines as well as an abstraction layer to GNU Radio flowgraphs which power SDR signal processing. This abstraction layer improves usability and maintainability by providing a declarative experiment configuration format instead of requiring constant manipulation of the signal processing code during experimentation. We show that Snout does not result in significant computational overhead, and maintains a predictable and modest memory footprint. Finally, we address the visibility problem arising from the growing number of IoT protocols across large bands of radio spectrum. We model an SDR-based IoT monitor which is capable of scanning multiple channels (including across multiple protocols), and employs channel switching policies to maximize freshness of information obtained by transmitting devices. We present multiple policies and compare their performance against an optimal Markov Decision Process (MDP) model, as well as through event-based simulation using real-world device traffic. The results of this work demonstrate the use of SDR technology in privacy and security research of IoT device communication, and open up opportunities for further low-layer protocol discoveries that require the use of software-defined radio as a research tool

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks