Design and analysis of optimal resource allocation policies in wireless networks

Ph.DDOCTOR OF PHILOSOPH

A Connection Admission Control Framework for UMTS based Satellite Systems.An Adaptive Admission Control algorithm with pre-emption control mechanism for unicast and multicast communications in satellite UMTS.

In recent years, there has been an exponential growth in the use of multimedia applications. A satellite system offers great potential for multimedia applications with its ability to broadcast and multicast a large amount of data over a very large area as compared to a terrestrial system. However, the limited transmission capacity along with the dynamically varying channel conditions impedes the delivery of good quality multimedia service in a satellite system which has resulted in research efforts for deriving efficient radio resource management techniques. This issue is addressed in this thesis, where the main emphasis is to design a CAC framework which maximizes the utilization of the scarce radio resources available in the satellite and at the same time increases the performance of the system for a UMTS based satellite system supporting unicast and multicast traffic. The design of the system architecture for a UMTS based satellite system is presented. Based on this architecture, a CAC framework is designed consisting of three different functionalities: the admission control procedure, the retune procedure and the pre-emption procedure. The joint use of these functionalities is proposed to allow the performance of the system to be maintained under congestion. Different algorithms are proposed for different functionalities; an adaptive admission control algorithm, a greedy retune algorithm and three pre-emption algorithms (Greedy, SubSetSum, and Fuzzy). A MATLAB simulation model is developed to study the performance of the proposed CAC framework. A GUI is created to provide the user with the flexibility to configure the system settings before starting a simulation. The configuration settings allow the system to be analysed under different conditions. The performance of the system is measured under different simulation settings such as enabling and disabling of the two functionalities of the CAC framework; retune procedure and the pre-emption procedure. The simulation results indicate the CAC framework as a whole with all the functionalities performs better than the other simulation settings

Comparison of vertical handover decision-based techniques in heterogeneous networks

Industry leaders are currently setting out standards for 5G Networks projected for 2020 or even sooner. Future generation networks will be heterogeneous in nature because no single network type is capable of optimally meeting all the rapid changes in customer demands. Heterogeneous networks are typically characterized by some network architecture, base stations of varying transmission power, transmission solutions and the deployment of a mix of technologies (multiple radio access technologies). In heterogeneous networks, the processes involved when a mobile node successfully switches from one radio access technology to the other for the purpose of quality of service continuity is termed vertical handover or vertical handoff. Active calls that get dropped, or cases where there is discontinuity of service experienced by mobile users can be attributed to the phenomenon of delayed handover or an outright case of an unsuccessful handover procedure. This dissertation analyses the performance of a fuzzy-based VHO algorithm scheme in a Wi-Fi, WiMAX, UMTS and LTE integrated network using the OMNeT++ discrete event simulator. The loose coupling type network architecture is adopted and results of the simulation are analysed and compared for the two major categories of handover basis; multiple and single criteria based handover methods. The key performance indices from the simulations showed better overall throughput, better call dropped rate and shorter handover time duration for the multiple criteria based decision method compared to the single criteria based technique. This work also touches on current trends, challenges in area of seamless handover and initiatives for future Networks (Next Generation Heterogeneous Networks)

On The Dynamic Spectrum Access For Next Generation Wireless Communication Systems

Ph.DDOCTOR OF PHILOSOPH

Managed access dependability for critical services in wireless inter domain environment

The Information and Communications Technology (ICT) industry has through the last decades changed and still continues to affect the way people interact with each other and how they access and share information, services and applications in a global market characterized by constant change and evolution. For a networked and highly dynamic society, with consumers and market actors providing infrastructure, networks, services and applications, the mutual dependencies of failure free operations are getting more and more complex. Service Level Agreements (SLAs) between the various actors and users may be used to describe the offerings along with price schemes and promises regarding the delivered quality. However, there is no guarantee for failure free operations whatever efforts and means deployed. A system fails for a number of reasons, but automatic fault handling mechanisms and operational procedures may be used to decrease the probability for service interruptions. The global number of mobile broadband Internet subscriptions surpassed the number of broadband subscriptions over fixed technologies in 2010. The User Equipment (UE) has become a powerful device supporting a number of wireless access technologies and the always best connected opportunities have become a reality. Some services, e.g. health care, smart power grid control, surveillance/monitoring etc. called critical services in this thesis, put high requirements on service dependability. A definition of dependability is the ability to deliver services that can justifiably be trusted. For critical services, the access networks become crucial factors for achieving high dependability. A major challenge in a multi operator, multi technology wireless environment is the mobility of the user that necessitates handovers according to the physical movement. In this thesis it is proposed an approach for how to optimize the dependability for critical services in multi operator, multi technology wireless environment. This approach allows predicting the service availability and continuity at real-time. Predictions of the optimal service availability and continuity are considered crucial for critical services. To increase the dependability for critical services dual homing is proposed where the use of combinations of access points, possibly owned by different operators and using different technologies, are optimized for the specific location and movement of the user. A central part of the thesis is how to ensure the disjointedness of physical and logical resources so important for utilizing the dependability increase potential with dual homing. To address the interdependency issues between physical and logical resources, a study of Operations, Administrations, and Maintenance (OA&M) processes related to the access network of a commercial Global System for Mobile Communications (GSM)/Universal Mobile Telecommunications System (UMTS) operator was performed. The insight obtained by the study provided valuable information of the inter woven dependencies between different actors in the delivery chain of services. Based on the insight gained from the study of OA&M processes a technological neutral information model of physical and logical resources in the access networks is proposed. The model is used for service availability and continuity prediction and to unveil interdependencies between resources for the infrastructure. The model is proposed as an extension of the Media Independent Handover (MIH) framework. A field trial in a commercial network was conducted to verify the feasibility in retrieving the model related information from the operators' Operational Support Systems (OSSs) and to emulate the extension and usage of the MIH framework. In the thesis it is proposed how measurement reports from UE and signaling in networks are used to define virtual cells as part of the proposed extension of the MIH framework. Virtual cells are limited geographical areas where the radio conditions are homogeneous. Virtual cells have radio coverage from a number of access points. A Markovian model is proposed for prediction of the service continuity of a dual homed critical service, where both the infrastructure and radio links are considered. A dependability gain is obtained by choosing a global optimal sequence of access points. Great emphasizes have been on developing computational e cient techniques and near-optimal solutions considered important for being able to predict service continuity at real-time for critical services. The proposed techniques to obtain the global optimal sequence of access points may be used by handover and multi homing mechanisms/protocols for timely handover decisions and access point selections. With the proposed extension of the MIH framework a global optimal sequence of access points providing the highest reliability may be predicted at real-time

WAVEFORM DESIGN AND NETWORK SELECTION IN WIDEBAND SMALL CELL NETWORKS

The explosion in demand for wireless data traffic in recent years has triggered rapid development and pervasive deployment of wireless communication networks. To meet the exponentially increasing demand, a promising solution is the concept of wideband small cells, which is based on the idea of using broader frequency bandwidth and employing more efficient radio frequency resource reuse by dense deployment of wideband, short-range, low cost and low power base-stations. Broader bandwidth provides substantial degrees of freedom as well as challenges for system design due to the abundant multipaths and thus interference in high speed systems under large delay spread channels. Reducing the transmission range and increasing the number of cells permit better spatial reuse of spectrum. With the proliferation of wideband small cells, the strategy of selection among multiple networks has significant impacts to the performance of users and to the load balance of the system. In this dissertation, we address these problems with a focus on waveform design and network selection. In time-reversal communication systems, the time-reversal transmit waveform can boost the signal-to-noise ratio at the receiver with simple single-tap detection by utilizing channel reciprocity with very low transmitter complexity. However, the large delay spread gives rise to severe inter-symbol interference when the data rate is high, and the achievable transmission rate is further degraded in the multiuser downlink due to the inter-user interference. We study the weighted sum rate optimization problem by means of waveform design in the time-reversal multiuser downlink. We propose a new power allocation algorithm, which is able to achieve comparable sum rate performance to that of globally optimal power allocation. Further, we study the joint waveform design and interference pre-cancellation by exploiting the symbol information to further improve the performance by utilizing the information of previous symbols. In the proposed joint design, the causal interference is subtracted using interference pre-cancellation and the anti-causal interference can be further suppressed by waveform design with more degrees of freedom. The second part of this dissertation is concerned with the wireless access network selection problem considering the negative network externality, i.e, the influence of subsequent users' decisions on an individual's throughput due to the limited available resources. We formulate the wireless network selection problem as a stochastic game with negative network externality and show that finding the optimal decision rule can be modelled as a multi-dimensional Markov decision process. A modified value iteration algorithm is proposed to efficiently obtain the optimal decision rule with a simple threshold structure, which enables us to reduce the storage space of the strategy profile. We further investigate the mechanism design problem with incentive compatibility constraints, which enforce the networks to reveal the truthful state information. We analyze a data set of wireless LAN traces collected from campus networks, from which we observe that the number of user arrivals is approximately Poisson distributed; the session time and the waiting time to switch network can be approximated by exponential distributions. Based on the analysis, we formulate a wireless access network association game with both arriving strategy and switching strategy and validate the effectiveness of the proposed best response strategy

Quantum Reinforcement Learning for Dynamic Spectrum Access in Cognitive Radio Networks

Abstract This thesis proposes Quantum Reinforcement Learning (QRL) as an improvement to conventional reinforcement learning-based dynamic spectrum access used within cognitive radio networks. The aim is to overcome the slow convergence problem associated with exploration within reinforcement learning schemes. A literature review for the background of the carried out research work is illustrated. Review of research works on learning-based assignment techniques as well as quantum search techniques is provided. Modelling of three traditional dynamic channel assignment techniques is illustrated and the advantage characteristic of each technique is discussed. These techniques have been simulated to provide a comparison with learning based techniques, including QRL. Reinforcement learning techniques are used as a direct comparison with the Quantum Reinforcement Learning approaches. The elements of Quantum computation are then presented as an introduction to quantum search techniques. The Grover search algorithm is introduced. The algorithm is discussed from a theoretical perspective. The Grover algorithm is then used for the first time as a spectrum allocation scheme and compared to conventional schemes. Quantum Reinforcement Learning (QRL) is introduced as a natural evolution of the quantum search. The Grover search algorithm is combined as a decision making mechanism with conventional Reinforcement Learning (RL) algorithms resulting in a more efficient learning engine. Simulation results are provided and discussed. The convergence speed has been significantly increased. The beneficial effects of Quantum Reinforcement Learning (QRL) become more pronounced as the traffic load increases. The thesis shows that both system performance and capacity can be improved. Depending on the traffic load, the system capacity has improved by 9-84% from a number of users supported perspective. It also demonstrated file delay reduction for up to an average of 26% and 2.8% throughput improvement

Efficient Scheduling Algorithms for Wireless Resource Allocation and Virtualization in Wireless Networks

The continuing growth in demand for better mobile broadband experiences has motivated rapid development of radio-access technologies to support high data rates and improve quality of service (QoS) and quality of experience (QoE) for mobile users. However, the modern radio-access technologies pose new challenges to mobile network operators (MNO) and wireless device designers such as reducing the total cost of ownership while supporting high data throughput per user, and extending battery life-per-charge of the mobile devices. In this thesis, a variety of optimization techniques aimed at providing innovative solutions for such challenges are explored. The thesis is divided into two parts. In the first part, the challenge of extending battery life-per-charge is addressed. Optimal and suboptimal power-efficient schedulers that minimize the total transmit power and meet the QoS requirements of the users are presented. The second outlines the benefits and challenges of deploying wireless resource virtualization (WRV) concept as a promising solution for satisfying the growing demand for mobile data and reducing capital and operational costs. First, a WRV framework is proposed for single cell zone that is able to centralize and share the spectrum resources between multiple MNOs. Consequently, several WRV frameworks are proposed, which virtualize the spectrum resource of the entire network for cloud radio access network (C-RAN)- one of the front runners for the next generation network architecture. The main contributions of this thesis are in designing optimal and suboptimal solutions for the aforementioned challenges. In most cases, the optimal solutions suffer from high complexity, and therefore low-complexity suboptimal solutions are provided for practical systems. The optimal solutions are used as benchmarks for evaluating the suboptimal solutions. The results prove that the proposed solutions effectively contribute in addressing the challenges caused by the demand for high data rates and power transmission in mobile networks

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

Energy efficiency in wireless communication

This era would probably be recognized as the information age, hence as a paramount milestone in the progress of mankind, by the future historians. One of the most significant achievements of this age is, making it possible to transmit and receive information effectively and reliably via wireless radio technology. The demand of wireless communication is increasing in a never-resting pace, imposing bigger challenge not only on service providers but also on innovators and researches to innovate out-of-the-box technologies. These challenges include faster data communication over seamless, reliable and cost effective wireless networks, utilizing the limited physical radio resources as well as considering the environmental impact caused by the increasing energy consumption. The ever-expanding wireless communication infrastructure is withdrawing higher energy than ever, raising the need for finding more efficient systems. The challenge of developing efficient wireless systems can be addressed on several levels, starting from device electronics, up to the network-level architecture and protocols. The anticipated gains of achieving such efficiency is the key feature of extending mobile devices' battery life and reducing environmental and economic impacts of wireless communication infrastructure. Therefore energy efficient designs are urgently needed from both environmental and economic aspects of wireless networks. In this research, we explore the field of energy efficiency in MAC and Physical layers of wireless networks in order to enhance the performance and reliability of future wireless networks as well as to reduce its environmental footprint. In the first part of this research, we analyse the energy efficiency of two mostly used modulation techniques, namely MQAM and MFSK, for short range wireless transmissions, up to a few $100$s of meters, and propose optimum rate adaptation to minimize the energy dissipation during transmissions. Energy consumed for transmitting the data over a distance to maintain a prescribed error probability together with the circuit energy have been considered in our work. We provide novel results for optimal rate adaptation for improved energy efficiency. Our results indicate that the energy efficiency can be significantly improved by performing optimal rate adaptation given the radio and channel parameters, and furthermore we identify the maximum distance where optimal rate adaptation can be performed beyond which the optimum rate then becomes the same as the minimum data rate. In the second part of this research, we propose energy efficient algorithm for cellular base stations. In cellular networks, the base stations are the most energy consuming parts, which consume approximately $60-80\%$ of the total energy. Hence control and optimization of energy consumption at base stations should be at the heart of any green radio engineering scheme. Sleep mode implementation in base stations has proven to be a very good approach for the energy efficiency of cellular BSs. Therefore, we have proposed a novel strategy for improving energy efficiency on ternary state transceivers for cellular BSs. We consider transceivers that are capable of switching between sleep, stand-by and active modes whenever required. We have modelled these ternary state transceivers as a three-state Markov model and have presented an algorithm based on Markov model to intelligently switch among the states of the transceivers based on the offered traffic whilst maintaining a prescribed minimum rate per user. We consider a typical macro BS with state changeable transceivers and our results show that it is possible to improve the energy efficiency of the BS by approximately $40\%$ using the proposed MDP based algorithm. In the third part of this research, we propose energy efficient algorithm for aerial base stations. Recently aerial base stations are investigated to provide wireless coverage to terrestrial radio terminals. The advantages of using aerial platforms in providing wireless coverage are many including larger coverage in remote areas, better line-of-sight conditions etc. Energy is a scarce resource for aerial base stations, hence the wise management of energy is quite beneficial for the aerial network. In this context, we study the means of reducing the total energy consumption by designing and implementing an energy efficient aerial base station. Sleep mode implementation in base stations (BSs) has proven to be a very good approach for improving the energy efficiency; therefore we propose a novel strategy for further improving energy efficiency by considering ternary state transceivers of aerial base stations. Using the three state model we propose a Markovian Decision process (MDP) based algorithm to switch between the states for improving the energy efficiency of the aerial base station. The MDP based approach intelligently switches between the states of the transceivers based on the offered traffic whilst maintaining a prescribed minimum channel rate per user. Our simulation results show that there is a around $40\%$ gain in the energy efficiency when using our proposed MDP algorithm together with the three-state transceiver model for the base station compared to the always active mode. We have also shown the energy-delay trade-off in order to design an efficient aerial base station. In the final part of our work, we propose a novel energy efficient handover algorithm, based on Markov decision process (MDP) for the two-tier LTE network, towards reducing power transmissions at the mobile terminal side. The proposed policy is LTE backward-compatible, as it can be employed by suitably adapting a prescribed SNR target and standard LTE measurements. Simulation results reveal that compared to the widely adopted policy based on strongest cell and another energy efficient policy, our proposed policy can greatly reduce the power consumption at the LTE mobile terminals. Most of our works presented in this dissertation has been published in conference proceeding and some of them are currently undergoing a review process for journals. These publications will be highlighted and identified at the end of the first chapter of this dissertation