Intelligent Reflecting Surfaces Positioning in 6G Networks

The work analyzed the positioning of IRS over the coverage region of micro cell to derive optimal placement location to support cell-edge Internet of Things (IoT) devices with a favorable signal-to-interference plus noise ratio (SINR). Moreover, the work derived that the implementation of IRS significantly enhances energy efficiency notably reducing the transmit power of the micro cell base station

5G and beyond networks

This chapter investigates the Network Layer aspects that will characterize the merger of the cellular paradigm and the IoT architectures, in the context of the evolution towards 5G-and-beyond, including some promising emerging services as Unmanned Aerial Vehicles or Base Stations, and V2X communications

MM-Wave HetNet in 5G and beyond Cellular Networks Reinforcement Learning Method to improve QoS and Exploiting Path Loss Model

This paper presents High density heterogeneous networks (HetNet) which are the most promising technology for the fifth generation (5G) cellular network. Since 5G will be available for a long time, previous generation networking systems will need customization and updates. We examine the merits and drawbacks of legacy and Q-Learning (QL)-based adaptive resource allocation systems. Furthermore, various comparisons between methods and schemes are made for the purpose of evaluating the solutions for future generation. Microwave macro cells are used to enable extra high capacity such as Long-Term Evolution (LTE), eNodeB (eNB), and Multimedia Communications Wireless technology (MC), in which they are most likely to be deployed. This paper also presents four scenarios for 5G mm-Wave implementation, including proposed system architectures. The WL algorithm allocates optimal power to the small cell base station (SBS) to satisfy the minimum necessary capacity of macro cell user equipment (MUEs) and small cell user equipment (SCUEs) in order to provide quality of service (QoS) (SUEs). The challenges with dense HetNet and the massive backhaul traffic they generate are discussed in this study. Finally, a core HetNet design based on clusters is aimed at reducing backhaul traffic. According to our findings, MM-wave HetNet and MEC can be useful in a wide range of applications, including ultra-high data rate and low latency communications in 5G and beyond. We also used the channel model simulator to examine the directional power delay profile with received signal power, path loss, and path loss exponent (PLE) for both LOS and NLOS using uniform linear array (ULA) 2X2 and 64x16 antenna configurations at 38 GHz and 73 GHz mmWave bands for both LOS and NLOS (NYUSIM). The simulation results show the performance of several path loss models in the mmWave and sub-6 GHz bands. The path loss in the close-in (CI) model at mmWave bands is higher than that of open space and two ray path loss models because it considers all shadowing and reflection effects between transmitter and receiver. We also compared the suggested method to existing models like Amiri, Su, Alsobhi, Iqbal, and greedy (non adaptive), and found that it not only enhanced MUE and SUE minimum capacities and reduced BT complexity, but it also established a new minimum QoS threshold. We also talked about 6G researches in the future. When compared to utilizing the dual slope route loss model alone in a hybrid heterogeneous network, our simulation findings show that decoupling is more visible when employing the dual slope path loss model, which enhances system performance in terms of coverage and data rate

Resource allocation in future green wireless networks : applications and challenges

Over the past few years, green radio communication has been an emerging topic since the footprint from the Information and Communication Technologies (ICT) is predicted to increase 7.3% annually and then exceed 14% of the global footprint by 2040. Moreover, the explosive progress of ICT, e.g., the fifth generation (5G) networks, has resulted in expectations of achieving 10-fold longer device battery lifetime, and 1000-fold higher global mobile data traffic over the fourth generation (4G) networks. Therefore, the demands for increasing the data rate and the lifetime while reducing the footprint in the next-generation wireless networks call for more efficient utilization of energy and other resources. To overcome this challenge, the concepts of small-cell, energy harvesting, and wireless information and power transfer networks can be evaluated as promising solutions for re-greening the world. In this dissertation, the technical contributions in terms of saving economical cost, protecting the environment, and guaranteeing human health are provided. More specifically, novel communication scenarios are proposed to minimize energy consumption and hence save economic costs. Further, energy harvesting (EH) techniques are applied to exploit available green resources in order to reduce carbon footprint and then protect the environment. In locations where implemented user devices might not harvest energy directly from natural resources, base stations could harvest-and-store green energy and then use such energy to power the devices wirelessly. However, wireless power transfer (WPT) techniques should be used in a wise manner to avoid electromagnetic pollution and then guarantee human health. To achieve all these aspects simultaneously, this thesis proposes promising schemes to optimally manage and allocate resources in future networks. Given this direction, in the first part, Chapter 2 mainly studies a transmission power minimization scheme for a two-tier heterogeneous network (HetNet) over frequency selective fading channels. In addition, the HetNet backhaul connection is unable to support a sufficient throughput for signaling an information exchange between two tiers. A novel idea is introduced in which the time reversal (TR) beamforming technique is used at a femtocell while zero-forcing-based beamforming is deployed at a macrocell. Thus, a downlink power minimizationscheme is proposed, and optimal closed-form solutions are provided. In the second part, Chapters 3, 4, and 5 concentrate on EH and wireless information and power transfer (WIPT) using RF signals. More specifically, Chapter 3 presents an overview of the recent progress in green radio communications and discusses potential technologies for some emerging topics on the platforms of EH and WPT. Chapter 4 develops a new integrated information and energy receiver architecture based on the direct use of alternating current (AC) for computation. It is shown that the proposed approach enhances not only the computational ability but also the energy efficiency over the conventional one. Furthermore, Chapter 5 proposes a novel resource allocation scheme in simultaneous wireless information and power transfer (SWIPT) networks where three crucial issues: power-efficient improvement, user-fairness guarantee, and non-ideal channel reciprocity effect mitigation, are jointly addressed. Hence, novel methods to derive optimal and suboptimal solutions are provided. In the third part, Chapters 6, 7, and 8 focus on simultaneous lightwave information and power transfer (SLIPT) for indoor applications, as a complementary technology to RF SWIPT. In this research, Chapter 6 investigates a hybrid RF/visible light communication (VLC) ultrasmall cell network where optical transmitters deliver information and power using the visible light, whereas an RF access point works as a complementary power transfer system. Thus, a novel resource allocation scheme exploiting RF and visible light for power transfer is devised. Chapter 7 proposes the use of lightwave power transfer to enable future sustainable Federated Learning (FL)-based wireless networks. FL is a new data privacy protection technique for training shared machine learning models in a distributed approach. However, the involvement of energy-constrained mobile devices in the construction of the shared learning models may significantly reduce their lifetime. The proposed approach can support the FL-based wireless network to overcome the issue of limited energy at mobile devices. Chapter 8 introduces a novel framework for collaborative RF and lightwave power transfer for wireless communication networks. The constraints on the transmission power set by safety regulations result in significant challenges to enhance the power transfer performance. Thus, the study of technologies complementary to conventional RF SWIPT is essential. To cope with this isue, this chapter proposes a novel collaborative RF and lightwave power transfer technology for next-generation wireless networks

Resource Allocation and Service Management in Next Generation 5G Wireless Networks

The accelerated evolution towards next generation networks is expected to dramatically increase mobile data traffic, posing challenging requirements for future radio cellular communications. User connections are multiplying, whilst data hungry content is dominating wireless services putting significant pressure on network's available spectrum. Ensuring energy-efficient and low latency transmissions, while maintaining advanced Quality of Service (QoS) and high standards of user experience are of profound importance in order to address diversifying user prerequisites and ensure superior and sustainable network performance. At the same time, the rise of 5G networks and the Internet of Things (IoT) evolution is transforming wireless infrastructure towards enhanced heterogeneity, multi-tier architectures and standards, as well as new disruptive telecommunication technologies. The above developments require a rethinking of how wireless networks are designed and operate, in conjunction with the need to understand more holistically how users interact with the network and with each other. In this dissertation, we tackle the problem of efficient resource allocation and service management in various network topologies under a user-centric approach. In the direction of ad-hoc and self-organizing networks where the decision making process lies at the user level, we develop a novel and generic enough framework capable of solving a wide array of problems with regards to resource distribution in an adaptable and multi-disciplinary manner. Aiming at maximizing user satisfaction and also achieve high performance - low power resource utilization, the theory of network utility maximization is adopted, with the examined problems being formulated as non-cooperative games. The considered games are solved via the principles of Game Theory and Optimization, while iterative and low complexity algorithms establish their convergence to steady operational outcomes, i.e., Nash Equilibrium points. This thesis consists a meaningful contribution to the current state of the art research in the field of wireless network optimization, by allowing users to control multiple degrees of freedom with regards to their transmission, considering mobile customers and their strategies as the key elements for the amelioration of network's performance, while also adopting novel technologies in the resource management problems. First, multi-variable resource allocation problems are studied for multi-tier architectures with the use of femtocells, addressing the topic of efficient power and/or rate control, while also the topic is examined in Visible Light Communication (VLC) networks under various access technologies. Next, the problem of customized resource pricing is considered as a separate and bounded resource to be optimized under distinct scenarios, which expresses users' willingness to pay instead of being commonly implemented by a central administrator in the form of penalties. The investigation is further expanded by examining the case of service provider selection in competitive telecommunication markets which aim to increase their market share by applying different pricing policies, while the users model the selection process by behaving as learning automata under a Machine Learning framework. Additionally, the problem of resource allocation is examined for heterogeneous services where users are enabled to dynamically pick the modules needed for their transmission based on their preferences, via the concept of Service Bundling. Moreover, in this thesis we examine the correlation of users' energy requirements with their transmission needs, by allowing the adaptive energy harvesting to reflect the consumed power in the subsequent information transmission in Wireless Powered Communication Networks (WPCNs). Furthermore, in this thesis a fresh perspective with respect to resource allocation is provided assuming real life conditions, by modeling user behavior under Prospect Theory. Subjectivity in decisions of users is introduced in situations of high uncertainty in a more pragmatic manner compared to the literature, where they behave as blind utility maximizers. In addition, network spectrum is considered as a fragile resource which might collapse if over-exploited under the principles of the Tragedy of the Commons, allowing hence users to sense risk and redefine their strategies accordingly. The above framework is applied in different cases where users have to select between a safe and a common pool of resources (CPR) i.e., licensed and unlicensed bands, different access technologies, etc., while also the impact of pricing in protecting resource fragility is studied. Additionally, the above resource allocation problems are expanded in Public Safety Networks (PSNs) assisted by Unmanned Aerial Vehicles (UAVs), while also aspects related to network security against malign user behaviors are examined. Finally, all the above problems are thoroughly evaluated and tested via a series of arithmetic simulations with regards to the main characteristics of their operation, as well as against other approaches from the literature. In each case, important performance gains are identified with respect to the overall energy savings and increased spectrum utilization, while also the advantages of the proposed framework are mirrored in the improvement of the satisfaction and the superior Quality of Service of each user within the network. Lastly, the flexibility and scalability of this work allow for interesting applications in other domains related to resource allocation in wireless networks and beyond

Mobile Edge Cloud: Intelligent deployment and services for 5G Indoor Network

This thesis was submitted for the award of doctor of Philosophy and was awarded by Brunel University LondonFifth-Generation (5G) mobile networks are expected to perform according to the stringent performance targets assigned by standardization committees. Therefore, significant changes are proposed to the network infrastructure to achieve the expected performance levels. Network Function Virtualization, cloud computing and Software Defined Networks are some of the main technologies being utilised to ensure flexible network design, with optimum performance and efficient resource utilization. The aforementioned technologies are shifting the network architecture into service-based rather device-based architecture. In this regard, this thesis provides experimental investigation, design, implementation and evaluation of various multimedia services along with integration design and caching solution for 5G indoor network. The multimedia services are targeting the enhancement of UEs’ Quality of Experience, by exploiting the intelligence offered by the synergy between SDN and NFV technologies, to design and develop new multimedia solutions with improved QoE. The caching solution is designed to achieve a good trade-off between latency reduction and resource utilization that satisfies efficient network performance and resource utilization. The proposed network integration design targets deploying IoRL gNB with its innovative intelligent services. It have successfully achieved lower overhead signalling compared to the traditional network architectures. Whilst all of the proposed solutions have proven to provide enhancement to the system performance, the testing results for the multimedia services showed high QoS performance parameters in the form of zero packet loss due to route switching, very high throughput and 0.03 ms jitter. The caching solution test results provided up to 300% server utilization improvement (based on the deployed scenario) with negligible extra delay cost (0.5ms). As for the proposed integration design, the quantification of the performance enhancement is represented by the amount of the reduced overhead signalling. In the case of Intra-secondary gNB handover within the same Main eNB, the back-haul signalling for the AMF was reduced 100% while the overall overhead signalling is reduced by 50% compared to traditional deployment architecture.European Union’s Horizon 2020 research progra

A Localization System for Optimizing the Deployment of Small Cells in 2-Tier Heterogeneous Wireless Networks

Due to the ever growing population of mobile device users and expansion on the number of devices and applications requiring data usage, there is an increasing demand for improved capacity in wireless cellular networks. Cell densification and 2-tier heterogeneous networks (HetNets) are two solutions which will assist 5G systems in meeting these growing capacity demands. Small-cell deployment over existing heterogeneous networks have been considered by researchers. Different strategies for deploying these small-cells within the existing network among which are random, cell-edge and high user concentration (HUC) have also been explored. Small cells deployed on locations of HUC offloads traffic from existing network infrastructure, ensure good Quality of Service (QoS) and balanced load in the network but there is a challenge of identifying HUC locations. There has been considerable research performed into techniques for determining user location and cell deployment. Currently localization can be achieved using time dependent methods such as Time of Arrival (ToA), Time Difference of Arrival (TDoA), or Global Positioning Systems (GPS). GPS based solutions provide high accuracy user positioning but suffer from concerns over user privacy, and other time dependent approaches require regular synchronization which can be difficult to achieve in practice. Alternatively, Received Signal Strength (RSS) based solutions can provide simple anonymous user data, requiring no extra hardware within the mobile handset but often rely on triangulation from adjacent Base Stations (BS). In mobile cellular networks such solutions are therefore often only applicable near the cell edge, as installing additional BS would increase the complexity and cost of a network deployment. The work presented in this thesis overcomes these limitations by providing an observer system for wireless networks that can be used to periodically monitor the cell coverage area and identify regions of high concentrations of users for possible small cell deployment in 2-tier heterogeneous networks. The observer system comprises of two collinear antennas separated by λ/2. The relative phase of each antenna was varied using a phase shifter so that the combined output of the two antennas were used to create sum and difference radiation patterns, and to steer the antenna radiation pattern creating different azimuth positions for AoA estimation. Statistical regression analysis was used to develop range estimation models based on four different environment empirical pathloss models for user range estimation. Users were located into clusters by classifying them into azimuth-range classes and counting the number of users in each class. Locations for small cell deployment were identified based on class population. BPEM, ADEM, BUEM, EARM and NLOS models were developed for more accurate range estimation. A prototype system was implemented and tested both outdoor and indoor using a network of WiFi nodes. Experimental results show close relationship with simulation and an average PER in range estimation error of 80% by applying developed error models. Based on both simulation and experiment, system showed good performance. By deploying micro-, pico-, or femto-cells in areas of higher user concentration, high data rates and good quality of service in the network can be maintained. The observer system provides the network manager with relative angle of arrival (AoA), distance estimation and relative location of user clusters within the cell. The observer system divides the cell into a series of azimuthal and range sectors, and determines which sector the users are located in. Simulation and a prototype design of the system is presented and results have shown system robustness and high accuracy for its purpose