A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial

Tutorial on LTE/LTE-A Cellular Network Dimensioning Using Iterative Statistical Analysis

LTE is the fastest growing cellular technology and is expected to increase its footprint in the coming years, as well as progress toward LTE-A. The race among operators to deliver the expected quality of experience to their users is tight and demands sophisticated skills in network planning. Radio network dimensioning (RND) is an essential step in the process of network planning and has been used as a fast, but indicative, approximation of radio site count. RND is a prerequisite to the lengthy process of thorough planning. Moreover, results from RND are used by players in the industry to estimate preplanning costs of deploying and running a network; thus, RND is, as well, a key tool in cellular business modelling. In this work, we present a tutorial on radio network dimensioning, focused on LTE/LTE-A, using an iterative approach to find a balanced design that mediates among the three design requirements: coverage, capacity, and quality. This approach uses a statistical link budget analysis methodology, which jointly accounts for small and large scale fading in the channel, as well as loading due to traffic demand, in the interference calculation. A complete RND manual is thus presented, which is of key importance to operators deploying or upgrading LTE/LTE-A networks for two reasons. It is purely analytical, hence it enables fast results, a prime factor in the race undertaken. Moreover, it captures essential variables affecting network dimensions and manages conflicting targets to ensure user quality of experience, another major criterion in the competition. The described approach is compared to the traditional RND using a commercial LTE network planning tool. The outcome further dismisses the traditional RND for LTE due to unjustified increase in number of radio sites and related cost, and motivates further research in developing more effective and novel RND procedures

A survey on hybrid beamforming techniques in 5G : architecture and system model perspectives

The increasing wireless data traffic demands have driven the need to explore suitable spectrum regions for meeting the projected requirements. In the light of this, millimeter wave (mmWave) communication has received considerable attention from the research community. Typically, in fifth generation (5G) wireless networks, mmWave massive multiple-input multiple-output (MIMO) communications is realized by the hybrid transceivers which combine high dimensional analog phase shifters and power amplifiers with lower-dimensional digital signal processing units. This hybrid beamforming design reduces the cost and power consumption which is aligned with an energy-efficient design vision of 5G. In this paper, we track the progress in hybrid beamforming for massive MIMO communications in the context of system models of the hybrid transceivers' structures, the digital and analog beamforming matrices with the possible antenna configuration scenarios and the hybrid beamforming in heterogeneous wireless networks. We extend the scope of the discussion by including resource management issues in hybrid beamforming. We explore the suitability of hybrid beamforming methods, both, existing and proposed till first quarter of 2017, and identify the exciting future challenges in this domain

An efficient multichannel wireless sensor networks MAC protocol based on IEEE 802.11 distributed co-ordinated function.

This research aimed to create new knowledge and pioneer a path in the area relating to future trends in the WSN, by resolving some of the issues at the MAC layer in Wireless Sensor Networks. This work introduced a Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks. This work commenced by surveying different protocols: contention-based MAC protocols, transport layer protocols, cross-layered design and multichannel multi-radio assignments. A number of existing protocols were analysed, each attempting to resolve one or more problems faced by the current layers. The 802.15.4 performed very poorly at high data rate and at long range. Therefore 802.15.4 is not suitable for sensor multimedia or surveillance system with streaming data for future multichannel multi-radio systems. A survey on 802.11 DCF - which was designed mainly for wireless networks –supports and confirm that it has a power saving mechanism which is used to synchronise nodes. However it uses a random back-off mechanism that cannot provide deterministic upper bounds on channel access delay and as such cannot support real-time traffic. The weaknesses identified by surveying this protocol form the backbone of this thesis The overall aim for this thesis was to introduce multichannel with single radio as a new paradigm for IEEE 802.11 Distributed Coordinated Function (DCF) in wireless sensor networks (WSNs) that is used in a wide range of applications, from military application, environmental monitoring, medical care, smart buildings and other industry and to extend WSNs with multimedia capability which sense for instance sounds or motion, video sensor which capture video events of interest. Traditionally WSNs do not need high data rate and throughput, since events are normally captured periodically. With the paradigm shift in technology, multimedia streaming has become more demanding than data sensing applications as such the need for high data rate protocol for WSN which is an emerging technology in this area. The IEEE 802.11 can support data rates up to 54Mbps and 802.11 DCF was designed specifically for use in wireless networks. This thesis focused on designing an algorithm that applied multichannel to IEEE 802.11 DCF back-off algorithm to reduce the waiting time of a node and increase throughput when attempting to access the medium. Data collection in WSN tends to suffer from heavy congestion especially nodes nearer to the sink node. Therefore, this thesis proposes a contention based MAC protocol to address this problem from the inspiration of the 802.11 DCF backoff algorithm resulting from a comparison of IEEE 802.11 and IEEE 802.15.4 for Future Green Multichannel Multi-radio Wireless Sensor Networks

Optimisation of a propagation model for last mile connectivity with low altitude platforms using machine learning

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonOur related research review on propagation models reveals six factors that are significant in last mile connectivity via LAP: path loss, elevation angle, LAP altitude, coverage area, power consumption, operation frequency, interference, and antenna type. These factors can help with monitoring system performance, network planning, coverage footprint, receivers’ line-of-sight, quality of service requirements, and data rates which may all vary in response to geomorphology characteristics. Several competing propagation models have been proposed over the years but whilst they collectively raise many shortcomings such as limited altitude up to few tens of meters, lack of cover across different environments, low perdition accuracy they also exhibit several advantages. Four propagation models, which are representatives of their types, have been selected since they exhibit advantages in relation to high altitude, wide coverage range, adaption across different terrains. In addition, all four have been extensively deployed in the past and as a result their correction factors have evolved over the years to yield extremely accurate results which makes the development and evaluation aspects of this research very precise. The four models are: ITU-R P.529-3, Okumura, Hata-Davidson, and ATG. The aim of this doctoral research is to design a new propagation model for last-mile connectivity using LAPs technology as an alternative to aerial base station that includes all six factors but does not exhibit any of the shortcomings of existing models. The new propagation model evolves from existing models using machine learning. The four models are first adapted to include the elevation angle alongside the multiple-input multiple-output diversity gain, our first novelty in propagation modelling. The four adapted models are then used as input in a Neural Network framework and their parameters are clustered in a Self-Organizing-Map using a minimax technique. The framework evolves an optimal propagation model that represents the main research contribution of this research. The optimal propagation model is deployed in two proof-of-concept applications, a wireless sensor network, and a cellular structure. The performance of the optimal model is evaluated and then validated against that of the four adapted models first in relation to predictions reported in the literature and then in the context of the two proof-of-concept applications. The predictions of the optimised model are significantly improved in comparison to those of the four adapted propagation models. Each of the two proof-of-concept applications also represent a research novelty.The Royal Saudi Embassy and the Saudi Cultural Bureau in London, and Taif University in the Kingdom of Saudi Arabia

Radio Resource Management Optimization For Next Generation Wireless Networks

The prominent versatility of today’s mobile broadband services and the rapid advancements in the cellular phones industry have led to a tremendous expansion in the wireless market volume. Despite the continuous progress in the radio-access technologies to cope with that expansion, many challenges still remain that need to be addressed by both the research and industrial sectors. One of the many remaining challenges is the efficient allocation and management of wireless network resources when using the latest cellular radio technologies (e.g., 4G). The importance of the problem stems from the scarcity of the wireless spectral resources, the large number of users sharing these resources, the dynamic behavior of generated traffic, and the stochastic nature of wireless channels. These limitations are further tightened as the provider’s commitment to high quality-of-service (QoS) levels especially data rate, delay and delay jitter besides the system’s spectral and energy efficiencies. In this dissertation, we strive to solve this problem by presenting novel cross-layer resource allocation schemes to address the efficient utilization of available resources versus QoS challenges using various optimization techniques. The main objective of this dissertation is to propose a new predictive resource allocation methodology using an agile ray tracing (RT) channel prediction approach. It is divided into two parts. The first part deals with the theoretical and implementational aspects of the ray tracing prediction model, and its validation. In the second part, a novel RT-based scheduling system within the evolving cloud radio access network (C-RAN) architecture is proposed. The impact of the proposed model on addressing the long term evolution (LTE) network limitations is then rigorously investigated in the form of optimization problems. The main contributions of this dissertation encompass the design of several heuristic solutions based on our novel RT-based scheduling model, developed to meet the aforementioned objectives while considering the co-existing limitations in the context of LTE networks. Both analytical and numerical methods are used within this thesis framework. Theoretical results are validated with numerical simulations. The obtained results demonstrate the effectiveness of our proposed solutions to meet the objectives subject to limitations and constraints compared to other published works

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.acceptedVersio

Reconfigurable antennas for adaptive MIMO communication systems

The requirements for the next generation wireless systems seek to provide reliable high data rate at low cost. Unfortunately the current wireless communication infrastructure is notfully equipped to over this unprecedented quality of service. Major obstacles include: limited bandwidth availability, limited transmit power, and signal strength uctuations which are intrinsic to the multivariate wireless channel. Multiple Input Multiple Output (MIMO) antenna systems have emerged as one of the most significant technical breakthrough in modern wireless communications able to satisfy these stringent requirements. However the necessity of assuring a high data rate in a large variety of environments while reducing the antenna array space occupation on portable devices requires an improvement in current MIMO technology. To overcome these limitations, we propose in this thesis, the use of reconfigurable antennas that adaptively change, through RF switches, their radiation properties and frequency of operation according to wireless channel characteristics.The key idea of this work is to show that reconfigurable antennas, through their capability to dynamically change their electrical and radiation properties, can be used to change the propagation characteristics of the wireless channel existing between the transmitting and receiving antennas. The proposed MIMO system breaks from the conventional wisdom that the wireless propagation channel cannot be changed intentionally by the transceivers in the link.Three different novel classes of electrically multi element reconfigurable antennas are proposed as suitable candidates for reconfigurable MIMO systems: i ) a reconfigurable printeddipole antenna array that exploits inter element mutual coupling to achieve pattern reconfigurability, ii ) circular patches capable of exciting higher order modes to achieve pattern and polarization diversity, and iii ) a metamaterial leaky wave array that can be reconfigured in pattern to achieve unprecedented degrees of pattern reconfigurability.To effectively use such antennas with actual communication systems, a low power consumption method for selecting the array configuration is proposed. This technique exploits the close relationship between the environment that surrounds the antenna array and the antenna radiation characteristics in order to select optimal array radiation patterns without the need for intense channel sensing or excessive training. A complete reconfigurable antenna system composed of mutli-element reconfigurable antennas and a control unit capable of efficently driving the antennas is proposed to deliver unprecedented system performance.Analytical models of the proposed system are used to fully characterize the functionality and performance of the technology. A complete evaluation of the proposed system is conducted through electromagnetic simulations and eld measurements collected with a channel sounder speciiically designed to measure the performance of multi element antennasystems. It is demonstrated that the novel multi element reconfigurable antenna system is capable of providing i ) increased data rate compared to common non reconfigurable antennas in single link communications as well as in multi-link ad hoc networks, ii ) reduced space occupation by the antenna on the communication device exploiting the principles of pattern and polarization diversity, iii ) reduced number of radio-frequency chains needed at the receiver/transmitter and iv ) reduced amount of transmit power for achieving performancecomparable to that of standard non reconfigurable antenna systems.Ph.D., Electrical Engineering -- Drexel University, 200