On the performance of aerial LTE base-stations for public safety and emergency recovery

Recent events have shown that in the aftermath of an unexpected incident, communication infrastructures play an important role in supporting critical services. Airborne communication networks have been recently studied for the provision of wireless communication services and it is a promising candidate for rapidly deployable and resilient emergency networks. However, the choice of communication technologies from Aerial platforms is a challenging issue and depends on a variety of factors including platform payload capacity, coverage and capacity requirements, to name a few. In this paper, we investigate the performance of 4G LTE-WiFi multimode base stations deployed on airborne platforms which provides coverage for first responders during emergencies. We present an adapted simulation model for the analysis of hybrid aerial-terrestrial systems and study the impact of platform elevation and mobility on the cell coverage and channel capacity. Performance analysis with a platform deployment of a single Aerial Base Station (eNodeB) corroborates that airborne units with 4G communication capabilities are very promising candidates for robust communication links during emergency relief operations

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

Performance evaluation of future wireless networks: node cooperation and aerial networks

Perhaps future historians will only refer to this era as the \emph{information age}, and will recognize it as a paramount milestone in mankind progress. One of the main pillars of this age is the ability to transmit and communicate information effectively and reliably, where wireless radio technology became one of the most vital enablers for such communication. A growth in radio communication demand is notably accelerating in a never-resting pace, pausing a great challenge not only on service providers but also on researches and innovators to explore out-of-the-box technologies. These challenges are mainly related to providing faster data communication over seamless, reliable and cost efficient wireless network, given the limited availability of physical radio resources, and taking into consideration the environmental impact caused by the increasing energy consumption. Traditional wireless communication is usually deployed in a cellular manner, where fixed base stations coordinate radio resources and play the role of an intermediate data handler. The concept of cellular networks and hotspots is widely adopted as the current stable scheme of wireless communication. However in many situations this fixed infrastructure could be impaired with severe damages caused by natural disasters, or could suffer congestions and traffic blockage. In addition to the fact that in the current networks any mobile-to-mobile data sessions should pass through the serving base station that might cause unnecessary energy consumption. In order to enhance the performance and reliability of future wireless networks and to reduce its environmental footprint, we explore two complementary concepts: the first is node cooperation and the second is aerial networks. With the ability of wireless nodes to cooperate lays two main possible opportunities; one is the ability of the direct delivery of information between the communicating nodes without relaying traffic through the serving base station, thus reducing energy consumption and alleviating traffic congestion. A second opportunity would be that one of the nodes helps a farther one by relaying its traffic towards the base station, thus extending network coverage and reliability. Both schemes can introduce significant energy saving and can enhance the overall availability of wireless networks in case of natural disasters. In addition to node cooperation, a complementary technology to explore is the \emph{aerial networks} where base stations are airborne on aerial platforms such as airships, UAVs or blimps. Aerial networks can provide a rapidly deployable coverage for remote areas or regions afflicted by natural disasters or even to patch surge traffic demand in public events. Where node cooperation can be implemented to complement both regular terrestrial coverage and to complement aerial networks. In this research, we explore these two complementary technologies, from both an experimental approach and from an analytic approach. From the experimental perspective we shed the light on the radio channel properties that is hosting terrestrial node cooperation and air-to-ground communication, namely we utilize both simulation results and practical measurements to formulate radio propagation models for device-to-device communication and for air-to-ground links. Furthermore we investigate radio spectrum availability for node cooperation in different urban environment, by conductive extensive mobile measurement survey. Within the experimental approach, we also investigate a novel concept of temporary cognitive femtocell network as an applied solution for public safety communication networks during the aftermath of a natural disaster. While from the analytical perspective, we utilize mathematical tools from stochastic geometry to formulate novel analytical methodologies, explaining some of the most important theoretical boundaries of the achievable enhancements in network performance promised by node cooperation. We start by determining the estimated coverage and rate received by mobile users from convectional cellular networks and from aerial platforms. After that we optimize this coverage and rate ensuring that relay nodes and users can fully exploit their coverage efficiently. We continue by analytically quantifying the cellular network performance during massive infrastructure failure, where some nodes play the role of low-power relays forming multi-hop communication links to assist farther nodes outside the reach of the healthy network coverage. In addition, we lay a mathematical framework for estimating the energy saving of a mediating relay assisting a pair of wireless devices, where we derive closed-form expressions for describing the geometrical zone where relaying is energy efficient. Furthermore, we introduce a novel analytic approach in analyzing the energy consumption of aerial-backhauled wireless nodes on ground fields through the assistance of an aerial base station, the novel mathematical framework is based on Mat\'{e}rn hard-core point process. Then we shed the light on the points interacting of these point processes quantifying their main properties. Throughout this thesis we relay on verifying the analytic results and formulas against computer simulations using Monte-Carlo analysis. We also present practical numerical examples to reflect the usefulness of the presented methodologies and results in real life scenarios. Most of the work presented in this dissertation was published in-part or as a whole in highly ranked peer-reviewed journals, conference proceedings, book chapters, or otherwise currently undergoing a review process. These publications are highlighted and identified in the course of this thesis. Finally, we wish the reader to enjoy exploring the journey of this thesis, and hope it will add more understanding to the promising new technologies of aerial networks and node cooperation

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