On the efficiency of dynamic licensed shared access for 5G/6G wireless communications

The licensed shared access (LSA) is a spectrum licensing scheme authorizing additional new users (the licensees) to dynamically share the same spectrum with the old users (the incumbents). Contained in the terms of the spectrum usage authorization is a set of strict protective measures for the incumbent system which introduce extra restrictions on the licensee operations. Such measures imply that the licensee’s access to the spectrum can be revoked or restricted at any time which may result in the degradation of critical performance metrics of the latter. Addressing this issue and the accompanying challenges as we enter the 5G zettabytes era motivates the research problems addressed in this thesis. A vertical LSA spectrum sharing involving a mobile network operator (MNO) as the licensee and two categories of incumbent including the aeronautical telemetry, and a group of terrestrial public and ancillary wireless services is adopted in this thesis. Firstly, an analytical examination of the uplink and downlink licensee’s transmit power, when its spectrum access right is revoked (i.e., the limited transmit power) is done. Then a power allocation scheme that maximizes the energy efficiency (EE) of the licensee when it is operating with limited transmit power is proposed. Simulation results reveal the impact of the LSA spectrum access revocation on the allowable transmit power of the licensee as a function of the effect of different interference propagation path and the transmission direction. A comparison of the proposed optimal power allocation method with the equal power allocation (EPA) method further shows considerable improvement in the achievable EE of the licensee. Furthermore, in the LSA, the achievable spectrum efficiency (SE) of the licensee is limited by the interference threshold constraint set by the incumbent’s protective measures. Consequent on this, we propose an SE maximization of the licensee’s system subject to the incumbent interference threshold constraint. Furthermore, the LSA band spectral utilization was characterised as a function of the licensee’s achievable SE and the statistics of the LSA spectrum availability. The obtained results provide quantitative insights for practical system design and deployment of the LSA system, especially when compared to the results obtained in the maximization of the EE. In particular, the effect of variations in critical operational parameters throws up interesting network design trade-off challenge, worthy of consideration. This informs the subsequent multi objective optimization of the EE-SE trade-off investigated next. Interestingly, the obtained results indicate that with careful selection of the licensee eNodeB coverage radius, transmit power, and number of user equipment per eNodeB coverage area, one can engineer the best possible trade-off between the spectrum and energy efficiency in practical LSA deployment. A major LSA feature is guaranteeing predictable quality of service (QoS) for both the incumbent and the licensee systems. In terrestrial implementation, the reduction in the achievable data rate caused by the incumbents’ protective measures, may violate guaranteed QoS in the licensee system. To address this issue, we propose a LSA - based hybrid aerialterrestrial system with drone base station (D-BS). Simulation results show that using the proposed scheme, the licensee, when operating under the incumbents’ imposed restrictions, is able to achieve the QoS data rate requirements of the users on its network. In conclusion, the findings in this research indicates that the dynamic LSA is a practically viable solution to the spectrum management requirements of the emerging vertical wireless technologies in 5G and beyond

On three use cases of multi-connectivity paradigm in emerging wireless networks

As envisioned by global network operators, the increasing trend of data traffic demand is expected to continue with exponential growth in the coming years. To cope with this rapid increase, significant efforts from the research community, industry and even regulators have been focused towards improving two main aspects of the wireless spectrum: (i) spectrum capacity and (ii) spectral efficiency. Concerning the spectrum capacity enhancement, the multi-connectivity paradigm has been seen to be fundamentally important to solve the capacity problem in the next generation networks. Multi-connectivity is a feature that allows wireless devices to establish and maintain multiple simultaneous connections across homogeneous or heterogeneous technologies. In this thesis, we focus on identifying the core issues in applying the multi-connectivity paradigm for different use cases and propose novel solutions to address them. Specifically, this thesis studies three use cases of the multi-connectivity paradigm. First, we study the uplink/downlink decoupling problem in 4G networks. More specifically, we focus on the user association problem in the decoupling context, which is considered challenging due to the conflicting objectives of different entities (e.g., mobile users and base stations) in the system. We use a combination of matching theory and stochastic geometry to reconcile competing objectives between users in the uplink/downlink directions and also from the perspective of base stations. Second, we tackle the spectrum aggregation problem for wireless backhauling links in unlicensed opportunistic shared spectrum bands, specifically, TV White Space (TVWS) spectrum. In relation to this, we present a DIY mobile network deployment model to accelerate the roll-out of high-end mobile services in rural and developing regions. As part of this model, we highlight the importance of low-cost and high-capacity backhaul infrastructure for which TVWS spectrum can be exploited. Building on that, we conduct a thorough analytical study to identify the characteristics of TVWS in rural areas. Our study sheds light on the nature of TVWS spectrum fragmentation for the backhauling use case, which in turn poses requirements for the design of spectrum aggregation systems for TVWS backhaul. Motivated by these findings, we design and implement WhiteHaul, a flexible platform for spectrum aggregation in TVWS. Three challenges have been tackled in this work. First, TVWS spectrum is fragmented in that the spectrum is available in non-contiguous manner. To fully utilize the available spectrum, multiple radios should be enabled to work simultaneously. However, all the radios have to share only a single antenna. The key challenge is to design a system architecture that is capable of achieving different aggregation configurations while avoiding the interference. Second, the heterogeneous nature of the available spectrum (i.e., in terms of bandwidth and link characteristics) requires a design of efficient traffic distribution algorithm that takes into account these factors. Third, TVWS is unlicensed opportunistic shared spectrum. Thus, the coordination mechanism between the two nodes of backhauling link is essential to enable seamless channel switching. Third, we study the integration of multiple radio access technologies (RATs) in the context of 4G/5G networks. More specifically, we study the potential gain of enabling the Multi-RAT integration at the Packet Data Convergence Protocol (PDCP) layer compared with doing it at the transport layer. In this work, we consider ultra-reliable low-latency communication (URLLC) as one of the motivating services. This work tackles the different challenges that arise from enabling the Multi-RAT integration at the PDCP layer, including, packet reordering and traffic scheduling

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