Sum-Rate Analysis for High Altitude Platform (HAP) Drones with Tethered Balloon Relay

High altitude platform (HAP) drones can provide broadband wireless connectivity to ground users in rural areas by establishing line-of-sight (LoS) links and exploiting effective beamforming techniques. However, at high altitudes, acquiring the channel state information (CSI) for HAPs, which is a key component to perform beamforming, is challenging. In this paper, by exploiting an interference alignment (IA) technique, a novel method for achieving the maximum sum-rate in HAP-based communications without CSI is proposed. In particular, to realize IA, a multiple-antenna tethered balloon is used as a relay between multiple HAP drones and ground stations (GSs). Here, a multiple-input multiple-output X network system is considered. The capacity of the considered M*N X network with a tethered balloon relay is derived in closed-form. Simulation results corroborate the theoretical findings and show that the proposed approach yields the maximum sum-rate in multiple HAPs-GSs communications in absence of CSI. The results also show the existence of an optimal balloon's altitude for which the sum-rate is maximized.Comment: Accepted in IEEE Communications Letter

The Coverage, Capacity and Coexistence of Mixed High Altitude Platform and Terrestrial Segments

This thesis explores the coverage, capacity and coexistence of High Altitude Platform (HAP) and terrestrial segments in the same service area. Given the limited spectrum available, mechanisms to manage the co-channel interference to enable effective coexistence between the two infrastructures are examined. Interference arising from the HAP, caused by the relatively high transmit power and the antenna beam profile, has the potential to significantly affect the existing terrestrial system on the ground if the HAP beams are deployed without a proper strategy. Beam-pointing strategies exploiting phased array antennas on the HAPs are shown to be an effective way to place the beams, with each of them forming service cells onto the ground in the service area, especially dense user areas. Using a newly developed RF clustering technique to better point the cells over an area of a dense group of users, it is shown that near maximum coverage of 96% of the population over the service area can be provided while maintaining the coexistence with the existing terrestrial system. To improve the user experience at the cell edge, while at the same time improving the overall capacity of the system, Joint Transmission – Coordinated Multipoint (JT-CoMP) is adapted for a HAP architecture. It is shown how the HAP can potentially enable the tight scheduling needed to perform JT-CoMP due to the centralisation of all virtual E-UTRAN Node Bs (eNodeBs) on the HAP. A trade-off between CINR gain and loss of capacity when adapting JT-CoMP into the HAP system is identified, and strategies to minimise the trade-off are considered. It is shown that 57% of the users benefit from the JT-CoMP. In order to enable coordination between the HAP and terrestrial segments, a joint architecture based on a Cloud – Radio Access Network (C-RAN) system is introduced. Apart from adapting a C-RAN based system to centrally connect the two segments together, the network functional split which varies the degree of the centralised processing is also considered to deal with the limitations of HAP fronthaul link requirements. Based on the fronthaul link requirements acquired from the different splitting options, the ground relay station diversity to connect the HAP to centralised and distributed units (CUs and DUs) is also considered

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

Enhancement in Network Architectures for Future Wireless Systems

This thesis investigates innovative wireless deployment strategies for dense ultra-small cells networks. In particular, this thesis focuses on improving the resource utilisation, reliability and energy efficiency of future wireless networks by exploiting the existing flexibility in the network architecture. The wireless backhaul configurations and topology management schemes proposed in this thesis consider a dense urban area scenario with static outdoor users. In the first part of this thesis, a novel mm-wave dual-hop backhaul network architecture is investigated for future cellular networks to achieve better resource utilization and user experience at the expense of path diversity available in dense deployment of base stations. The system-level performance is analysed and compared for the backhaul section using mm-wave band. Followed by the performance of the network model which is validated using a Markov Model. The second part of the thesis illustrates a topology management strategy for the same dual-hop backhaul network architecture. The same path diversity is also utilized by the topology management technique to achieve high energy savings and improvement in performance. The results show that the proposed architecture facilitates the topology management process to turn-off some portion of the network in order to minimize the power consumption and can deliver Quality-of-Service guarantee. Finally, the methodology to admit new users into the system, to best control the capacity resource, is investigated for radio resource management in a multi hop, multi-tier heterogeneous network. A novel analytical Markov Model based on a two-dimensional state-transition rate diagram is developed to describe system behaviour of a coexistence scenarios containing two different sets of users, which have full and limited access to the network resources. Different levels of restriction to access the network by specific groups of users are compared and conclusions are drawn

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

Effect of imperfect CSI on interference alignment in multiple-High Altitude Platforms based communication

Interference Alignment (IA) offers maximum sum-rate in a wireless X channel. Though IA was proposed for maximizing sum-rate, its application for exploiting high data rate in air-to-ground communication has not been explored much. In this paper, the application of IA in a High Altitude Platform (HAP) to Ground Station (GS) communication is considered. Recent studies suggest that IA provides maximum sum-rate for a 2 × 2 transmitter–receiver system. However, independent channels are required to achieve IA conditions. The application of IA is proposed here for a generalized channel in an HAP-to-GS communication link that takes into account angle-of-departure and angle-of-arrival at the transmitter and at the receiver, respectively. We verify the minimum distance criteria in receiving nodes to achieve independent channels. Receivers are placed at optimal distance for best error performance. Furthermore, in view of an actual scenario, we investigate the effect of imperfect CSI, resulting from changes in imperfection in HAP's stabilization, in the performance of our model. The performance, in terms of Bit Error Rate (BER), is presented for IA and non-IA based communication. For this purpose, an analytical expression is developed for the probability of error. A perfect match is shown between the error rate measured with Monte Carlo simulations and the error probability found using the derived analytical expressions

Mobile and Wireless Communications

Mobile and Wireless Communications have been one of the major revolutions of the late twentieth century. We are witnessing a very fast growth in these technologies where mobile and wireless communications have become so ubiquitous in our society and indispensable for our daily lives. The relentless demand for higher data rates with better quality of services to comply with state-of-the art applications has revolutionized the wireless communication field and led to the emergence of new technologies such as Bluetooth, WiFi, Wimax, Ultra wideband, OFDMA. Moreover, the market tendency confirms that this revolution is not ready to stop in the foreseen future. Mobile and wireless communications applications cover diverse areas including entertainment, industrialist, biomedical, medicine, safety and security, and others, which definitely are improving our daily life. Wireless communication network is a multidisciplinary field addressing different aspects raging from theoretical analysis, system architecture design, and hardware and software implementations. While different new applications are requiring higher data rates and better quality of service and prolonging the mobile battery life, new development and advanced research studies and systems and circuits designs are necessary to keep pace with the market requirements. This book covers the most advanced research and development topics in mobile and wireless communication networks. It is divided into two parts with a total of thirty-four stand-alone chapters covering various areas of wireless communications of special topics including: physical layer and network layer, access methods and scheduling, techniques and technologies, antenna and amplifier design, integrated circuit design, applications and systems. These chapters present advanced novel and cutting-edge results and development related to wireless communication offering the readers the opportunity to enrich their knowledge in specific topics as well as to explore the whole field of rapidly emerging mobile and wireless networks. We hope that this book will be useful for students, researchers and practitioners in their research studies

Good practices for agrobiodiversity management

Native agricultural genetic resources have been generally under-valued, therefore, some initiatives have been taken through Global In-situ agrobiodiversity project joinly implemented by NARC, LI-BIRD and Bioversity International since 1997 in Nepal for conservation and sustainable use of agrobiodiversity on-farm. Global in-situ project (1997-2006) has developed many good practices for agrobiodiversity management which are published in On-farm Management of Agricultural Biodiversity in Nepal: Good Practices 2006 (B Sthapit, P Shrestha and M Upadyay, eds). A good practice is a process or methodology or action that is effective and successful; environmentally, economically and socially sustainable; technically feasible; inherently participatory; replicable and adaptable, that has been proven to work well and produce good results. It is a successful experience tested and validated in achieving its objective. For further widening the scope of good practices in the country, NAGRC, LI-BIRD and Bioversity International have generated, tested and adapted a number of good practices in four sites, Jungu, Dolakha; Ghapanpokhara, Lamjung; Hanku, Jumla; and Chippra, Humla through a project Integrating Traditional Crop Genetic Diversity into Technology: Using a Biodiversity Portfolio Approach to Buffer against Unpredictable Environmental Change in the Nepal Himalayas , commonly called as Local Crop Project (LCP) from 2014 to 2019. Good practices listed here are well tested and adapted by the communtiies in the fields, shown their positive impact, shared and discussed among the relevant stakholders. Project team have tested and validated many good practices, however, we have included 22 good practices that are worth sharing for its dessimination and mainstreaming. These practices, though specially based on eight crops (rice, bean, barley, foxtail millet, proso millet, amaranth and buckwheat), can be widely applicable to other agricultural genetic ressources in different locations, national and globally