Power Optimisation and Relay Selection in Cooperative Wireless Communication Networks

Cooperative communications have emerged as a significant concept to improve reliability and throughput in wireless systems. In cooperative networks, the idea is to implement a scheme in wireless systems where the nodes can harmonize their resources thereby enhancing the network performance in different aspects such as latency, BER and throughput. As cooperation spans from the basic idea of transmit diversity achieved via MIMO techniques and the relay channel, it aims to reap somewhat multiple benefits of combating fading/burst errors, increasing throughput and reducing energy use. Another major benefit of cooperation in wireless networks is that since the concept only requires neighbouring nodes to act as virtual relay antennas, the concept evades the negative impacts of deployment costs of multiple physical antennas for network operators especially in areas where they are difficult to deploy. In cooperative communications energy efficiency and long network lifetimes are very important design issues, the focus in this work is on ad hoc and sensor network varieties where the nodes integrate sensing, processing and communication such that their cooperation capabilities are subject to power optimisation. As cooperation communications leads to trade-offs in Quality of Services and transmit power, the key design issue is power optimisation to dynamically combat channel fluctuations and achieve a net reduction of transmit power with the goal of saving battery life. Recent researches in cooperative communications focus on power optimisation achieved via power control at the PHY layer, and/or scheduling mechanism at the MAC layer. The approach for this work will be to review the power control strategy at the PHY layer, identify their associated trade-offs, and use this as a basis to propose a power control strategy that offers adaptability to channel conditions, the road to novelty in this work is a channel adaptable power control algorithm that jointly optimise power allocation, modulation strategy and relay selection. Thus, a novel relay selection method is developed and implemented to improve the performance of cooperative wireless networks in terms of energy consumption. The relay selection method revolves on selection the node with minimum distance to the source and destination. The design is valid to any wireless network setting especially Ad-hoc and sensor networks where space limitations preclude the implementation of bigger capacity battery. The thesis first investigates the design of relay selection schemes in cooperative networks and the associated protocols. Besides, modulation strategy and error correction code impact on energy consumption are investigated and the optimal solution is proposed and jointly implemented with the relay selection method. The proposed algorithm is extended to cooperative networks in which multiple nodes participate in cooperation in fixed and variable rate system. Thus, multi relay selection algorithm is proposed to improve virtual MIMO performance in terms of energy consumption. Furthermore, motivated by the trend of cell size optimisation in wireless networks, the proposed relay selection method is extended to clustered wireless networks, and jointly implemented with virtual clustering technique. The work will encompass three main stages: First, the cooperative system is designed and two major protocols Decode and Forward (DF) and amplify and forward (AF) are investigated. Second, the proposed algorithm is modelled and tested under different channel conditions with emphasis on its performance using different modulation strategies for different cooperative wireless networks. Finally, the performance of the proposed algorithm is illustrated and verified via computer simulations. Simulation results show that the distance based relay selection algorithm exhibits an improved performance in terms of energy consumption compared to the conventional cooperative schemes under different cooperative communication scenarios

Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting

Recently, interest on the utilization of unmanned aerial vehicles (UAVs) has aroused. Specifically, UAVs can be used in cellular networks as aerial users for delivery, surveillance, rescue search, or as an aerial base station (aBS) for communication with ground users in remote uncovered areas or in dense environments requiring prompt high capacity. Aiming to satisfy the high requirements of wireless aerial networks, several multiple access techniques have been investigated. In particular, space-division multiple access(SDMA) and power-domain non-orthogonal multiple access (NOMA) present promising multiplexing gains for aerial downlink and uplink. Nevertheless, these gains are limited as they depend on the conditions of the environment. Hence, a generalized scheme has been recently proposed, called rate-splitting multiple access (RSMA), which is capable of achieving better spectral efficiency gains compared to SDMA and NOMA. In this paper, we present a comprehensive survey of key multiple access technologies adopted for aerial networks, where aBSs are deployed to serve ground users. Since there have been only sporadic results reported on the use of RSMA in aerial systems, we aim to extend the discussion on this topic by modelling and analyzing the weighted sum-rate performance of a two-user downlink network served by an RSMA-based aBS. Finally, related open issues and future research directions are exposed.Comment: 16 pages, 6 figures, submitted to IEEE Journa

Allocation of Communication and Computation Resources in Mobile Networks

Konvergence komunikačních a výpočetních technologií vedlo k vzniku Multi-Access Edge Computing (MEC). MEC poskytuje výpočetní výkon na tzv. hraně mobilních sítí (základnové stanice, jádro mobilní sítě), který lze využít pro optimalizaci mobilních sítí v reálném čase. Optimalizacev reálném čase je umožněna díky nízkému komunikačnímu zpoždění například v porovnání s Mobile Cloud Computing (MCC). Optimalizace mobilních sítí vyžaduje informace o mobilní síti od uživatelských zařízeních, avšak sběr těchto informací využívá komunikační prostředky, které jsou využívány i pro přenos uživatelských dat. Zvyšující se počet uživatelských zařízení, senzorů a taktéž komunikace vozidel tvoří překážku pro sběr informací o mobilních sítích z důvodu omezeného množství komunikačních prostředků. Tudíž je nutné navrhnout řešení, která umožní sběr těchto informací pro potřeby optimalizace mobilních sítí. V této práci je navrženo řešení pro komunikaci vysokého počtu zařízeních, které je postaveno na využití přímé komunikace mezi zařízeními. Pro motivování uživatelů, pro využití přeposílání dat pomocí přímé komunikace mezi uživateli je navrženo přidělování komunikačních prostředků jenž vede na přirozenou spolupráci uživatelů. Dále je provedena analýza spotřeby energie při využití přeposílání dat pomocí přímé komunikace mezi uživateli pro ukázání jejích výhod z pohledu spotřeby energie. Pro další zvýšení počtu komunikujících zařízení je využito mobilních létajících základových stanic (FlyBS). Pro nasazení FlyBS je navržen algoritmus, který hledá pozici FlyBS a asociaci uživatel k FlyBS pro zvýšení spokojenosti uživatelů s poskytovanými datovými propustnostmi. MEC lze využít nejen pro optimalizaci mobilních sítí z pohledu mobilních operátorů, ale taktéž uživateli mobilních sítí. Tito uživatelé mohou využít MEC pro přenost výpočetně náročných úloh z jejich mobilních zařízeních do MEC. Z důvodu mobility uživatel je nutné nalézt vhodně přidělení komunikačních a výpočetních prostředků pro uspokojení uživatelských požadavků. Tudíž je navržen algorithmus pro výběr komunikační cesty mezi uživatelem a MEC, jenž je posléze rozšířen o přidělování výpočetných prostředků společně s komunikačními prostředky. Navržené řešení vede k snížení komunikačního zpoždění o desítky procent.The convergence of communication and computing in the mobile networks has led to an introduction of the Multi-Access Edge Computing (MEC). The MEC combines communication and computing resources at the edge of the mobile network and provides an option to optimize the mobile network in real-time. This is possible due to close proximity of the computation resources in terms of communication delay, in comparison to the Mobile Cloud Computing (MCC). The optimization of the mobile networks requires information about the mobile network and User Equipment (UE). Such information, however, consumes a significant amount of communication resources. The finite communication resources along with the ever increasing number of the UEs and other devices, such as sensors, vehicles pose an obstacle for collecting the required information. Therefore, it is necessary to provide solutions to enable the collection of the required mobile network information from the UEs for the purposes of the mobile network optimization. In this thesis, a solution to enable communication of a large number of devices, exploiting Device-to-Device (D2D) communication for data relaying, is proposed. To motivate the UEs to relay data of other UEs, we propose a resource allocation algorithm that leads to a natural cooperation of the UEs. To show, that the relaying is not only beneficial from the perspective of an increased number of UEs, we provide an analysis of the energy consumed by the D2D communication. To further increase the number of the UEs we exploit a recent concept of the flying base stations (FlyBSs), and we develop a joint algorithm for a positioning of the FlyBS and an association of the UEs to increase the UEs satisfaction with the provided data rates. The MEC can be exploited not only for processing of the collected data to optimize the mobile networks, but also by the mobile users. The mobile users can exploit the MEC for the computation offloading, i.e., transferring the computation from their UEs to the MEC. However, due to the inherent mobility of the UEs, it is necessary to determine communication and computation resource allocation in order to satisfy the UEs requirements. Therefore, we first propose a solution for a selection of the communication path between the UEs and the MEC (communication resource allocation). Then, we also design an algorithm for joint communication and computation resource allocation. The proposed solution then lead to a reduction in the computation offloading delay by tens of percent