Optimizing Stochastic Small Base Station Deployment with Particle Swarm Technique

Small base stations (SBSs) play a vital role in 5G communication to improve the throughput of cellular networks. However, care needs to be taken to ensure that improving the throughput of a cellular network via SBS deployment does not lead to unacceptable interferences that negatively impact the network’s overall efficiency. The unpredictable nature of SBS deployment also has implications for energy consumption. This research study proposes a weighted- sum modified particle swarm optimization (PSO) algorithm to find the density of SBSs that maximizes the throughput and energy gains of a cellular network. A stochastic geometry approach is taken to the optimization process, and some form of SBS sleep strategies are also explored at high and low traffic levels. The study showed that the strategic sleep mode favours lower densities of SBSs at lower transmission power levels than the random sleep mode at low traffic levels. The strategic sleep mode selects higher densities of SBSs at higher transmission power levels than the random sleep mode at high traffic levels. The strategic sleep mode provided a better optimal solution to the SE and EE maximization problem at both high and low transmit levels. The proposed PSO algorithm generated all Pareto optimal fronts regardless of the network traffic level. In contrast, the ParetoSearch algorithm could generate the Pareto optimal front at only low traffic levels. The result of this study provides cellular network engineers with a means of simultaneously adjusting network parameters to achieve the desired throughput and energy savings in SBS-enhanced cellular networks

A Distributed Game Theoretic Approach for Blockchain-based Offloading Strategy

Keeping patients’ sensitive information secured and untampered in the e-Health system is of paramount importance. Emerging as a promising technology to build a secure and reliable distributed ledger, blockchain can protect data from being falsified, which has attracted much attention from both academia and industry. However, with limited computational resources, medical IoT devices do not have efficient ability to fulfill the functionalities as a full node in wireless blockchain network (WBN). Facing this dilemma, Mobile Edge Computing (MEC) brings us dawn and hope through offloading the high resource demanding blockchain functionalities at the IoT devices to the MEC. However, aiming to maximize the mining profit, most of existing offloading strategies have ignored the other needs of wireless devices, e.g., faster transaction writing. In this paper, according to different needs, blockchain nodes are firstly divided into two categories. One is blockchain users whose needs are faster transaction uploading, the other is blockchain miners whose goals are maximum revenue. Then, to maximize both the utilities of blockchain users and blockchain miners, a Stackelberg game is introduced to formulate the interaction between them. From the simulation results, this game is proved to converge to a unique optimal equilibrium

Fast and efficient energy-oriented cell assignment in heterogeneous networks

The cell assignment problem is combinatorial, with increased complexity when it is tackled considering resource allocation. This paper models joint cell assignment and resource allocation for cellular heterogeneous networks, and formalizes cell assignment as an optimization problem. Exact algorithms can find optimal solutions to the cell assignment problem, but their execution time increases drastically with realistic network deployments. In turn, heuristics are able to find solutions in reasonable execution times, but they get usually stuck in local optima, thus failing to find optimal solutions. Metaheuristic approaches have been successful in finding solutions closer to the optimum one to combinatorial problems for large instances. In this paper we propose a fast and efficient heuristic that yields very competitive cell assignment solutions compared to those obtained with three of the most widely-used metaheuristics, which are known to find solutions close to the optimum due to the nature of their search space exploration. Our heuristic approach adds energy expenditure reduction in its algorithmic design. Through simulation and formal statistical analysis, the proposed scheme has been proved to produce efficient assignments in terms of the number of served users, resource allocation and energy savings, while being an order of magnitude faster than metaheuritsic-based approaches.This paper has been supported by the National Council of Research and Technology (CONACYT) through Grant FONCICYT/272278 and the ERANetLAC (Network of the European Union, Latin America, and the Caribbean Countries) Project ELAC2015/T100761. This paper is partially supported also by the ADVICE Project, TEC2015-71329 (MINECO/FEDER) and the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 777067 (NECOS Project)

Radio Resource Management in LTE-Advanced Systems with Carrier Aggregation

In order to meet the ever-increasing demand for wireless broadband services from fast growing mobile users, the Long Term Evolution -Advanced (LTE-A) standard has been proposed to effectively improve the system capacity and the spectral efficiency for the fourth-generation (4G) wireless mobile communications. Many advanced techniques are incorporated in LTE-A systems to jointly ameliorate system performance, among which Carrier Aggregation (CA) is considered as one of the most promising improvements that has profound significance even in the upcoming 5G era. Component carriers (CCs) from various portions of the spectrum are logically concatenated to form a much larger virtual band, resulting in remarkable boosted system capacity and user data throughput. However, the unique features of CA have posed many emerging challenges as well as span-new opportunities on the Radio Resource Management (RRM) in the LTE-A systems. First, although multi-CC transmission can bring higher throughput, it may incur more intensive interference for each CC and more power consumption for users. Thus the performance gain of CA under different conditions needs fully evaluating. Besides, as CA offers flexible CC selection and cross-CC load balancing and scheduling, enhanced RRM strategies should be designed to further optimize the overall resource utilization. In addition, CA enables the frequency reuse on a CC resolution, adding another dimension to inter-cell interference management in heterogeneous networks (HetNets). New interference management mechanisms should be designed to take the advantage of CA. Last but not least, CA empowers the LTE-A systems to aggregate the licensed spectrum with the unlicensed spectrum, thus offering a capacity surge. Yet how to balance the traffic between licensed and unlicensed spectrum and how to achieve a harmony coexistence with other unlicensed systems are still open issues. To this end, the dissertation emphasizes on the new functionalities introduced by CA to optimize the RRM performance in LTE-A systems. The main objectives are four-fold: 1) to fully evaluate the benefits of CA from different perspectives under different conditions via both theoretical analysis and simulations; 2) to design cross-layer CC selection, packet scheduling and power control strategies to optimize the target performance; 3) to analytically model the interference of HetNets with CA and propose dynamic interference mitigation strategies in a CA scenario; and 4) to investigate the impact of LTE transmissions on other unlicensed systems and develop enhanced RRM mechanisms for harmony coexistence. To achieve these objectives, we first analyze the benefits of CA via investigating the user accommodation capabilities of the system in the downlink admission control process. The LTE-A users with CA capabilities and the legacy LTE users are considered. Analytical models are developed to derive the maximum number of users that can be admitted into the system given the user QoS requirements and traffic features. The results show that with only a slightly higher spectrum utilization, the system can admit as much as twice LTE-A users than LTE users when the user traffic is bursty. Second, we study the RRM in the single-tier LTE-A system and propose a cross-layer dynamic CC selection and power control strategy for uplink CA. Specifically, the uplink power offset effects caused by multi-CC transmission are considered. An estimation method for user bandwidth allocation is developed and a combinatorial optimization problem is formulated to improve the user throughput via maximizing the user power utilization. Third, we explore the interference management problem in multi-tier HetNets considering the CC-resolution frequency reuse. An analytical model is devised to capture the randomness behaviors of the femtocells exploiting the stochastic geometry theory. The interaction between the base stations of different tiers are formulated into a two-level Stackelberg game, and a backward induction method is exploited to obtain the Nash equilibrium. Last, we focus on the mechanism design for licensed and unlicensed spectrum aggregation. An LTE MAC protocol on unlicensed spectrum is developed considering the coexistence with the Wi-Fi systems. The protocol captures the asynchronous nature of Wi-Fi transmissions in time-slotted LTE frame structure and strike a tunable tradeoff between LTE and Wi-Fi performance. Analytical analysis is also presented to reveal the essential relation among different parameters of the two systems. In summary, the dissertation aims at fully evaluating the benefits of CA in different scenarios and making full use of the benefits to develop efficient and effective RRM strategies for better LTE-Advanced system performance

Modeling the Techno-Economic Interactions of Infrastructure and Service Providers in 5G Networks With a Multi-Leader-Follower Game

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Delay and energy efficiency optimizations in smart grid neighbourhood area networks

Smart grids play a significant role in addressing climate change and growing energy demand. The role of smart grids includes reducing greenhouse gas emission reduction by providing alternative energy resources to the traditional grid. Smart grids exploit renewable energy resources into the power grid and provide effective two-way communications between smart grid domains for efficient grid control. The smart grid communication plays a pivotal role in coordinating energy generation, energy transmission, and energy distribution. Cellular technology with long term evolution (LTE)-based standards has been a preference for smart grid communication networks. However, integrating the cellular technology and the smart grid communication network puts forth a significant challenge for the LTE because LTE was initially invented for human centric broadband purpose. Delay and energy efficiency are two critical parameters in smart grid communication networks. Some data in smart grids are real-time delay-sensitive data which is crucial in ensuring stability of the grid. On the other hand, when abnormal events occur, most communication devices in smart grids are powered by local energy sources with limited power supply, therefore energy-efficient communications are required. This thesis studies energy-efficient and delay-optimization schemes in smart grid communication networks to make the grid more efficient and reliable. A joint power control and mode selection in device-to-device communications underlying cellular networks is proposed for energy management in the Future Renewable Electric Energy Delivery and Managements system. Moreover, a joint resource allocation and power control in heterogeneous cellular networks is proposed for phasor measurement units to achieve efficient grid control. Simulation results are presented to show the effectiveness of the proposed schemes

QoS-aware Adaptive Resource Management in OFDMA Networks

PhDOne important feature of the future communication network is that users in the network are required to experience a guaranteed high quality of service (QoS) due to the popularity of multimedia applications. This thesis studies QoS-aware radio resource management schemes in different OFDMA network scenarios. Motivated by the fact that in current 4G networks, the QoS provisioning is severely constrained by the availability of radio resources, especially the scarce spectrum as well as the unbalanced traffic distribution from cell to cell, a joint antenna and subcarrier management scheme is proposed to maximise user satisfaction with load balancing. Antenna pattern update mechanism is further investigated with moving users. Combining network densi fication with cloud computing technologies, cloud radio access network (C-RAN) has been proposed as the emerging 5G network architecture consisting of baseband unit (BBU) pool, remote radio heads (RRHs) and fronthaul links. With cloud based information sharing through the BBU pool, a joint resource block and power allocation scheme is proposed to maximise the number of satisfi ed users whose required QoS is achieved. In this scenario, users are served by high power nodes only. With spatial reuse of system bandwidth by network densi fication, users' QoS provisioning can be ensured but it introduces energy and operating effciency issue. Therefore two network energy optimisation schemes with QoS guarantee are further studied for C-RANs: an energy-effective network deployment scheme is designed for C-RAN based small cells; a joint RRH selection and user association scheme is investigated in heterogeneous C-RAN. Thorough theoretical analysis is conducted in the development of all proposed algorithms, and the effectiveness of all proposed algorithms is validated via comprehensive simulations.China Scholarship Counci

Game-Theoretic Frameworks for the Techno-Economic Aspects of Infrastructure Sharing in Current and Future Mobile Networks

RÉSUMÉ Le phénomène de partage d’infrastructure dans les réseaux mobiles a prévalu au cours des deux dernières décennies. Il a pris de l’ampleur en particulier pendant les deux dernières migrations technologiques, à savoir de la 2G à la 3G et de la 3G à la 4G et il sera encore plus crucial à très court terme avec l’avènement de la 5G. En permettant aux Opérateurs de Réseaux Mobiles (ORM) de faire face à la demande croissante des utilisateurs et à la baisse des revenus. Il n’est pas rare non plus que le partage d’infrastructure s’accompagne du partage du spectre, une ressource essentielle et de plus en plus rare pour les réseaux mobiles. Dans ce milieu, la communauté des chercheurs, parmis d’autres, a étudié les multiples aspects techniques du partage d’infrastructure parfois associés au partage du spectre. Entre autres, ces aspects techniques comprennent l’évaluation des performances en termes de métriques de réseau, de gestion de ressources et d’habilitateurs et d’architectures adaptées. Les aspects économiques ont également été abordés, mais généralement en se concentrant étroitement sur l’estimation des économies de coûts des dfférentes alternatives de partage d’infrastructure. Cependant, lorsqu’on considère le problème du partage d’infrastructure, et le cas échéant aussi du partage du spectre du point de vue d’un ORM, qui est une entité intéressée à maximiser le profit, il est important d’évaluer non seulement la réduction des coûts de cette infrastructure, et le cas échéant aussi le partage du spectre, mais aussi leur impact sur les performances du réseau et par conséquent sur les revenus de l’ORM. De ce point de vue, la viabilité du partage d’infrastructure ne doit pas être prise pour acquise ; afin d’étudier le problème stratégique d’un ORM concluant un accord de partage avec un ou plusieurs autres ORM, les aspects techniques et économiques doivent être pris en compte. Cette étude constitue le premier objectif de ce projet de recherche doctorale. Plus précisément, nous avons considéré plusieurs variantes résultant de deux cas où chaque variante a été abordée par un modèle mathématique approprié. Ces variantes répondent à un scénario 4G commun dans lequel il existe un ensemble de ORM avec des parts de marché données qui coexistent dans une zone géographique urbaine dense ; chaque ORM doit décider s’il faut déployer une couche de petites cellules dans la zone et, le cas échéant, s’il doit le faire lui-même ou en concluant un accord de partage en créant un réseau partagé avec certains, ou la totalité, des autres ORM, auquel cas une coalition est créée. Une caractéristique commune importante de ces variantes est le modèle de tarification de l’utilisateur défini comme une fonction linéaire du taux moyen perçu par l’utilisateur en fonction de la coalition dont fait partie l’ORM de l’utilisateur.----------ABSTRACT The phenomenon of infrastructure sharing in mobile networks has been prevalent over the last two decades. It has gathered momentum especially during the last two technology migrations, i.e., from 2G to 3G and from 3G to 4G and it will be even more crucial with the advent of 5G. The key rationale behind such phenomenon is cost reduction as a means for Mobile Network Operators (MNOs) to deal with an increasing user demand but declining revenues. It is also not unusual for infrastructure sharing to go hand in hand with sharing of spectrum, an essential and increasingly scarce resource for mobile networks. In this milieu, the research community (but not only) has addressed multiple technical aspects of infrastructure sharing sometimes combined with spectrum sharing. Among others, such technical aspects include performance evaluation in terms of network metrics, resource management and enablers and adapted architectures. Economic aspects have been addressed as well, but usually with a narrow focus on estimating the cost savings of the di˙erent infrastructure sharing alternatives. However, from the perspective of an MNO, which is a self-interested, profit-maximizing entity, it is important to assess not only the cost reduction that infrastructure sharing, and when applicable, also spectrum sharing bring about, but also their impact on the network performance and consequently on the MNO’s revenues. From this perspective, the viability of infrastructure sharing should not be taken for granted; in order to study the strategic problem of an MNO entering a sharing agreement with one or multiple other MNOs, both technical and economic aspects should be taken into account – such study has been the first objective of this doctoral research project. We have specifically considered multiple variants arising from two cases where each variant has been tackled by an appropriate mathematical model. These variants address a common 4G scenario in which there is a set of MNOs with given market shares that coexist in a given dense urban geographical area; each MNO has to decide whether to deploy a layer of small cells in the area and if so, whether to do that by itself or by entering a sharing agreement, i.e., building a shared network with a subset or all other MNOs (in which case a coalition is created). One key common feature of these variants is the user pricing model which is defined as a linear function of the average rate perceived by the user depending on the coalition joined by the user’s MNO; such pricing model allows us to capture the impact that infrastructure sharing, and, when applicable, also spectrum sharing have on the MNO’s revenues through a network performance metric. In turn, the two key outcomes of the models tackling these variants are the set of coalitions and the number of small cells they deploy

Ethics and taxation : a cross-national comparison of UK and Turkish firms

This paper investigates responses to tax related ethical issues facing busines