NB-IoT via LEO satellites: An efficient resource allocation strategy for uplink data transmission

In this paper, we focus on the use of Low-Eart Orbit (LEO) satellites providing the Narrowband Internet of Things (NB-IoT) connectivity to the on-ground user equipment (UEs). Conventional resource allocation algorithms for the NBIoT systems are particularly designed for terrestrial infrastructures, where devices are under the coverage of a specific base station and the whole system varies very slowly in time. The existing methods in the literature cannot be applied over LEO satellite-based NB-IoT systems for several reasons. First, with the movement of the LEO satellite, the corresponding channel parameters for each user will quickly change over time. Delaying the scheduling of a certain user would result in a resource allocation based on outdated parameters. Second, the differential Doppler shift, which is a typical impairment in communications over LEO, directly depends on the relative distance among users. Scheduling at the same radio frame users that overcome a certain distance would violate the differential Doppler limit supported by the NB-IoT standard. Third, the propagation delay over a LEO satellite channel is around 4-16 times higher compared to a terrestrial system, imposing the need for message exchange minimization between the users and the base station. In this work, we propose a novel uplink resource allocation strategy that jointly incorporates the new design considerations previously mentioned together with the distinct channel conditions, satellite coverage times and data demands of various users on Earth. The novel methodology proposed in this paper can act as a framework for future works in the field.Comment: Tis work has been submitted to the IEEE IoT Journal for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Automated test sequence generation for finite state machines using genetic algorithms

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Testing software implementations, formally specified using finite state automata (FSA) has been of interest. Such systems include communication protocols and control sections of safety critical systems. There is extensive literature regarding how to formally validate an FSM based specification, but testing that an implementation conforms to the specification is still an open problem. Two aspects of FSA based testing, both NP-hard problems, are discussed in this thesis and then combined. These are the generation of state verification sequences (UIOs) and the generation of sequences of conditional transitions that are easy to trigger. In order to facilitate test sequence generation a novel representation of the transition conditions and a number of fitness function algorithms are defined. An empirical study of the effectiveness on real FSA based systems and example FSAs provides some interesting positive results. The use of genetic algorithms (GAs) makes these problems scalable for large FSAs. The experiments used a software tool that was developed in Java

Non-convex distributed power allocation games in cognitive radio networks

In this thesis, we explore interweave communication systems in cognitive radio networks where the overall objective is to maximize the sum-rate of each cognitive radio user by optimizing jointly both the detection operation based on sensing and the power allocation across channels, taking into account the influence of the sensing accuracy and the interference limitation to the primary users. The optimization problem is addressed in single and multiuser cognitive radio networks for both single-input single-output and multi-input multi-output channels. Firstly, we study the resource allocation optimization problem for single-input single-output single user cognitive radio networks, wherein the cognitive radio aims at maximizing its own sum-rate by jointly optimizing the sensing information and power allocation over all the channels. In this framework, we consider an opportunistic spectrum access model under interweave systems, where a cognitive radio user detects active primary user transmissions over all the channels, and decides to transmit if the sensing results indicate that the primary user is inactive at this channel. However, due to the sensing errors, the cognitive users might access the channel when it is still occupied by active primary users, which causes harmful interference to both cognitive radio users and primary users. This motivates the introduction of a novel interference constraint, denoted as rate-loss gap constraint, which is proposed to design the power allocation, ensuring that the performance degradation of the primary user is bounded. The resulting problem is non-convex, thus, an exhaustive optimization algorithm and an alternating direction optimization algorithm are proposed to solve the problem efficiently. Secondly, the resource allocation problem for a single-input single-output multiuser cognitive radio network under a sensing-based spectrum sharing scheme is analyzed as a strategic non-cooperative game, where each cognitive radio user is selfish and strives to use the available spectrum in order to maximize its own sum-rate by considering the effect of imperfect sensing information. The resulting game-theoretical formulations belong to the class of non-convex games. A distributed cooperative sensing scheme based on a consensus algorithm is considered in the proposed game, where all the cognitive radio users can share their sensing information locally. We start with the alternating direction optimization algorithm, and prove that the local Nash equilibrium is achieved by the alternating direction optimization algorithm. In the next step, we use a new relaxed equilibrium concept, namely, quasi-Nash equilibrium for the non-convex game. The analysis of the sufficient conditions for the existence of the quasi-Nash equilibrium for the proposed game is provided. Furthermore, an iterative primal-dual interior point algorithm that converges to a quasi-Nash equilibrium of the proposed game is also proposed. From the simulation results, the proposed algorithm is shown to yield a considerable performance improvement in terms of the sum-rate of each cognitive radio user, with respect to previous state-of-the-art algorithms. Finally, we investigate a multiple-input multiple-output multiuser cognitive radio network under the opportunistic spectrum access scheme. We focus on the throughput of each cognitive radio user under correct sensing information, and exclude the throughput due to the erroneous decision of the cognitive radio users to transmit over occupied channels. The optimization problem is analyzed as a strategic non-cooperative game, where the transmit covariance matrix, sensing time, and detection threshold are considered as multidimensional variables to be optimized jointly. We also use the new relaxed equilibrium concept quasi-Nash equilibrium and prove that the proposed game can achieve a quasi-Nash equilibrium under certain conditions, by making use of the variational inequality method. In particular, we prove theoretically the sufficient condition of the existence and the uniqueness of the quasi-Nash equilibrium for this game. Furthermore, a possible extension of this work considering equal sensing time is also discussed. Simulation results show that the iterative primal-dual interior point algorithm is an efficient solution that converges to the quasi-Nash equilibrium of the proposed game

Automated test sequence generation for finite state machines using genetic algorithms

Testing software implementations, formally specified using finite state automata (FSA) has been of interest. Such systems include communication protocols and control sections of safety critical systems. There is extensive literature regarding how to formally validate an FSM based specification, but testing that an implementation conforms to the specification is still an open problem. Two aspects of FSA based testing, both NP-hard problems, are discussed in this thesis and then combined. These are the generation of state verification sequences (UIOs) and the generation of sequences of conditional transitions that are easy to trigger. In order to facilitate test sequence generation a novel representation of the transition conditions and a number of fitness function algorithms are defined. An empirical study of the effectiveness on real FSA based systems and example FSAs provides some interesting positive results. The use of genetic algorithms (GAs) makes these problems scalable for large FSAs. The experiments used a software tool that was developed in Java.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Agency Self-Insulation Under Presidential Review

Agencies possess enormous regulatory discretion. This discretion allows executive branch agencies in particular to insulate their decisions from presidential review by raising the costs of such review. They can do so, for example, through variations in policymaking form, cost-benefit analysis quality, timing strategies, and institutional coalition-building. This Article seeks to help shift the literature\u27s focus on courtcentered agency behavior to consider instead the role of the President under current executive orders. Specifically, the Article marshals public-choice insights to offer an analytic framework for what it calls agency self-insulation under presidential review, illustrates the phenomenon, and assesses some normative implications. The framework generates several empirically testable hypotheses regarding how presidential transitions and policy shifts will influence agency behavior. It also challenges the doctrinal focus on removal restrictions and highlights instead a more functional understanding of agency independence. Finally, these dynamics suggest a role for courts to help enforce separation of powers principles within the executive branch and also, along with Congress, to facilitate political monitoring by encouraging information from sources external to the presidential review process

Legitimation of the economic community of West African states (ECOWAS): a normative and institutional inquiry

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonThis study is an attempt at determining the normative legitimacy of the Economic Community of West African States (ECOWAS). At its core, it scrutinizes the current mandate of the organization following the layering of economic integration objectives with human rights protection, sustenance of democracy, and the rule of law. The study discusses the elements of legitimacy across disciplines mainly, international law, international relations and political science. Legitimacy is eventually split along two divides, the normative and descriptive/sociological aspects. The study traces the normative content (shared/common values) underlying integration in Africa, concluding that integration has been born on new ideals such as human rights, democracy and the rule of law. Expectedly, Regional Economic Communities (RECs) as building blocks of the prospective African Economic Community (AEC) under the African Union (AU) regime are mandated to play a vital role in moving the continent forward upon these values. The inquiry is extended to the institutions of ECOWAS to determine their capacity to effectively implement the new mandate of the organization and operate supranationally. In the process, key legal and institutional shortcomings are discussed, particularly in relation to national institutions. It is argued that while human rights protection enhances the normative legitimacy of ECOWAS, it must not be pursued in isolation. Economic integration and protection of citizens’ rights are co-terminus and mutually reinforcing. Hence, community institutions must reflect this link if they are to be effective. The study concludes on the note that, while ECOWAS possesses layers of legitimacy, and have carried out legitimation steps, it cannot be considered a legitimate organization if Member States continue to be non-compliant with community objectives and if key legal questions remain unaddressed. It is submitted that ECOWAS is merely undergoing legitimation, whether it can eventually be considered a legitimate organization is dependent on addressing the identified challenges

Fundamentals

Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters