Modern applications involve green communication technologies motivating well optimization in the power-limited regime. In comparison with most of the existing related work that assumes perfect ...channel state information (CSI) is always available, which is unfortunately not true in reality, this paper focuses on an optimal energy-efficient solution for resource allocation in multiuser orthogonal frequency division multiple access networks in the presence of imperfect CSI and data outage conditions. In particular, in view that wireless channel conditions, circuit power consumptions, and users' quality-of-service (QoS) requirements are heterogeneous in nature, we enable attractive tuning options by letting energy efficiency optimization objective to assign weights to each allocation link. In addition, we interpret the effects of data outage due to imperfect CSI using a profound insight on the monotonicity of noncentral chi-squared inverse distribution function, which reveals that our design complies with expected physics and mechanics of conventional energy efficiency approach and that it can be successfully degenerated to the energy-efficiency model with perfect CSI. Furthermore, we formulate a mixed combinatorial problem toward maximizing the energy efficiency subject to a minimum QoS requirement, channel interference, and transmitting power constraints. The problem is transformed into an equivalent quasi-concave problem with respect to power, and concave problem with respect to the subcarrier indexing coefficients using the concept of subcarrier time sharing. We optimize through a simple and versatile methodology, which uses standard-Lagrangian optimization technique to obtain joint dynamic subcarrier and adaptive power allocations by means of final formulas. We also examine key properties of the introduced optimal solution in terms of implementation convergence and complexity, level of optimality, and impact of imperfect CSI coefficients and circuit power on network performance. The simulation results demonstrate the effectiveness of our allocation scheme for achieving higher energy efficiency performance with the guaranteed QoS support and lower complexity than the existing approaches especially when perfect CSI is not available.
This paper proposes a new Nash bargaining solution (NBS) based cooperative game-theoretic scheduling framework for joint channel and power allocation in orthogonal frequency division multiple access ...cognitive radio (CR) systems. Our objectives are to maximize the overall throughput of the CR system with the protection of primary users' transmission, while guaranteeing each CR user's minimum rate requirement and the proportional fairness and efficient power distribution among CR users. Using time-sharing variable transformation, we introduce a novel method that involves Lambert-W function properties and obtain closed-form analytical solutions. A low-complexity algorithm is also developed which does not require iterative processes as usual to search the optimal solution numerically. Simulation results demonstrate that our optimal policies outperform the existing maximal rate, fixed assignment and max-min fairness, while achieving the 99.985% in average of the optimal capacity.
A key challenge toward green communications is how to maximize energy efficiency by optimally allocating wireless resources in large-scale multiuser multicarrier orthogonal frequency-division ...multiple-access (OFDMA) systems. The quality-of-service (QoS)-constrained energy efficiency maximization problem is generally hard to solve due to the inverse transposition of the optimization operands in the optimization objective. We apply convex relaxation to make the problem quasiconcave with respect to power and concave with respect to the subcarrier indexing coefficients. The Karush-Kuhn-Tucker (KKT) optimality conditions lead to transcendental functions, where existing solutions are only numerically tractable. Different from the existing approaches, we apply the Maclaurin series expansion technique to transform the complex transcendental functions into simple polynomial expressions that allow us to obtain the global optimum in fast polynomial time, with the tractable upper bound of truncation error. With the new solution method, we propose a joint optimal allocation policy for both adaptive power and dynamic subcarrier allocations. We gain insight on the optimality, feasibility, and computational complexity of the joint optimal solution to show that the proposed scheme is theoretically and practically sound with fast convergence toward near-optimal solutions with an explicitly tractable truncation error. The simulation results confirm that the proposed scheme achieves a much higher energy efficiency performance with the guaranteed QoS and much lower complexity than existing approaches in the literature.
The development of modellings and analytical tools to structurise and study the allocation of resources through noble user competitions become essential, especially considering the increased degree ...of heterogeneity in application and service demands that will be cornerstone in future communication systems. Stochastic asymmetric Blotto games appear promising to modelling such problems, and devising their Nash equilibrium (NE) strategies by anticipating the potential outcomes of user competitions. In this regard, this paper approaches the generic energy efficiency problem with a new stochastic asymmetric Blotto game paradigm to enable the derivation of joint optimal bandwidth and transmit power allocations by setting multiple users to compete in multiple auction-like contests for their individual resource demands. The proposed modelling innovates by abstracting the notion of fairness from centrally-imposed to distributed-competitive, where each user's pay-off probability is expressed as quantitative bidding metric, so as, all users' actions can be interdependent, i.e., each user attains its utility given the allocations of other users, which eliminates the chance of low-valued carriers not being claimed by any user, and, in principle, enables the full utilisation of wireless resources. We also contribute by resolving the allocation problem with low complexity using new mathematical techniques based on Charnes-Cooper transformation, which eliminate the additional coefficients and multipliers that typically appear during optimisation analysis, and derive the joint optimal strategy as a set of linear single-variable functions for each user. We prove that our strategy converges towards a unique, monotonous and scalable NE, and examine its optimality, positivity and feasibility properties in detail. Simulation comparisons with relevant studies confirm the superiority of our approach in terms of higher energy efficiency performance, fairness index and quality-of-service provision.
The 5G communication network will underpin a vast number of new and emerging services, paving the way for unprecedented performance and capabilities in mobile networks. In this setting, the Internet ...of Things (IoT) will proliferate, and IoT devices will be included in many 5G application contexts, including the Smart Grid. Even though 5G technology has been designed by taking security into account, design provisions may be undermined by software-rooted vulnerabilities in IoT devices that allow threat actors to compromise the devices, demote confidentiality, integrity and availability, and even pose risks for the operation of the power grid critical infrastructures. In this paper, we assess the current state of the vulnerabilities in IoT software utilized in smart grid applications from a source code point of view. To that end, we identified and analyzed open-source software that is used in the power grid and the IoT domain that varies in characteristics and functionality, ranging from operating systems to communication protocols, allowing us to obtain a more complete view of the vulnerability landscape. The results of this study can be used in the domain of software development, to enhance the security of produced software, as well as in the domain of automated software testing, targeting improvements to vulnerability detection mechanisms, especially with a focus on the reduction of false positives.
The advent of deep-learning technology promises major leaps forward in addressing the ever-enduring problems of wireless resource control and optimization, and improving key network performances, ...such as energy efficiency, spectral efficiency, transmission latency, etc. Therefore, a common understanding for quantum deep-learning algorithms is that they exploit advantages of quantum hardware, enabling massive optimization speed ups, which cannot be achieved by using classical computer hardware. In this respect, this paper investigates the possibility of resolving the energy efficiency problem in wireless communications by developing a quantum neural network (QNN) algorithm of deep-learning that can be tested on a classical computer setting by using any popular numerical simulation tool, such as Python. The computed results show that our QNN algorithm can be indeed trainable and that it can lead to solution convergence during the training phase. We also show that the proposed QNN algorithm exhibits slightly faster convergence speed than its classical ANN counterpart, which was considered in our previous work. Finally, we conclude that our solution can accurately resolve the energy efficiency problem and that it can be extended to optimize other communications problems, such as the global optimal power control problem, with promising trainability and generalization ability.
Energy efficient designs of communication systems are receiving great attention in both academia and industry. This letter investigates the energy efficient resource allocation schemes with Quality ...of Service (QoS) guarantee towards green wireless communication systems. We utilise the convex optimisation theory to obtain the optimal joint subcarrier and power allocation strategy. A new solution methodology is proposed to achieve the resolutions of transcendental equations. The simulation results demonstrate that our scheme outperforms other related approaches in terms of the energy efficiency performance, QoS guarantee and implementation complexity.
The definition of multiple slicing types in 5G has created a wide field for service innovation in communications. However, the advantages that network slicing has to offer remain to be fully ...exploited by today’s applications and users. An important area that can potentially benefit from 5G slicing is emergency communications for First Responders. The latter consists of heterogeneous teams, imposing different requirements on the connectivity network. In this paper, the RESPOND-A platform is presented, which provides First Responders with network-enabled tools on top of 5G on-scene planning, with enhanced service slicing capabilities tailored to emergency communications. Furthermore, a mapping of emergency services and communications to specific slice types is proposed to identify the current challenges in the field. Additionally, the proposed tentative mechanism is evaluated in terms of energy efficiency. Finally, the approach is summarized by discussing future steps in the convergence of 5G network slicing in various areas of emergency vertical applications.
This study delves into the potential of 5G and blockchain technologies in smart agriculture, specifically targeting remote farming sectors. A conceptual architecture is proposed, aiming to leverage ...these cutting-edge technologies while ensuring energy efficiency and sustainable development within the agriculture industry. We provide an in-depth analysis of 5G applications and explore alternative communication channels that could empower remote communities, introducing them to state-of-the-art technological solutions. A unique aspect of our research is the detailed presentation of a parametric insurance business case, designed to align with the proposed architecture, thereby illustrating the practicality of our approach. Moreover, we propose an innovative solution to the challenge of providing internet connectivity in rural areas using Unmanned Aerial Vehicles (UAVs). Current limitations due to the weight of onboard equipment, which includes an access network and a backhaul link for internet provision, are addressed by introducing a lightweight 5G system onboard the UAV. This system serves multiple user equipment on the ground, with one acting as a connection gateway to the internet. This unique approach not only streamlines the process of providing rural internet connectivity but also opens up new markets for service providers and businesses related to lightweight 5G systems and UAV technology. Our work presents an avant-garde solution to technical challenges and offers significant business opportunities in the rapidly evolving telecommunications sector and beyond.
Energy efficiency is a huge opportunity for both the developed and the developing world, and ICT will be the key enabler towards realising this challenge, in a huge variety of ways across the full ...range of industries. In the telecommunications space in particular, power consumption and the resulting energy-related pollution are becoming major operational and economical concerns. The exponential increases in network traffic and the number of connected devices both make energy efficiency an increasingly important concern for the mobile networks of the (near) future. More specifically, as 5G is being deployed at a time when energy efficiency appears as a significant matter for the network ability to take into account and to serve societal and environmental issues, this can play a major role in helping industries to achieve sustainability goals. Within this scope, energy efficiency has recently gained its own role as a performance measure and design constraint for 5G communication networks and this has identified new challenges for the future. In particular, the inclusion of AI/ML techniques will further enhance 5G’s capabilities to achieve lower power consumption and, most importantly, dynamic adaption of the network elements to any sort of energy requirements, to ensure effective functioning.
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