Energy efficient green wireless communication systems with imperfect CSI and data outage

Modern applications involve green communication technologies motivating well optimisation in the power–limited regime. In comparison to most of existing related work that assumes perfect channel state information (CSI) is always available, which is unfortunately not true in reality, this work focuses on an optimal energy efficient solution for resource allocation in multiuser orthogonal frequency division multiple access (OFDMA) networks in the presence of imperfect CSI and data outage conditions. Particularly, 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 optimisation objective to assign weights to each allocation link. Also, we interpret 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 towards maximising the energy efficiency subject to a minimum QoS requirement, channel interference and transmitting power constraints. The problem is transformed into an equivalent quasiconcave problem with respect to power, and concave problem with respect to the subcarrier indexing coefficients using the concept of subcarrier time–sharing. We optimise through a simple and versatile methodology, which uses standard–Lagrangian optimisation 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 existing approaches especially when perfect CSI is not available

Enabling radioprotection capabilities in next generation wireless communication systems:An ecological green approach

In future fifth-generation and beyond radio systems, access points equipped with massive antennas will be deployed to support the increased communication demands. As a result, radio environments will become more dense and users will be exposed to higher electromagnetic field (EMF) radiation from wireless devices than today. This paper proposes to take preemptive action toward protecting the public health from potential EMF-related ill effects by examining radiation-aware solutions for future green wireless communication systems from the radio resource scheduling perspective. Our efforts focus on correlating the transmit power levels of the wireless system with the operands used to express the EMF dosimetry metrics known as maximum permissible exposure and specific absorption rate. In addition, we formulate power minimization problems subject to the maximum permissible exposure and specific absorption rate safety standards, and the individual user quality-of-service demands to derive convex optimization-based solution of dynamic subcarrier allocation and adaptive power management. The simulation results confirm that our green solution reduces significantly the user exposure to radiation, while providing the required quality of service. We expect that our findings can kick off new research directions for controlling the public exposure to radiation from wireless devices in dense networks toward safer fifth-generation communication systems. © 2018 John Wiley & Sons, Ltd

Intrusion Response Systems for the 5G Networks and Beyond : A New Joint Security-vs-QoS Optimization Approach

Network connectivity exposes the network infrastructure and assets to vulnerabilities that attackers can exploit. Protecting network assets against attacks requires the application of security countermeasures. Nevertheless, employing countermeasures incurs costs, such as monetary costs, along with time and energy to prepare and deploy the countermeasures. Thus, an Intrusion Response System (IRS) shall consider security and QoS costs when dynamically selecting the countermeasures to address the detected attacks. This has motivated us to formulate a joint Security-vs-QoS optimization problem to select the best countermeasures in an IRS. The problem is then transformed into a matching game-theoretical model. Considering the monetary costs and attack coverage constraints, we first derive the theoretical upper bound for the problem and later propose stable matching-based solutions to address the trade-off. The performance of the proposed solution, considering different settings, is validated over a series of simulations

Convex optimization-based resource scheduling for multi-user wireless systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.For the thesis abstract, please see the main thesis file. The abstract is available in English and Greek.United Kingdom Engineering and Physical Sciences Research Council (EPSRC) and Motorola Ltd: Grant number EP/G070350/1 and 07000486

Energy efficient designs for communication systems:resolutions on inverse resource allocation principles

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

Maximizing energy efficiency in multiuser multicarrier broadband wireless systems:convex relaxation and global optimization techniques

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

A performance comparative study on the implementation methods for OFDMA cross-layer optimization

One key issue in cross-layer optimization techniques for next-generation multi-user orthogonal frequency division multiple access (OFDMA)-based broadband wireless network systems lies in the implementation methods of optimal resource scheduling. In the literature the optimal solutions are derived either through dynamic programming (referred to as a purely numerical approach) or via mathematical analysis (referred to as an analytical approach). When the latter approach is adopted, an additional iterative process is usually needed for the final optimal solution to be obtained. This paper presents a first in-depth comparative study on the implementation performance between the analytical and the numerical techniques. For this purpose, various popular iterative methods and numerical methods are investigated in our study. Several performance metrics (e.g., achieved overall data rate, absolute approximation error, and computational time) are utilized for comparison. Our simulation results demonstrate clearly that the analytical approaches indeed outperform the numerical ones. Furthermore, regarding different iterative methods, it is shown that the semi-implicit root (SIR) mechanism performs best in terms of the convergence rate, the root-finding accuracy, and the computational time. (C) 2011 Elsevier B.V. All rights reserved