On the solutions of a class of difference equations

AbstractIn this note we investigate the solutions of a class of difference equations and prove that Conjectures 4.8.2, 4.8.3, 5.4.6 and 6.10.3 proposed by M. Kulenovic and G. Ladas in [M. Kulenovic, G. Ladas, Dynamics of Second Order Rational Difference Equations, with Open Problems and Conjectures, Chapman & Hall/CRC Press, 2002] are true

Realising energy-aware communication over fading channels under QoS constraints

There exists a trade-off between energy consumption and spectral efficiency in wireless communication systems under quality of service (QoS) constraints. This paper studies the use of effective capacity theory to characterise the maximum supported channel capacity over fading channels whilst considering both QoS constraints and energy consumption. Moreover, a generalised fading channel model, i.e., the hyper Fox's H fading model, is considered that includes many practical fading channel models as special cases, e.g., Rayleigh, Rician, Weibull and Nakagami-m fading channel models. The results are readily applicable to design energy-aware communication systems over fading channels with QoS constraints, e.g., wireless sensor networks and smart grid communication systems

Wireless Power Transfer: Survey and Roadmap

Wireless power transfer (WPT) technologies have been widely used in many areas, e.g., the charging of electric toothbrush, mobile phones, and electric vehicles. This paper introduces fundamental principles of three WPT technologies, i.e., inductive coupling-based WPT, magnetic resonant coupling-based WPT, and electromagnetic radiation-based WPT, together with discussions of their strengths and weaknesses. Main research themes are then presented, i.e., improving the transmission efficiency and distance, and designing multiple transmitters/receivers. The state-of-the-art techniques are reviewed and categorised. Several WPT applications are described. Open research challenges are then presented with a brief discussion of potential roadmap

Analyzing Impact of Data Uncertainty in Distributed Energy Resources using Bayesian Networks

With the high penetration of distributed energy resources (DERs), distribution networks have become more prone to uncertainties associated with renewable energy sources (RESs). If not handled judiciously, these uncertainties may lead to interruption in power supply and even failure of the entire power system in the long run. In this paper, a Bayesian Network (BN) approach is used to find the hidden inter-dependencies among the various weather parameters and how these affect renewable energy generation. A heuristic algorithm is then proposed to identify the root-cause of the uncertainty which increases the overall grid dependency and thereby, tackling its associated carbon emissions. To check the efficacy of the proposed approach, the effect of data uncertainty in the distribution network with DERs penetration in nine different regions of England is discussed. Furthermore, a case-study of a residential area of Newcastle upon Tyne is discussed in detail to back-trace the root-cause of the fault that occurred in one of the DERs

QoS-Balancing Algorithm for Optimal Relay Selection in Heterogeneous Vehicular Networks

Intelligent Transportation System (ITS) could facilitate communications among various road entities to improve the driver's safety and driving experience. These communications are called Vehicle-to-Everything (V2X) communications that can be supported by LTE-V2X protocols. Due to frequent changes of network topology in V2X, the source node (e.g., a vehicle) may have to choose a Device-to-Device(D2D) relay node to forward its packet to the destination node. In this paper, we propose a new method for choosing an optimal D2D relay node. The proposed method considers Quality of Service (QoS) requirements for selecting D2D relay nodes. It employs an Analytic Hierarchy Process (AHP) for making decisions. The decision criteria are linked with channel capacity, link stability and end-to-end delay. A number of simulations were performed considering various network scenarios to evaluate the performance of the proposed method. Simulation results show that the proposed method improves Packet Dropping Rate (PDR) by 30% and delivery ratio by 23% in comparison with the existing methods

Calculating the Maximum Penetration of Electric Vehicles in Distribution Networks with Renewable Energy and V2G

The uptake of electric vehicles and distributed energy generation is adding significant new demand to distribution networks, however it is unknown whether this can be accommodated by existing infrastructure. This paper first presents an Optimisation approach for determining the maximum penetration of electric vehicles that can be accommodated within a distribution network in conjunction with renewable energy and battery storage. An alternative approach, utilising Network Impact Tokens is then introduced, simplifying the original Optimisation approach while providing accurate results. The electric vehicle hosting capacity of the network is then analysed with increasing penetration of solar generation, battery storage and the use of V2G, showing that distributed generation can increase the the electric vehicle capacity by up to 38%

Adaptive Energy-Efficient Power Allocation in Green Interference Alignment Based Wireless Networks

Interference alignment (IA) is a promising technique for interference management in wireless networks. However, the sum rate may fall short of the theoretical maximum especially at low signal-to-noise ratio (SNR) levels since IA mainly concentrates on mitigating the interference, instead of improving the quality of desired signal. Moreover, most of the previous works focused on improving spectrum efficiency, but the energy efficiency aspect is largely ignored. In this paper, an adaptive energy-efficient IA algorithm is proposed through power allocation and transmission-mode adaptation for green IAbased wireless networks. The power allocation problem for IA is first analyzed, then we propose a power allocation scheme that optimizes the energy efficiency of IA-based wireless networks. When SNR is low, the transmitted power of some users may become zero. Thus the users with low transmitted power are turned into the sleep mode in our scheme to save energy. The transmitted power and transmission mode of the remaining active users are adapted again to further improve the energy efficiency of the network. To guarantee the interests of all the users, fairness among users is also considered in the proposed scheme. Simulation results are presented to show the effectiveness of the proposed algorithm in improving the energy efficiency of IAbased wireless networks