• Energy Research

The rapidly-increasing high data rate wireless networks and the fast-growing smartphone techniques are continually changing our daily behaviors and coloring our life. However, in order to fully experience the high rate broadband multimedia services, prolonging the battery life of user equipment is critical for the mobile users, especially for the smartphone users. In this work, the problem of offloading the cellular data via a collaborative mobile cloud in an energy efficient manner is investigated. The CMC is formed by a group of users interested in downloading the same content from the operator. Through Device-to-Device communications, the users inside CMC are able to cooperate during downloading procedure and offload data from Base Station for other CMC members. When considering wireless power transfer and MIMO wireless channel, an efficient algorithm is presented to address how to optimally schedule the data offloading and radio resources to obtain the energy efficiency as well as fairness among mobile users. Specifically, the proposed framework takes energy saving maximization, Quality of Service (QoS) requirement as well as user fairness into consideration. Performance evaluations demonstrate that significant energy saving gain can be achieved by the proposed data offloading scheme.

When integrating device-to-device (D2D) communications with densely deployed cellular networks, both energy efficiency (EE) and quality of service (QoS) will be severely degraded by strong intracell and intercell interference. To optimize EE while guaranteeing QoS provisioning, a three-stage energy-efficient resource allocation algorithm is proposed, which combines centralized interference mitigation and distributed power allocation algorithms by exploiting multi-cell cooperations, nonco-operative game, nonlinear fractional programming, and Lagrange dual decomposition. Simulation results have demonstrated that the proposed algorithm achieves a nearly zero infeasibility ratio, and improves EE performance significantly for both cellular and D2D user equipments (UEs) compared to the previous distributed scheme.

In this paper, a bidirectional wireless information and power transmission model with an energy accumulating relay is studied. To implement wireless information and power transmission simultaneously, a time-switching protocol is adopted. In addition, two energy harvesting (EH) protocols are proposed. In the bidirectional continuous-time EH (BI-CT) protocol, the whole transmission block is divided into two parts: EH and information transmission. In the bidirectional discrete-time EH (BI-DT) protocol, the EH time is either 0 or 1. The relay first harvests energy and then forwards information from the user node to the source node. Notably, the relay node stores energy during poor channel conditions, increasing the energy efficiency. Theoretical analyses on the performance of the two proposed protocols are given. It is found that the throughput efficiency depends on various system parameters, such as the transfer power at the relay, distance between the nodes, noise power, and SNR detection threshold. Furthermore, it is observed that BI-DT outperforms BI-CT when the noise power at the relay is high or the distance between the source and the relay is large.

In this work, we propose a distributed user association and resource allocation scheme for the wireless virtualized information-centric networks with hybrid energy supply, where the base station (BS) equipped with caching and energy harvesting capabilities to reduce the COPEX and OPEX cost. In particular, with the objective to obtain the utility maximization for the network operators, a joint user association, caching, spectrum and power problem is presented. To tackle the formulated mixed combinatorial and non-convex optimization problem with low complexity, the original problem is divided into two subproblems and we propose an alternating direction method of multipliers (ADMM)-based distributed algorithm to address them efficiently and effectively. Extensive simulation studies demonstrate the advantages of our presented system architecture and proposed schemes.

Fog computing system is able to facilitate computation-intensive applications and emerges as one of the promising technology for realizing the Internet of Things (IoT). By offloading the computational tasks to the fog node (FN) at the network edge, both the service latency and energy consumption can be improved, which is significant for industrial IoT applications. However, the dynamics of computational resource usages in the FN, the radio environment and the energy in the battery of IoT devices make the offloading mechanism design become challenging. Therefore, in this article, we propose a dynamic optimization scheme for the IoT fog computing system with multiple mobile devices (MDs), where the radio and computational resources, and offloading decisions, can be dynamically coordinated and allocated with the variation of radio resources and computation demands. Specifically, with the objective to minimize the system cost related to latency, energy consumption, and weights of MDs, we propose a joint computation offloading and radio resource allocation algorithm based on Lyapunov optimization. Through minimizing the derived upper bound of the Lyapunov drift-plus-penalty function, we divide the main problem into several subproblems at each time slot and address them accordingly. Through performance evaluation, the effectiveness of the proposed scheme can be verified.

In this study, an energy‐efficient optimisation scheme for a large‐scale multiple‐antenna system with wireless power transfer (WPT) is presented. In the considered system, the user is charged by a base station with a large number of antennas via downlink WPT and then utilises the received power to carry out uplink data transmission. Novel antenna selection, time allocation and power allocation schemes are presented to optimise the energy efficiency of the overall system. In addition, the authors also consider channel state information cannot be perfectly obtained when designing the resource allocation schemes. The non‐linear fractional programming‐based algorithm is utilised to address the formulated problem. Their proposed schemes are validated by extensive simulations and it shows superior performance over the existing schemes.

Energy harvesting relays are predicted to play a pivotal role in large scale networks. This paper evaluates the secrecy performance of a system that employs a two-way decode-and-forward relay assisting transmission between two nodes. The relay has RF energy harvesting capability and it can receive energy from the RF signal and the transmission of the system can be overheard by an eavesdropper. More specifically, we derive an exact expression for the interception probability when the main and wiretap links experience generalized κ-μ fading. The impacts of the power- splitting factor at the relay and the fading parameters on the secrecy performance of the considered system are also assessed. Numerical and simulation results are presented to verify the derived results.

The explosively growing demands for mobile traffic services bring both challenges and opportunities to wireless networks. Wireless network virtualization is proposed as the main evolution path toward the forthcoming fifth generation (5G) cellular networks. In this paper, we propose a software defined and virtualized (SDV) wireless network architecture for enabling multi-flow transmission with multiple infrastructure providers (InPs) and multiple mobile virtual network operators (MVNOs). In order to ensure the heterogeneity, we formulate the virtual resource allocation problem with diverse QoS requirements as a social welfare maximization problem with distance-related transaction cost. Due to hidden information of InPs and MVNOs for the auctioneer, we introduce a shadow price for ensuring desirable economic properties and total welfare for the system. Simulations are conducted with different system configurations to show the effectiveness and the energy efficiency performance of the proposed SDV wireless network framework and iterative double auction mechanism.