Mobile edge computing (MEC) is a promising paradigm to provide cloud-computing capabilities in close proximity to mobile devices in fifth-generation (5G) networks. In this paper, we study energy-efficient computation offloading (EECO) mechanisms for MEC in 5G heterogeneous networks. We formulate an optimization problem to minimize the energy consumption of the offloading system, where the energy cost of both task computing and file transmission are taken into consideration. Incorporating the multi-access characteristics of the 5G heterogeneous network, we then design an EECO scheme, which jointly optimizes offloading and radio resource allocation to obtain the minimal energy consumption under the latency constraints. Numerical results demonstrate energy efficiency improvement of our proposed EECO scheme.

Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks

This expanded and thoroughly revised edition of Thomas H. Lee's acclaimed guide to the design of gigahertz RF integrated circuits features a completely new chapter on the principles of wireless systems. The chapters on low-noise amplifiers, oscillators and phase noise have been significantly expanded as well. The chapter on architectures now contains several examples of complete chip designs that bring together all the various theoretical and practical elements involved in producing a prototype chip. First Edition Hb (1998): 0-521-63061-4 First Edition Pb (1998); 0-521-63922-0

The Design of CMOS Radio-Frequency Integrated Circuits: RF CIRCUITS THROUGH THE AGES

This paper considers a UAV-enabled mobile edge computing (MEC) system, where a UAV first powers the Internet of things device (IoTD) by utilizing Wireless Power Transfer (WPT) technology. Then each IoTD sends the collected data to the UAV for processing by using the energy harvested from the UAV. In order to improve the energy efficiency of the UAV, we propose a new time division multiple access (TDMA) based workflow model, which allows parallel transmissions and executions in the UAV-assisted system. We aim to minimize the total energy consumption of the UAV by jointly optimizing the IoTDs association, computing resources allocation, UAV hovering time, wireless powering duration and the services sequence of the IoTDs. The formulated problem is a mixed-integer non-convex problem, which is very difficult to solve in general. We transform and relax it into a convex problem and apply flow-shop scheduling techniques to address it. Furthermore, an alternative algorithm is developed to set the initial point closer to the optimal solution. Simulation results show that the total energy consumption of the UAV can be effectively reduced by the proposed scheme compared with the conventional systems.

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Joint Resources and Workflow Scheduling in UAV-Enabled Wirelessly-Powered MEC for IoT Systems

With the drastic increase of mobile devices, there are more and more mobile traffic and repeated requests for content. In 5G networks, small cell base stations (SBSs) caching and caching in wireless device-to-device network can effectively decrease the mobile traffic during peak hours. Currently, most of the related work is focused on how to cache content on SBSs and on mobile devices, and it is assumed that the user can download the entire requested content through the connected SBSs and mobile devices. However, few works have taken user mobility and the randomness of contact duration into consideration. How to improve the caching strategy by exploiting user mobility is still a challenging problem. Thus, in this paper, we first investigate the problem of how to conduct caching placement on SBS and on mobile devices leveraging user mobility, aiming to maximize the cache hit ratio. Specifically, the caching placement on SBSs and on mobile devices is formulated as an integer programming problem, and submodular optimization is adopted to solve the formulated problem. Then, we give the optimal transmission power of SBSs and mobile devices to deliver the caching content in order to reduce the energy cost. Simulation results prove that our caching strategy is more efficient than other existing caching strategies in terms of both cache hit ratio and energy efficiency.

Green and Mobility-Aware Caching in 5G Networks

Disclosed is an apparatus for inductively transferring power to movable consumer, it extends in the form of a conductor loop along a trajectory of a predetermined consumer, disposed on the consumer it is capable of power therefrom drawn by the secondary conductor, comprising at least one primary conductor. To produce a simple and inexpensive variable route layout, the device, galvanically (galvanically) isolated two conductor loops are provided, it is assigned to different sectors of the track Te, so that it can be power distributed to the consumer that is transmitted by inductive coupling conductor loop to at least one second conductor loop from the first conductor loop is arranged relative to each other . Sectors of the two conductor loops which is inductively coupled to form a transformer, which is preferably provided with a two-piece ferromagnetic core. Movable consumer is guided on a rail, one sector of the inductively coupled by conductor loop, the movable portion of the rail switch with only such binding occurs last position of the rail switch with, It is connected.

Apparatus for transmitting electrical energy inductively

This paper describes a new type of communication network called data and energy integrated communication networks (DEINs), which integrates the traditionally separate two processes, i.e., wireless information transfer (WIT) and wireless energy transfer (WET), fulfilling co-transmission of data and energy. In particular, the energy transmission using radio frequency is for the purpose of energy harvesting (EH) rather than information decoding. One driving force of the advent of DEINs is wireless big data, which comes from wireless sensors that produce a large amount of small piece of data. These sensors are typically powered by battery that drains sooner or later and will have to be taken out and then replaced or recharged. EH has emerged as a technology to wirelessly charge batteries in a contactless way. Recent research work has attempted to combine WET with WIT, typically under the label of simultaneous wireless information and power transfer. Such work in the literature largely focuses on the communication side of the whole wireless networks with particular emphasis on power allocation. The DEIN communication network proposed in this paper regards the convergence of WIT and WET as a full system that considers not only the physical layer but also the higher layers, such as media access control and information routing. After describing the DEIN concept and its high-level architecture/protocol stack, this paper presents two use cases focusing on the lower layer and the higher layer of a DEIN network, respectively. The lower layer use case is about a fair resource allocation algorithm, whereas the high-layer section introduces an efficient data forwarding scheme in combination with EH. The two case studies aim to give a better explanation of the DEIN concept. Some future research directions and challenges are also pointed out.

Data and Energy Integrated Communication Networks for Wireless Big Data

A typical data and energy integrated communication network (DEIN) conceives a conventional base station, which is capable of simultaneously transmitting the data and energy to user equipments (UEs) during the downlink (DL) transmissions by invoking the time-division-multiple-access (TDMA) protocol in the medium access control (MAC) layer. Several UEs operating in this DEIN are capable of harvesting the energy from the DL transmissions by adopting the power splitting (PS) technique and they are also capable of exploiting the harvested energy for powering their uplink (UL) data transmissions by invoking the TDMA protocol in the MAC layer. Both of the UL sum-throughput and the UL fair-throughput of the DEIN is maximized by deciding the duration of each time-slot during the DL/UL transmissions and by determining the optimal PS factor for each UE. Both of these optimization problems are finally solved by the classic method of Lagrange multipliers in close-form. An interesting observation shows that supporting low-throughput data services during the DL transmissions does not degrade the wireless energy transfer and hence does not reduce the throughput of the UL transmissions.

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Throughput Maximization and Fairness Assurance in Data and Energy Integrated Communication Networks

RF signals can be relied upon for transferring energy to those power-thirsty wireless devices. Thanks to the broadcast nature of wireless channels, dedicated RF signals for delivering information to specific devices can also be received by others for energy harvesting. Coordinating the conventional wireless information transfer and the wireless energy transfer (WET) requires a systematic design in all OSI layers, which yields data and energy integrated communication networks. Based on the classic carrier-sense-multiple-access with collision avoidance protocol, we originally propose a distributed multiple access protocol in the medium access control (MAC) layer for the indoor wireless-local-area-network (WLAN) powered by RF signal-based WET. The operation of our proposed protocol in the WET powered indoor WLAN is modeled by a multi-dimensional Markov chain, which is exploited for deriving the closed-form throughput of the WLAN studied. The simulation results demonstrate the accuracy of our theoretical analysis, which pave the way for the future optimization design in the MAC layer of WET powered indoor WLAN.

Modelling and Performance Analysis of Wireless LAN Enabled by RF Energy Transfer

With the rapid advancement of wireless network technologies and the rapid increase in the number of mobile devices, mobile users (MUs) have an increasing high demand to access the Internet with guaranteed quality-of-service (QoS). Data and energy integrated communication networks (DEINs) are emerging as a new type of wireless networks that have the potential to simultaneously transfer wireless energy and information via the same base station (BS). This means that a physical BS is virtualized into two parts: one is transferring energy and the other is transferring information. The former is called virtual energy base station (eBS) and the latter is named as data base station (dBS). One important issue in such setting is dynamic resource allocation. Here the resource concerned includes both power and time. In this paper, we propose a fair data-and-energy resource allocation algorithm for DEINs by jointly designing the downlink energy beamforming and a power-and-time allocation scheme, with the consideration of finite capacity batteries at MUs and power sensitivity of radio frequency (RF) to direct current (DC) conversion circuits. Simulation results demonstrate that our proposed algorithm outperforms the existing algorithms in terms of fairness, beamforming design, sensitivity, and average throughput.

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A Fair Resource Allocation Algorithm for Data and Energy Integrated Communication Networks

In order to address the energy shortage in communication networks, RF signals are exploited for transferring energy to miniature devices, which yields wireless powered communication networks (WPCNs) A full-duplex aided hybrid-base-station (H-BS) is conceived in a WPCN for simultaneously transferring energy during downlink transmissions and receiving data during uplink transmissions UEs may deplete all the energy received from the H-BS for supporting their own uplink transmissions In this full-duplex WPCN, A joint time allocation and UE scheduling algorithm is proposed for the sake of maximising the sum-uplink-throughput of multiple UEs by further considering UEs' actual data uploading requirements The numerical results demonstrate that the suboptimal solution is capable of achieving almost the same performance with its optimal counterparts, while our scheme outperforms other existing peers in terms of the sum-uplink-throughput

Qin Yu

Papers

Data and Energy Integrated Communication Networks for Wireless Big Data

Throughput Maximization and Fairness Assurance in Data and Energy Integrated Communication Networks

Modelling and Performance Analysis of Wireless LAN Enabled by RF Energy Transfer

A Fair Resource Allocation Algorithm for Data and Energy Integrated Communication Networks

A Joint Time Allocation and UE Scheduling Algorithm for Full-Duplex Wireless Powered Communication Networks