Reliable and flexible emergency communication is a key challenge for search and rescue in the event of disasters, especially for the case when base stations (BSs) are no longer functioning. Unmanned aerial vehicle (UAV) assisted network is emerging as a promising method to establish emergency networks. In this article, a unified framework of UAV-assisted emergency network is established in disasters. First, the trajectory and scheduling of UAV are jointly optimized to provide wireless service to ground devices with surviving BSs. Then, the transceiver design of UAV and establishment of multi-hop ground device-todevice (D2D) communication are studied to extend the wireless coverage of UAV. In addition, multi-hop UAV relaying is added to realize information exchange between the disaster areas and outside through optimizing the hovering positions of UAVs. Simulation results are presented to show the effectiveness of these three schemes. Finally, open research issues and challenges are discussed.

Index Terms-Energy efficiency (EE), non-orthogonal multiple access (NOMA), simultaneous wireless information and power transfer (SWIPT), time switching (TS).

(2018) Caching UAV assisted secure transmission in hyper-dense networks based on interference alignment. IEEE Transactions on Communication. Permanent WRAP URL:http://wrap.warwick.ac.uk/98753 Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way.Publisher's statement: "© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works." A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription. Abstract-Unmanned aerial vehicles (UAVs) can help smallcell base stations (SBSs) offload traffic via wireless backhaul to improve coverage and increase rate. However, the capacity of backhaul is limited. In this paper, UAV assisted secure transmission for scalable videos in hyper-dense networks via caching is studied. In the proposed scheme, UAVs can act as SBSs to provide videos to mobile users in some small cells. To reduce the pressure of wireless backhaul, UAVs and SBSs are both equipped with caches to store videos at off-peak time. To facilitate UAVs, a single antenna is equipped at each UAV and thus, only the precoding matrices of SBSs should be cooperatively designed to manage interference by exploiting the principle of interference alignment. On the other hand, the SBSs replaced by UAVs will be idle. Thus, in order to guarantee secure transmission, the idle SBSs can be further exploited to generate jamming signal to disrupt eavesdropping. The jamming signal is zero-forced at the legitimate users through the precoding of the idle SBSs, without affecting the legitimate transmission. The feasibility conditions of the proposed scheme are derived, and the secrecy performance is analyzed. Finally, simulation results are presented to verify the effectiveness of the proposed scheme.

Background and aimsThis study aims to examine the mediating effects of insomnia on the associations between problematic Internet use, including Internet addiction (IA) and online social networking addiction (OSNA), and depression among adolescents.MethodsA total of 1,015 secondary school students from Guangzhou in China participated in a cross-sectional survey. Levels of depression, insomnia, IA, and OSNA were assessed using the Center for Epidemiological Studies-Depression Scale, Pittsburgh Sleep Quality Index, Young’s Diagnostic Questionnaire, and Online Social Networking Addiction Scale, respectively. Logistic regression models were fit to test the associations between IA, OSNA, insomnia, and depression. The mediation effects of insomnia were tested using Baron and Kenny’s strategy.ResultsThe prevalence of depression at moderate level or above (CES-D ≥ 21), insomnia, IA, and OSNA were 23.5%, 37.2%, 8.1%, and 25.5%, respectively. IA and OSNA were significantly associated with depression (IA: AOR = 2.79, 95% CI: 1.71, 4.55; OSNA: AOR = 3.27, 95% CI: 2.33, 4.59) and insomnia (IA: AOR = 2.83, 95% CI: 1.72, 4.65; OSNA: AOR = 2.19, 95% CI: 1.61, 2.96), after adjusting for significant background factors. Furthermore, insomnia partially mediated 60.6% of the effect of IA on depression (Sobel Z = 3.562, p < .002) and 44.8% of the effect of OSNA on depression (Sobel Z = 3.919, p < .001), respectively.DiscussionThe high prevalence of IA and OSNA may be associated with increased risk of developing depression among adolescents, both through direct and indirect effects (via insomnia). Findings from this study indicated that it may be effective to develop and implement interventions that jointly consider the problematic Internet use, insomnia, and depression.

Simultaneous wireless information and power transfer (SWIPT) and multi-carrier non-orthogonal multiple access (MC-NOMA) are promising technologies for future fifth generation and beyond wireless networks due to their potential capabilities in energy-efficient and spectrum-efficient system designs, respectively. In this paper, the joint downlink resource allocation problem for a SWIPT-enabled MC-NOMA system with time switching-based receivers is investigated, where pattern division multiple access (PDMA) technique is employed. We focus on minimizing the total transmit power of the system while satisfying the quality-of-service requirements of each user in terms of data rate and harvested power. The corresponding optimization problem is a non-convex and a mixed integer programming problem which is difficult to solve. Different from the conventional iterative searching-based algorithms, we propose an efficient deep learning-based approach to determine an approximated optimal solution. Specifically, we employ a typical class of deep learning model, namely, deep belief network (DBN), where the detailed procedure of the developed approach consists of three parts, i.e., data preparation, training, and running. The simulation results demonstrate that the proposed DBN-based approach can achieve similar performance of power consumption to the exhaustive search method. Furthermore, the results also confirm that MC-NOMA with PDMA outperforms MC-NOMA with sparse code multiple access, single-carrier non-orthogonal multiple access, and orthogonal frequency division multiple access in terms of power consumption in SWIPT-enabled systems. INDEX TERMS Non-orthogonal multiple access (NOMA), simultaneous wireless information and power transfer (SWIPT), machine learning.

No abstract

In this paper, we consider an energy-constrained unmanned aerial vehicle (UAV)-enabled mobile relay assisted secure communication system in the presence of a legitimate source-destination pair and multiple eavesdroppers with imperfect locations. The energy-constrained UAV employs the power splitting (PS) scheme to simultaneously receive information and harvest energy from the source, and then exploits the time switching (TS) protocol to perform information relaying. Furthermore, we consider a full-duplex destination node which can simultaneously receive confidential signals from the UAV and cooperatively transmit artificial noise (AN) signals to confuse malicious eavesdroppers. To further enhance the reliability and security of this system, we formulate a worst case secrecy rate maximization problem, which jointly optimizes the position of the UAV, the AN transmit power, as well as the PS and TS ratios. The formulated problem is non-convex and generally intractable. In order to circumvent the non-convexity, we decouple the original optimization problem into three subproblems; this facilitates the design of a suboptimal iterative algorithm. In each iteration, we propose a multi-dimensional search and numerical method to handle the subproblem. Numerical simulation results are pro

No abstract