Wireless powered cooperation-assisted mobile edge computing

This paper studies a mobile edge computing (MEC) system in which two mobile devices are energized by the wireless power transfer (WPT) from an access point (AP) and they can offload part or all of their computation-intensive latency-critical tasks to the AP connected with an MEC server or an edge cloud. This harvest-then-offload protocol operates in an optimized time-division manner. To overcome the doubly near-far effect for the farther mobile device, cooperative communications in the form of relaying via the nearer mobile device is considered for offloading. Our aim is to minimize the AP's total transmit energy subject to the constraints of the computational tasks. We illustrate that the optimization is equivalent to a min-max problem, which can be optimally solved by a two-phase method. The first phase obtains the optimal offloading decisions by solving a sum-energy-saving maximization problem for given an energy transmit power. In the second phase, the optimal minimum energy transmit power is obtained by a bisection search method. Numerical results demonstrate that the optimized MEC system utilizing cooperation has significant performance improvement over systems without cooperation

Reflections, Resilience, and Recovery: A qualitative study of the COVID-19 impact on an international general population’s mental health and priorities for support

The impact of the coronavirus 2019 (COVID-19) pandemic on different countries and populations is well documented in quantitative studies, with some studies showing stable mental health symptoms and others showing fluctuating symptoms. However, the reasons behind why some symptoms are stable and others change are under-explored, which in turn makes identifying the types of support needed by participants themselves challenging. To address these gaps, this study thematically analysed 925 qualitative responses from five open-ended responses collected in the UCL-Penn Global COVID Study between 17 April to 31 July 2021 (wave 3). Three key themes comprised of 13 codes were reported by participants across countries and ages regarding the impact of COVID-19 on their health, both mental and physical, and livelihoods. These include: 1) Outlook on self/life, 2) Self-improvement, and 3) Loved ones (friends and family). In terms of support, while 2.91% did not require additional support, 91% wanted support beyond financial. Other unexpected new themes were also discussed regarding vulnerable populations suffering disproportionately. The pandemic has brought into sharp focus various changes in people’s mental health, physical health, and relationships. Greater policy considerations should be given to supporting citizens’ continued access to mental health when considering pandemic recovery

Robust Integrated Data and Energy Transfer Aided by Intelligent Reflecting Surfaces: Successive Target Migration Optimization Towards Energy Sustainability

Intelligent reflecting surfaces (IRSs) can actively adjust the wireless environment. However, accurate channel estimation on IRS-aided communication systems is difficult to obtain. Therefore, we study a robust beamforming design for an IRS-aided integrated data and energy transfer (IDET) with imperfect channel state information (CSI). Against the uncertain channel estimation error, we robustly design the transmit beamformers of the transmitter and the passive reflecting beamformer of the IRS to minimize the transmit power by satisfying both the wireless data transfer (WDT) and wireless energy transfer (WET) requirements for realising energy-sustainability in 6G. A successive target migration optimization (STMO) algorithm is proposed to obtain a robust design. The transmit covariance matrices are optimized by relaxing rank-one constraints, when a passive reflecting beamformer is given. Then, the target to minimize the transmit power is migrated to maximize the QoS requirements of energy users due to the fixed transmit power. A local optimal reflecting beamformer is obtained for improving the attainable WET performance, when the transmit covariance matrices are given. Finally, we prove that the rank-one transmit beamformers can always be found, which have the same WET and WDT performance as the transmit covariance matrices. The numerical results demonstrate the advantage of our design

Unary Coding Design for Simultaneous Wireless Information and Power Transfer with Practical M-QAM

Relying on the propagation of modulated radio-frequency (RF) signals, we can achieve simultaneous wireless information and power transfer (SWIPT) to support low-power communication devices. In this paper, we proposed a unary coding based SWIPT encoder by considering a practical M-QAM. Markov chains are exploited for characterising coherent binary information source and for modelling the generation process of modulated symbols. Therefore, both mutual information and the average energy harvesting performance at the SWIPT receiver are analysed in semi-closed-form. With the aid of the genetic algorithm, the sub-optimal codeword distribution of the coded information source is obtained by maximising the average energy harvesting performance, while satisfying the requirement of the mutual information. Simulation results demonstrate the advantage of the SWIPT encoder. Moreover, a higher-level unary code and a lower-order M-QAM results in higher WPT performance, when the maximum transmit power of the modulated symbol is fixed

Wideband Waveforming for Integrated Data and Energy Transfer: Creating Extra Gain Beyond Multiple Antennas and Multiple Carriers

When wideband signals propagate in a rich-scatterer environment, we obtain abundant resolvable multiple transmission paths to form a number of virtual antennas. Therefore, substantial spatial gain can be attained by carefully waveforming in all these resolvable transmission paths without additional antennas. This resultant spatial gain is then exploited for improving the performance of integrated-data-and-energy-transfer (IDET) from a single transmitter to multiple receivers. We aim to maximise the downlink fair-throughput and sum-throughput, while satisfying the energy harvesting requirements by jointly optimising the waveformers at the transmitter and the power splitters at the receivers. A low-complexity fractional-programming (FP) based alternating algorithm is proposed to solve these non-convex optimisation problems. The non-convex wireless energy transfer (WET) constraints are transformed to be convex with a modified quadratic transform (MQT) method. As a result, the stationary points for both the fair-throughput and the sum-throughput maximisation problems are obtained. The numerical results demonstrate the advantage of our proposed algorithm over a minimum-mean-square-error (MMSE) scheme, a zero-forcing (ZF) scheme and a time-reversal (TR) scheme. Simulation results show that the wireless data transfer (WDT) performance of our scheme outperforms the single-input-single-output orthogonal-frequency-division-multiple-access (SISO-OFDMA) when the output direct current (DC) power requirement is high. When we have a practical individual subcarrier power constraint, the WDT performance of our scheme outperforms multiple-input-single-output orthogonal-frequency-division-multiplex-access (MISO-OFDMA)

Comparison between a novel liquid switch and a GaAs MMIC switch for reconfiguring the operating frequency of a Vivaldi antenna

This article proposes a novel liquid switch to reconfigure the operating frequency of a frequency-independent antenna. A Vivaldi antenna using a low-cost GaAs MMIC RF switch is used as a landmark to compare the measured results. Two prototypes are measured in an anechoic chamber and the results have been compared. The antennas operate in two modes: low-band mode at 3 GHz with 11 dBi of gain and high-band mode operating at 4.5 GHz with a measured gain of 10.8 dBi. The reconfigurable Vivaldi antenna proposed here presents high isolation between operating bands, a minimum of 12 dB, while maintaining high gain and stable radiation pattern which is suitable for cognitive radio applications

Secrecy Energy Efficiency in Wireless Powered Heterogeneous Networks: A Distributed ADMM Approach

OAPA This paper investigates the physical layer security in heterogeneous networks (HetNets) supported by simultaneous wireless information and power transfer (SWIPT). We first consider a two-tier HetNet composed of a macrocell and several femtocells, where the macrocell base station (BS) serves multiple users in the presence of a malicious eavesdropper, while each femtocell BS serves a couple of Internet-of-things (IoT) users. With regard to the energy constraint of IoT users, SWIPT is performed at the femtocell BSs, and IoT users accomplish the reception of information and energy in a time-switching (TS) manner, where information secrecy is to be protected. To enhance the secrecy performance, we inject artificial noise (AN) into the transmit beam at both macrocell and femtocell BSs, and for the sake of achieving green communications, we formulate the problem of maximizing secrecy energy efficiency while considering the fairness in a cross-tier multi-cell coordinated beamforming (MCBF) design. To handle this resulting nonconvex max-min fractional program problem, we propose an iterative algorithm by applying successive convex approximation method. Then, we further develop a decentralized solution based on alternative direction multiplier method (ADMM), which reduces the overhead of information exchange among coordinated BSs and achieves good approximation performance. Finally, simulation results demonstrate the performance of the proposed AN-aided cross-tier MCBF design and verify the validity of distributed ADMM-based approach

Multiple UAV-Borne IRS-Aided Millimeter Wave Multicast Communications: A Joint Optimization Framework

In this letter, we design a resource allocation algorithm for communications in millimeter wave (mmWave) multicast systems adopting multiple unmanned aerial vehicle (UAV)-borne intelligent reflecting surfaces (IRSs). Considering the effect of blockages of building, we jointly optimize the placement of UAVs and the beamforming at the ground base station (BS) and the passive beamforming at the UAV-borne IRSs for maximizing the minimum rate of multiple user clusters. For handling the non-convex optimization problem, firstly, we employ the simulated annealing (SA)-based hybrid particle swarm optimization (HPSO) algorithm to design the deployment of UAVs for maximizing the average minimum achievable rate. Then, we propose a penalty-based block coordinated descent (BCD) algorithm to design the active and passive beamforming for maximizing the instantaneous minimum rate. Simulation results validate the efficiency of our proposed joint optimization framework

Involving parents in paired reading with preschoolers: Results from a randomized controlled trial

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Transmit/Passive Beamforming Design for Multi-IRS Assisted Cell-Free MIMO Networks

For beyond fifth-generation and sixth-generation communication, intelligent reflecting surface (IRS)/reconfigurable intelligent surface, and cell-free networks have been proposed as revolutionary technologies, which could significantly improve the connection quality and coverage to meet future communication demands for extremely massive connectivity and high reliability. In this article, a transmit/passive beamforming strategy for multi-IRS assisted cell-free multi-input–multi-output network is proposed to maximize the weighted sum-rate (WSR). Specifically, for passive beamforming of IRS, an elementwise block coordinate descent framework is applied to efficiently solve the unit-modulus constraints and reduce computation complexity greatly. Note that, every variable in our proposed algorithm can be updated with closed-form solutions and our algorithm can be applied with distributed implementation. Both analytical and simulation results demonstrate that, while guaranteeing superiority in WSR performance and information interaction cost, the proposed scheme outperforms the benchmark algorithms with closed-form solutions significantly in terms of complexity cost