Diagnosis of indirectly driven double shell targets with point-projection hard x-ray radiography

We present an application of short-pulse laser-generated hard x rays for the diagnosis of indirectly driven double shell targets. Coneinserted double shell targets were imploded through an indirect drive approach on the upgraded SG-II laser facility. Then, based on thepoint-projection hard x-ray radiography technique, time-resolved radiography of the double shell targets, including that of their near-peakcompression, were obtained. The backlighter source was created by the interactions of a high-intensity short pulsed laser with a metalmicrowire target. Images of the target near peak compression were obtained with an Au microwire. In addition, radiation hydrodynamicsimulations were performed, and the target evolution obtained agrees well with the experimental results. Using the radiographic images, arealdensities of the targets were evaluated.

Joint User Association and Caching Placement for Cache-Enabling UAV Networks

Cache-enabling unmanned aerial vehicles(UAVs)are considered for storing popular contents and providing downlink data offloading in cellular networks.In this context,we formulate a joint optimization problem of user association,caching placement,and backhaul bandwidth allocation for minimizing content acquisition delay with consideration of UAVs’energy constraint.We decompose the formulated problem into two subproblems:i)user association and caching placement and ii)backhaul bandwidth allocation.We first obtain the optimal bandwidth allocation with given user association and caching placement by the Lagrangian multiplier approach.After that,embedding the backhaul bandwidth allocation algorithm,we solve the user association and caching placement problem by a threedimensional(3D)matching method.Then we decompose it into two two-dimensional(2D)matching problems and develop low-complexity algorithms.The proposed scheme converges and exhibits a low computational complexity.Simulation results demonstrate that the proposed cache-enabling UAV framework outperforms the conventional UAV-assisted cellular networks in terms of content acquisition delay and the proposed scheme achieves significantly lower content acquisition delay compared with other two benchmark schemes.

Mobile Coded Caching in Small Cell Networks:Algorithm Design and Performance Analysis

In coded caching,users cache pieces of files under a specific arrangement so that the server can satisfy their requests simultaneously in the broadcast scenario via e Xclusive OR(XOR)operation and therefore reduce the amount of transmission data.However,when users’locations are changing,the uploading of caching information is frequent and extensive that the traffic increase outweighed the traffic reduction that the traditional coded caching achieved.In this paper,we propose mobile coded caching schemes to reduce network traffic in mobility scenarios,which achieve a lower cost on caching information uploading.In the cache placement phase,the proposed scheme first constructs caching patterns,and then assigns the caching patterns to users according to the graph coloring method and four color theorem in our centralized cache placement algorithm or randomly in our decentralized cache placement algorithm.Then users are divided into groups based on their caching patterns.As a benefit,when user movements occur,the types of caching pattern,rather than the whole caching information of which file pieces are cached,are uploaded.In the content delivery phase,XOR coded caching messages are reconstructed.Transmission data volume is derived to measure the performance of the proposed schemes.Numerical results show that the proposed schemes achieve great improvement in traffic offloading.

Joint Doppler Shift and Channel Estimation for UAV mmWave System with Massive ULA

A joint Doppler shift and channel estimation method for the millimeter-wave communication system of an unmanned aerial vehicle(UAV) equipped with a large-scale uniform linear antenna(ULA) array has been proposed. Since Doppler shift induces intercarrier interference, the parameters of the channel paths have been decomposed into the Doppler shift and the channel information. In order to obtain the Doppler shift, a new estimation algorithm based on a combination of discrete Fourier transform and phase rotation has been proposed, which can determine the appropriate number of antennas. In addition to estimating the channel information, a low-complexity joint Doppler shift and channel estimation method has been designed that can quickly obtain accurate estimates. Furthermore, the achievable sum rate, the theoretical bounds of the mean squared errors, and the Cram?er-Rao lower bounds of the estimation method have been derived. The analysis and simulation results prove that the performance of the proposed approach is close to the theoretical inference.

Deep Reinforcement Learning-Based Resource Allocation for UAV-Enabled Federated Edge Learning

The resource allocation of the federated learning(FL)for unmanned aerial vehicle(UAV)swarm systems are investigated.The UAV swarms based on FL realize the artificial intelligence(AI)applications by means of distributed training on the basis of ensuring the security of private data.However,the direct application of the FL in UAV swarms will incur high overhead.Therefore,in this article,we consider the resource allocation problem in FL for UAV swarms.To avoid the high communication overhead between UAVs and the central server,we proposed an FL framework for UAV swarms based on mobile edge computing(MEC)in which model aggregation is migrated to edge servers.In the proposed framework,the total cost of the FL is defined as the weighted sum of the total delay of UAV swarms to complete the FL and system energy consumption.In order to minimize the total cost of FL,we propose a resource allocation algorithm for joint optimization of computing resources and multi-UAV association based on deep reinforcement learning(DRL).The simulation result shows that:(1)compared with the benchmark algorithm,the proposed algorithm can effectively reduce the total cost of FL;(2)the proposed algorithm can realize the trade-off between task completion delay and system energy consumption through weight changes.

Power allocation scheme for multicell interference coordination in OFDMA systems

To coordinate inter-cell interference,a multicell adaptive power allocation scheme is proposed for downlink orthogonal frequency division multiple access(OFDMA)cellular systems.This scheme uses the difference of the signal to interference plus noise ratio(SINR)between the co-subchannels of adjacent cells to balance SINR for coordinating the transmit power in the co-subchannels.The scheme can improve edge user performance,reduce interference between the co-subchannels of adjacent cells and improve radio resource utility.Simulation results show that the scheme can balance system performance and ensure system throughput.