Power Minimization for the IRS-Aided SWIPT Secure Communication System with Imperfect Cascaded Channel

Intelligent reflecting surface(IRS)-assisted simultaneous wireless information and power transfer(SWIPT)is a promising technology for prolonging the lifetime of the users and improving system performance.However,it is challenging to obtain the perfect channel state information(CSI)at the base station(BS)due to the lack of radio frequency(RF)chains at the IRS,which becomes even harder when eavesdroppers(Eves)exist.In this paper,we study the power issues in the IRS-aided SWIPT system under the imperfect CSI of BS-IRS-Eves links.We aim to minimize the transmitting power at the BS by jointly designing transmit beamforming and reflective beamforming with subject to the rate outage probability constraints of the Eves,the energy harvesting constraints of the energy receivers(ERs),and the minimum rate constraints of the information receivers(IRs).We use Bernstein-type inequality to solve the rate outage probability constraints.Afterward,the formulated nonconvex problem can be efficiently tackled by employing alternating optimization(AO)combined with semidefinite relaxation(SDR)and penalty convex-concave procedure(CCP).Numerical results demonstrate the effectiveness of the proposed scheme.

Distributed Intelligent Reflecting Surfaces-Aided Device-to-Device Communications System

Intelligent reflecting surface(IRS)is a revolutionizing and promising technology to improve the high transmission rate of the wireless communication systems.Specifically,an IRS consists of a great amount of low-cost passive reflecting elements,which reflect the incident signals to the desired user by collaboratively using passive beamforming.This paper introduces IRSs into a device-to-device(D2D)underlying cellular system to enhance transmission rate performance of the D2D pairs.We formulate an optimization problem of maximizing the transmission rate of the D2D pairs while satisfying the minimum required rate of the cellular users.We address this problem by jointly optimizing the reuse indicator,received beamforming,power allocation,and phase shift matrices.Block coordinate descent(BCD)algorithm is adopted to decouple the original problem into four subproblems.Closed form solutions are obtained by solving the sub-problems of optimizing the received beamforming and power allocation.Then,Kuhn-Munkres(KM)algorithm and minimization-majorization(MM)algorithm are adopted to solve the sub-problems of optimizing the reuse indicator and phase shift matrices,respectively.Simulation results demonstrate that IRSs can effectively improve the transmission rate of the D2D pairs and our proposed distributed IRSs scheme outperforms the other benchmark schemes.

Reflecting Surface-Aided Device-to-Device Communications System

Intelligent reflecting surface(IRS)is a promising technology for its capability of reflecting the incident signal towards the desired user.IRS can improve the efficiency of wireless communication systems.This paper introduces IRS into a device-to-device(D2D)communications system to improve the throughput of the D2D network.We adopt the block coordinate descent al-gorithm and semidefinite relaxation technique to optimize the beamforming vector,power allocation and phase shift matrix.Simulation results demonstrate that IRS is able to enhance the throughput of the D2D communications system,and the proposed algorithm significantly outper-forms the other benchmark algorithms.

An Autonomous Overtaking Maneuver Based on Relative Position Information

Reliable and efficient overtaking maneuvers are important and challenging for autonomous vehicles.Higher precision position information is thus required,rather than that traditional global navigation satellite systems can provide.In this paper,we try to perform reliable autonomous overtaking controls of vehicles,mainly based on the“relative”position information,including the distance,angle and velocity between vehicles,which can be achieved by on-board radars.To reduce the complexity of maneuvers,a fuzzy inference system is applied to analyze the driving behavior of the preceding vehicle based on the obtained consecutive relative position information.An output of“safe”or“dangerous”will be sent to the decision part based on reinforcement learning frameworks.Various overtaking maneuvers including“conservative”and“aggressive”can be obtained accordingly.Furthermore,we propose another overtaking strategy that vehicles can share their maneuver information during overtaking process via wireless links.Numeric results validate our analysis,and can provide meaningful performance benchmarks for practical system implementations.