Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.

Intelligent Reflecting Surface-Aided Secure and Covert Communications

This work employs intelligent reflecting surface(IRS)to enhance secure and covert communication performance.We formulate an optimization problem to jointly design both the reflection beamformer at IRS and transmit power at transmitter Alice in order to optimize the achievable secrecy rate at Bob subject to a covertness constraint.We first develop a Dinkelbach-based algorithm to achieve an upper bound performance and a high-quality solution.For reducing the overhead and computational complexity of the Dinkelbach-based scheme,we further conceive a low-complexity algorithm in which analytical expression for the IRS reflection beamforming is derived at each iteration.Examination result shows that the devised low-complexity algorithm is able to achieve similar secrecy rate performance as the Dinkelbach-based algorithm.Our examination also shows that introducing an IRS into the considered system can significantly improve the secure and covert communication performance relative to the scheme without IRS.

EXPONENTIAL CONVERGENCE FOR NONLINEAR SPDES WITH DOUBLE REFLECTING WALLS

The present article is devoted to nonlinear stochastic partial differential equations with double reflecting walls driven by possibly degenerate,multiplicative noise.We prove that the corresponding Markov semigroup possesses an exponentially attracting invariant measure through asymptotic coupling,in which Foias-Prodi estimation and the truncation technique are crucial for the realization of the Girsanov transform.

Intelligent Reflecting Surface Assisted Transmission Optimization Strategies in Wireless Networks

Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low latency.Although the intelligent reflecting surface(IRS)can be adopted to create effective virtual links to address the mmWave blockage problem,the conventional solutions only adopt IRS in the downlink from the Base Station(BS)to the users to enhance the received signal strength.In practice,the reflection of IRS is also applicable to the uplink to improve the spectral efficiency.It is a challenging to jointly optimize IRS beamforming and system resource allocation for wireless energy acquisition and information transmission.In this paper,we first design a Low-Energy Adaptive Clustering Hierarchy(LEACH)clustering protocol for clustering and data collection.Then,the problem of maximizing the minimum system spectral efficiency is constructed by jointly optimizing the transmit power of sensor devices,the uplink and downlink transmission times,the active beamforming at the BS,and the IRS dynamic beamforming.To solve this non-convex optimization problem,we propose an alternating optimization(AO)-based joint solution algorithm.Simulation results show that the use of IRS dynamic beamforming can significantly improve the spectral efficiency of the system,and ensure the reliability of equipment communication and the sustainability of energy supply under NLOS link.

Intelligent reflecting surface for sum rate enhancement in MIMO systems

The research for the Intelligent Reflecting Surface(IRS)which has the advantages of cost and energy efficiency has been studied.Channel capacity can be effectively increased by appropriately setting the phase value of IRS elements according to the channel conditions.However,the problem of obtaining an appropriate phase value of IRs is difficult to solve due to the non-convex problem.This paper proposes an iterative algorithm for the alternating optimal solution in the Single User Multiple-Input-Multiple-Output(SU-MIMO)systems.The proposed iterative algorithm finds an alternating optimal solution that is the phase value of IRS one by one.The results show that the proposed method has better performance than that of the randomized IRS systems.The number of iterations for maximizing the performance of the proposed algorithm depends on the channel state between the IRS and the receiver.

Joint Active and Passive Beamforming Design in Intelligent Reflecting Surface(IRS)-Assisted Covert Communications:A Multi-Agent DRL Approach

Intelligent Reflecting Surface(IRS),with the potential capability to reconstruct the electromagnetic propagation environment,evolves a new IRSassisted covert communications paradigm to eliminate the negligible detection of malicious eavesdroppers by coherently beaming the scattered signals and suppressing the signals leakage.However,when multiple IRSs are involved,accurate channel estimation is still a challenge due to the extra hardware complexity and communication overhead.Besides the crossinterference caused by massive reflecting paths,it is hard to obtain the close-formed solution for the optimization of covert communications.On this basis,the paper improves a heterogeneous multi-agent deep deterministic policy gradient(MADDPG)approach for the joint active and passive beamforming(Joint A&P BF)optimization without the channel estimation,where the base station(BS)and multiple IRSs are taken as different types of agents and learn to enhance the covert spectrum efficiency(CSE)cooperatively.Thanks to the‘centralized training and distributed execution’feature of MADDPG,each agent can execute the active or passive beamforming independently based on its partial observation without referring to others.Numeral results demonstrate that the proposed deep reinforcement learning(DRL)approach could not only obtain a preferable CSE of legitimate users and a low detection of probability(LPD)of warden,but also alleviate the communication overhead and simplify the IRSs deployment.

On the achievable rate for double intelligent reflecting surface enhanced cognitive radio network

Intelligent reflecting surface(IRS)can efficiently improve the performance of wireless commu-nication networks by intelligently reconfiguring the wireless propagation environment.Recently,IRS has been integrated with cognitive radio(CR)network in order to improve the resource utilization of communication systems.It is a challenging issue for IRS-assisted CR networks to improve the rate performance of the secondary user(SU)through the rational design of IRS passive beamforming while limiting the interference to the primary network.This paper investigates the optimization of downlink rate of SU in a double-IRS-assisted CR network.The achievable rate is maximized by jointly optimizing the active beamforming vector at the secondary transmitter(SU-TX)and the coop-eratively passive reflective beamforming at the two distributed IRSs.To solve the proposed non-con-vex joint optimization problem,the alternating optimization(AO)and semidefinite relaxation(SDR)techniques are then adopted to iteratively optimize the two variables.Numerical results vali-date that the proposed double-IRS assisted system can significantly improve the performance of the CR network compared with the existing single-IRS assisted CR system.

机器学习在智能反射面辅助的通信系统中的应用综述

智能反射面(intelligent reflecting surfaces,IRS)可以通过大量低成本的无源反射元件巧妙地调整信号反射,从而动态改变无线信道,提高通信性能,目前已成为无线通信研究的焦点。然而,由于IRS的加入,整个通信系统变得更加复杂,系统的动态性也更高,使通信系统面临着许多新的挑战。机器学习(machine learning,ML)具有很强的数据处理与自适应能力,能够不断适应变化的环境和需求,可以很好地应对通信系统中的许多挑战。因此,使用ML解决IRS辅助的通信系统中的问题,已经成为当前研究的重点。基于此,对ML在IRS系统中的应用进行了系统性的概述,从IRS辅助的通信系统中存在的问题入手,分别从反射因子的设计与优化、信道处理与建模、资源分配和管理、安全性增强4个方面对ML在IRS系统中的应用进行阐述和分析,并讨论了将ML应用在IRS系统中的优势及未来的发展趋势与挑战。

Joint Beamforming for Intelligent Reflecting Surface Aided Wireless Communication Using Statistical CSI

A joint beamforming algorithm is proposed for intelligent reflecting surface(IRS) aided wireless multiple-input multiple-output(MIMO) communication using statistical channel state information(CSI). The beamforming is done by alternatively optimizing the IRS reflecting coefficients and the covariance matrix of the transmit symbol vector, such that the ergodic rate of the system is maximized. The algorithm utilizes only the second order momentum of the random channel matrices and does assume any specific channel distribution, leading to a general framework for ergodic rate evaluation. A practical channel correlation model is configured to validate the performance gain. It is found that the rate can be enlarged by the joint optimization algorithm, however, the gain over that of randomly deployed reflecting coefficients depends highly on the relative correlation distance of the IRS elements and the spatial position of the IRS. In particular, the results suggest that IRS should be placed in the vicinity of either the transmitter or the receiver. Placing IRS far away from those positions is non-beneficial.

The seismic reflecting characteristics of gas hydrate bearing strata and its possible distribution in the South China Sea

The research on gas hydrate is one of the topics of general interest in the field of energy resource and environment. The South China Sea has favorable conditions for the occurrence and formation of gas hydrate. The presence of gas hydrate changes acoustic properties of the sedimentary strata and results in the occurrence of bottom simulating reflectors, which makes the multi-channel seismic investigation an important method to identify gas hydrates. First, the paper, based on results of seismic reflection imaging, analyzes the qualitative seismic reflection characteristics of sedimentary strata containing gas hydrate. Some key seismic imaging techniques are also discussed. Next, a pseudo-well is constructed to perform an impedance inversion to get the quantitative velocity structure of the strata since there is no well in the study area. Finally, the velocity field from geophysical inversion is integrated with the geochemical and geophysical data acquired on the Ocean Drilling Program 184 cruise. All information confirms the presence of gas hydrate and shows its spatial distribution.

Towards Intelligent Reflecting Surface Empowered 6G Terahertz Communications: A Survey

Terahertz(THz)communications have been widely envisioned as a promising enabler to provide adequate bandwidth and achieve ultra-high data rates for sixth generation(6G)wireless networks.In order to mitigate blockage vulnerability caused by serious propagation attenuation and poor diffraction of THz waves,an intelligent reflecting surface(IRS),which manipulates the propagation of incident electromagnetic waves in a programmable manner by adjusting the phase shifts of passive reflecting elements,is proposed to create smart radio environments,improve spectrum efficiency and enhance coverage capability.Firstly,some prospective application scenarios driven by the IRS empowered THz communications are introduced,including wireless mobile communications,secure communications,unmanned aerial vehicle(UAV)scenario,mobile edge computing(MEC)scenario and THz localization scenario.Then,we discuss the enabling technologies employed by the IRS empowered THz system,involving hardware design,channel estimation,capacity optimization,beam control,resource allocation and robustness design.Moreover,the arising challenges and open problems encountered in the future IRS empowered THz communications are also highlighted.Concretely,these emerging problems possibly originate from channel modeling,new material exploration,experimental IRS testbeds and intensive deployment.Ultimately,the combination of THz communications and IRS is capable of accelerating the development of 6G wireless networks.

Intelligent Reflecting Surfaces Enabled Cognitive Internet of Things Based on Practical Pathloss Model

In this paper,we aim to unlock the potential of intelligent reflecting surfaces(IRSs)in cognitive internet of things(loT).Considering that the secondary IoT devices send messages to the secondary access point(SAP)by sharing the spectrum with the primary network,the interference is introduced by the IoT devices to the primary access point(PAP)which profits from the IoT devices by pricing the interference power charged by them.A practical path loss model is adopted such that the IRSs deployed between the IoT devices and SAP serve as diffuse scatterers,but each reflected signal can be aligned with its own desired direction.Moreover,two transmission policies of the secondary network are investigated without/with a successive interference cancellation(SIC)technique.The signal-to-interference plus noise ratio(SINR)balancing is considered to overcome the nearfar effect of the IoT devices so as to allocate the resource fairly among them.We propose a Stackelberg game strategy to characterize the interaction between primary and secondary networks.For the proposed game,the Stackelberg equilibrium is analytically derived to optimally obtain the closed-form solution of the power allocation and interference pricing.Numerical results are demonstrated to validate the performance of the theoretical derivations.

Spectral Beam Combining of Fiber Lasers by Using Reflecting Volume Bragg Gratings

By employing three reflecting volume Bragg gratings, a near-infrared 4-channel spectral-beam-combining system is demonstrated to present 720 W combined power with a combining efficiency of 94.7%. The combined laser beam is near-diffraction-limited with a beam factor M^2-1.54. During this 4-channel beam-combining process, no special active cooling measures are used to evaluate the volume Bragg gratings as combining elements are under the higher power laser operation. Thermal expansion and period distortion are verified in a 2 k W 2-channel beam-combining process, and the heat issue in the transmission case is found to be more remarkable than that in the diffraction e-se. Transmitted and diffracted beams experience wave-front aberrations with different degrees, thus leading to distinct beam deterioration.

Secure Multigroup Multicast Communication Systems via Intelligent Reflecting Surface

This paper considers a secure multigroup multicast multiple-input single-output(MISO)communication system aided by an intelligent reflecting surface(IRS).Specifically,we aim to minimize the transmit power at Alice via jointly optimizing the transmit beamformer,artificial noise(AN)vector and phase shifts at the IRS subject to the secrecy rate constraints as well as the unit modulus constraints of IRS phase shifts.To tackle the optimization problem,we first transform it into a semidefinite relaxation(SDR)problem,and then alternately update the transmit beamformer and AN matrix as well as the phase shifts at the IRS.In order to reduce the high computational complexity,we further propose a low-complexity algorithm based on second-order cone programming(SOCP).We decouple the optimization problem into two sub-problems and optimize the transmit beamformer,AN vector and the phase shifts alternately by solving two corresponding SOCP subproblem.Simulation results show that the proposed SDR and SOCP schemes require half or less transmit power than the scheme without IRS,which demonstrates the advantages of introducing IRS and the effectiveness of the proposed methods.

Passive Beamforming Design for Intelligent Reflecting Surface Assisted MIMO Systems

Intelligent reflecting surfaces(IRSs)constitute passive devices,which are capable of adjusting the phase shifts of their reflected signals,and hence they are suitable for passive beamforming.In this paper,we conceive their design with the active beamforming action of multiple-input multipleoutput(MIMO)systems used at the access points(APs)for improving the beamforming gain,where both the APs and users are equipped with multiple antennas.Firstly,we decouple the optimization problem and design the active beamforming for a given IRS configuration.Then we transform the optimization problem of the IRS-based passive beamforming design into a tractable non-convex quadratically constrained quadratic program(QCQP).For solving the transformed problem,we give an approximate solution based on the technique of widely used semidefinite relaxation(SDR).We also propose a low-complexity iterative solution.We further prove that it can converge to a locally optimal value.Finally,considering the practical scenario of discrete phase shifts at the IRS,we give the quantization design for IRS elements on basis of the two solutions.Our simulation results demonstrate the superiority of the proposed solutions over the relevant benchmarks.

Delay Minimization for Intelligent Reflecting Surface Assisted Federated Learning

Federated learning(FL), which allows multiple mobile devices to cooperatively train a machine learning model without sharing their data with the central server, has received widespread attention.However, the process of FL involves frequent communications between the server and mobile devices,which incurs a long latency. Intelligent reflecting surface(IRS) provides a promising technology to address this issue, thanks to its capacity to reconfigure the wireless propagation environment. In this paper, we exploit the advantage of IRS to reduce the latency of FL. Specifically, we formulate a latency minimization problem for the IRS assisted FL system, by optimizing the communication resource allocations including the devices’ transmit-powers, the uploading time, the downloading time, the multi-user decomposition matrix and the phase shift matrix of IRS. To solve this non-convex problem, we propose an efficient algorithm which is based on the Block Coordinate Descent(BCD) and the penalty difference of convex(DC) algorithm to compute the solution. Numerical results are provided to validate the efficiency of our proposed algorithm and demonstrate the benefit of deploying IRS for reducing the latency of FL. In particular, the results show that our algorithm can outperform the baseline of Majorization-Minimization(MM) algorithm with the fixed transmit-power by up to 30%.

Performance Analysis of Intelligent Reflecting Surface Assisted Wireless Communication System

In this paper,we investigate the end-to-end performance of intelligent reflecting surface(IRS)-assisted wireless communication systems.We consider a system in which an IRS is deployed on a uniform planar array(UPA)configuration,including a large number of reflecting elements,where the transmitters and receivers are only equipped with a single antenna.Our objective is to analytically obtain the achievable ergodic rate,outage probability,and bit error rate(BER)of the system.Furthermore,to maximize the system’s signal-to-noise ratio(SNR),we design the phase shift of each reflecting element and derive the optimal reflection phase of the IRS based on the channel state information(CSI).We also derive the exact expression of the SNR probability density function(p.d.f.)and show that it follows a non-central Chi-square distribution.Using the p.d.f.,we then derive the theoretical results of the achievable rate,outage probability,and BER.The accuracy of the obtained theoretical results is also verified through numerical simulation.Itwas shown that the achievable rate,outage probability,and BER could be improved by increasing the number of reflecting elements and choosing an appropriate SNR regime.Furthermore,we also find that the IRS-assisted communication system achieves better performance than the existing end-to-end wireless communication.

Gaussian beamed millimetre wave propagation characteristics due to reflecting behaviour in circle tunnel

Propagation characterization is one of the main building blocks for millimetre wave （MMW） communication. The Gaussian beam has attractive features to become a prospective wave form for millimetre radio communication, especially for the utility inside tunnels. A ray tracing method embedded with spectral features of Gaussian beam is employed to analyze mil- limetre wave propagation in a circle tunnel in this paper. In consideration of geometrical figure of the tunnel, the superposition behaviour of direct and reflective beams is analyzed via simplified approximation of Gaussian beam spectral feature. Then the propagation models are established to derive amplitude, phase, and delay spread of received wave. A typical straight tunnel model is used to simulate the propagation behaviour, where strong multi-path effect with deeply fading of signal intensity and dramatically enhancing of delay spread emerges. For investigation of the spectral feature of the multi-path effect, a reflection loss of 14 dB is taken into consideration at a designated point. To analyze the influences of frequency and transmission distance, the propagation characteristics at three different frequencies of 45 GHz, 65 GHz and 85 GHz are compared with the beam travelling down the tunnel. In addition, three different reflection losses of 14 dB, 20 dB, and 26 dB at the frequency of 65 GHz are also investigated to research the influence of the reflecting coefficient.

Reflecting on the Conception of Post-Post-Cold War Era

After the September 11th events and especially after the follow-updevelopment of the US-Russian relationship,many Americangovernment officials in the Bush team stated time and again in

Plato as ＂Idealist,＇ and Aristotle as ＂Realist＂ （？） -Reflecting the idea and the ousia in View of Comparative Philosophy

One can see often in explanations of encyclopedia or lexicons of philosophy that Plato manifested primarily the absolute Idealism, whereas Aristotle verified antagonistically the relevance of realism. It is easy to pick up several parts of their representative works and prove that this thesis is corresponded to the original of Plato and Aristotle. But, in reflections of philosophy, we should not ignore a cautious view, focused just on this starting point： If the above mentioned thesis is used like a slogan, ＂Plato for idealism, Aristotle for realism,＂ as it often is, in the meantime there arises a dogmatic position which fixes our mental and intellectual activity only within the frame, so that everyone begins to reflect on Plato or Aristotle from that starting point in a certain framework. A critical and self-critical view of philosophy may bring this position for a query.