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Channel assignment and power allocation for throughput improvement with PPO in B5G heterogeneous edge networks

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Digital Communications and Networks 2024年第1期10卷 109-116页

作者： Xiaoming He Yingchi Mao Yinqiu Liu Ping Ping Yan Hong Han Hu The College of Computer and Information Hohai UniversityNanjingChina The Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai UniversityNanjing China The School of Computer Science and Engineering Nanyang Technological UniversitySingapore The College of Textile and Clothing Engineering Soochow UniversitySuzhouChina The College of Internet of Things Nanjing University of Posts and TelecomurunicationsNanjingChina

In Beyond the Fifth Generation(B5G)heterogeneous edge networks,numerous users are multiplexed on a channel or served on the same frequency resource block,in which case the transmitter applies coding and the receiver uses interference ***,uncoordinated radio resource allocation can reduce system throughput and lead to user inequity,for this reason,in this paper,channel allocation and power allocation problems are formulated to maximize the system sum rate and minimum user achievable *** the construction model is non-convex and the response variables are high-dimensional,a distributed Deep Reinforcement Learning(DRL)framework called distributed Proximal Policy Optimization(PPO)is proposed to allocate or assign ***,several simulated agents are trained in a heterogeneous environment to find robust behaviors that perform well in channel assignment and power ***,agents in the collection stage slow down,which hinders the learning of other ***,a preemption strategy is further proposed in this paper to optimize the distributed PPO,form DP-PPO and successfully mitigate the straggler *** experimental results show that our mechanism named DP-PPO improves the performance over other DRL methods.

关键词： B5G Heterogeneous edge networks PPO Channel assignment power allocation Throughput

A Deep Reinforcement Learning-Based Technique for Optimal power allocation in Multiple Access Communications

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Intelligent Automation & Soft Computing 2024年第1期39卷 93-108页

作者： Sepehr Soltani Ehsan Ghafourian Reza Salehi Diego Martín Milad Vahidi Department of Industrial Engineering College of EngineeringUniversity of HoustonHoustonTX77204USA Department of Computer Science Iowa State UniversityAmesIowaUSA ETSI de Telecomunicación Universidad Politécnica de MadridMadridSpain Faculty of School of Plant and Environmental Sciences Virginia Polytechnic Institute and StateUniversityBlacksburgVirginia24060USA

Formany years,researchers have explored power allocation(PA)algorithms driven bymodels in wireless networks where multiple-user communications with interference are ***,data-driven machine learning methods have become quite popular in analyzing wireless communication systems,which among them deep reinforcement learning(DRL)has a significant role in solving optimization issues under certain *** this purpose,in this paper,we investigate the PA problem in a k-user multiple access channels(MAC),where k transmitters(e.g.,mobile users)aim to send an independent message to a common receiver(e.g.,base station)through wireless *** this end,we first train the deep Q network(DQN)with a deep Q learning(DQL)algorithm over the simulation environment,utilizing offline ***,the DQN will be used with the real data in the online training method for the PA issue by maximizing the sumrate subjected to the source ***,the simulation results indicate that our proposedDQNmethod provides better performance in terms of the sumrate compared with the available DQL training approaches such as fractional programming(FP)and weighted minimum mean squared error(WMMSE).Additionally,by considering different user densities,we show that our proposed DQN outperforms benchmark algorithms,thereby,a good generalization ability is verified over wireless multi-user communication systems.

关键词： Deep reinforcement learning deep Q learning multiple access channel power allocation

power allocation and Antenna Selection for Heterogeneous Cellular Networks

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China Communications 2023年第8期20卷 220-233页

作者： Lingyi Kong Yulong Zou Yuhan Jiang Jia Zhu School of Telecommunications and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China

In this paper,we investigate the system performance of a heterogeneous cellular network consisting of a macro cell and a small cell,where each cell has one user and one base station with multiple *** macro base station(MBS)and the small base station(SBS)transmit their confidential messages to the macro user(MU)and the small user(SU)over their shared spectrum *** enhance the system sum rate(SSR)of MBS-MU and SBS-SU transmission,we propose joint antenna selection combined with optimal power allocation(JAS-OPA)scheme and independent antenna selection combined with optimal power allocation(IAS-OPA)*** JAS-OPA scheme requires to know the channel state information(CSI)of transmission channels and interference channels,while the IAS-OPA scheme only needs to know the CSI of transmission *** addition,we carry out the analysis for conventional round-robin antenna selection combined with optimal power allocation(RR-OPA)as a benchmark *** formulate the SSR maximization problem through the power allocation between MBS and SBS and propose iterative OPA algorithms for JAS-OPA,IAS-OPA and RR-OPA schemes,*** results show that the OPA schemes outperform the equal power allocation in terms of ***,we provide the closed-form expression of the system outage probability(SOP)for IAS scheme and RR scheme,it shows the SOP performance can be significantly improved by our proposed IAS scheme compared with RR scheme.

关键词： heterogeneous networks antenna selection inter-interference power allocation

Joint waveform selection and power allocation algorithm in manned/unmanned aerial vehicle hybrid swarm based on chance-constraint programming

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Journal of Systems Engineering and Electronics 2022年第3期33卷 551-562页

作者： ZHANG Yuanshi PAN Minghai LONG Weijun LI Hua HAN Qinghua College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China Nanjing Research Institute of Electronics Technology Nanjing 210039China College of Artificial Intelligence Zaozhuang UniversityZaozhuang 277160China

In this paper, we propose a joint waveform selection and power allocation(JWSPA) strategy based on chance-constraint programming(CCP) for manned/unmanned aerial vehicle hybrid swarm(M/UAVHS) tracking a single target. Accordingly,the low probability of intercept(LPI) performance of system can be improved by collaboratively optimizing transmit power and waveform. For target radar cross section(RCS) prediction, we design a random RCS prediction model based on electromagnetic simulation(ES) of target. For waveform selection, we build a waveform library to adaptively manage the frequency modulation slope and pulse width of radar waveform. For power allocation,the CCP is employed to balance tracking accuracy and power resource. The Bayesian Cramér-Rao lower bound(BCRLB) is adopted as a criterion to measure target tracking accuracy. The hybrid intelli gent algorithms, in which the stochastic simulation is integrated into the genetic algorithm(GA), are used to solve the stochastic optimization problem. Simulation results demonstrate that the proposed JWSPA strategy can save more transmit power than the traditional fixed waveform scheme under the same target tracking accuracy.

关键词： multistatic radar system(MRS) target tracking manned/unmanned aerial vehicle hybrid swarm(M/UAVHS) power allocation waveform selection

Joint target assignment and power allocation in the netted C-MIMO radar when tracking multi-targets in the presence of self-defense blanket jamming

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Defence Technology（防务技术） 2023年第6期24卷 414-427页

作者： Zhengjie Li Junwei Xie Haowei Zhang Jiahao Xie Air and Missile Defense College Air Force Engineering UniversityXi'an 710051China Space Engineering University of Strategic Support Force Beijing 101416China

The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking *** resource management can greatly ensure the combat capability of the *** this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is *** architecture based on the distributed fusion is used in the radar network to estimate target state *** deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is *** maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource *** the formulated JTAPA is non-convex,we propose an efficient two-step solution *** terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.

关键词： Netted radar system MIMO Target assignment power allocation Multi-targets tracking Self-defense blanket jamming

Trajectory Optimization and power allocation Scheme Based on DRL in Energy Efficient UAV-Aided Communication Networks

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Chinese Journal of Electronics 2022年第3期31卷 397-407页

作者： WANG Chaowei CUI Yuling DENG Danhao WANG Weidong JIANG Fan School of Electronic Engineering Beijing University of Posts and Telecommunications Key Laboratory of Universal Wireless Communications Ministry of Education School of Telecommunications and Information Engineering Xi'an University of Posts and Telecommunications

With flexibility, convenience and mobility, unmanned aerial vehicles(UAVS) can provide wireless communication networks with lower costs, easier deployment, higher network scalability and larger *** paper proposes the deep deterministic policy gradient algorithm to jointly optimize the power allocation and flight trajectory of UAV with constrained effective energy to maximize the downlink throughput to ground users. To validate the proposed algorithm, we compare with the random algorithm, Q-learning algorithm and deep Q network algorithm. The simulation results show that the proposed algorithm can effectively improve the communication quality and significantly extend the service time of UAV. In addition, the downlink throughput increases with the number of ground users.

关键词： Unmanned aerial vehicles Deep deterministic policy gradient Trajectory optimization power allocation Energy efficient

Energy-efficient power allocation for NOMA heterogeneous networks with imperfect CSI

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The Journal of China Universities of Posts and Telecommunications 2022年第1期29卷 102-112页

作者： Song Xin Huang Xue Gao Yiming Qian Haijun School of Computer and Communication Engineering Northeastern University at QinhuangdaoQinhuangdao 066000China

In this paper,an optimal user power allocation scheme is proposed to maximize the energy efficiency for downlink non-orthogonal multiple access(NOMA)heterogeneous networks(HetNets).Considering channel estimation errors and inter-user interference under imperfect channel state information(CSI),the energy efficiency optimization problem is formulated,which is non-deterministic polynomial(NP)-hard and *** cope with this intractable problem,the optimization problem is converted into a convex problem and address it by the Lagrangian dual ***,it is difficult to obtain closed-form solutions since the variables are coupled with each ***,a Lagrangian and sub-gradient based algorithm is *** the inner layer loop,optimal powers are derived by the sub-gradient *** the outer layer loop,optimal Lagrangian dual variables are *** results show that the proposed algorithm can significantly improve energy efficiency compared with traditional power allocation algorithms.

关键词： heterogeneous networks non-orthogonal multiple access imperfect channel state information power allocation

Elliptical Cell Based Beamforming Design with an Improved β-Fairness power allocation for HSR Communication Systems

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China Communications 2022年第5期19卷 112-128页

作者： Ximei Liu Deli Qiao School of Communication and Electronic Engineering East China Normal UniversityShanghai 200241China

In this paper,a beamforming scheme to improve the coverage in high-speed railway communication systems is investigated.A dedicated coverage model,where the coverage cell is an ellipse rather than the traditional circular or linear,is *** on the elliptical coverage cell,an optimization problem for the beamforming design is formulated to maximize the percentage of railway coverage,subject to the constraints on equal expected designed propagation gain(the gain obtained by a combination of designed beam and propagation channel)on the elliptical curve,i.e.,the expectation of designed propagation gain on the elliptical curve are all *** that the coverage can be improved by increasing the minimum designed propagation gain on the railway,the problem can be recast to maximizing the equal expected designed propagation gain on the elliptical ***,a beamforming design with an improved β-fairness power allocation,where the optimization problem is formulated to maximize the minimum expected received power over time with the constraints on elliptical cell based beamforming and mobile service amount,is proposed to further improve the *** alternating iteration algorithm is developed to find the optimal beamforming vector and the instantaneous transmit *** numerical results,it is found that the beamforming designed on the elliptical curve covers longer railway than beamforming designed on the railway directly,and the coverage of elliptical cell based beamforming can be increased with the *** addition,beamforming with the improvedβ-fairness power allocation can further improve the railway coverage and mobile service amount ***,it is shown that the larger eccentricity of the ellipse with appropriately chosen BS location,the larger coverage distance.

关键词： high-speed railway communication elliptical cell based beamforming coverage power allocation mobile service amount

Fairness optimization and power allocation in cognitive NOMA/OMA V2V network with imperfect SIC

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The Journal of China Universities of Posts and Telecommunications 2023年第6期30卷 68-81页

作者： Liang Xiaolin Liu Qianlong Cao Wangbin Liu Shuaiqi Zhao Shuhuan Zhao Xiongwen College of Electronic and Information Engineering Hebei UniversityBaoding 071002China Hebei Key Laboratory of power Internet of Things Technology North China Electric Power UniversityBaoding 071003China School of Electrical and Electronic Engineering North China Electric Power UniversityBaoding 071003China School of Electrical and Electronic Engineering North China Electric Power UniversityBeijing 102206China

In order to improve the reliability and resource utilization efficiency of vehicle-to-vehicle(V2V)communication system,in this paper,the fairness optimization and power allocation for the cognitive V2V network that takes into account the realistic three-dimensional(3D)channel are ***-scale and small-scale fading are considered in the proposed channel *** adaptive non-orthogonal multiple access(NOMA)/orthogonal multiple access(OMA)scheme is proposed to reduce the complexity of successive-interference-cancellation(SIC)in decoding and improve spectrum ***,a fairness index that takes into account each user's requirements is proposed to indicate the optimal point *** the imperfect SIC,the optimization problem of maximizing user fairness is ***,a subgradient descent method is proposed to solve the optimization problem with customizable *** the computational complexity of the proposed method is *** achievable rate,outage probability and user fairness are *** results show that the proposed adaptive NOMA/OMA(A-NOMA/OMA)outperforms both NOMA and *** simulation results are compared with validated analysis to confirm the theoretical analysis.

关键词： sadaptive non-orthogonal multiple access(NOMA)/orthogonal multiple access(OMA) user fairness power allocation imperfect successive-interference-cancellation(SIC) vehicle-to-vehicle(V2V)communication