An Optimal Algorithm for Resource Allocation in D2D Communication

The number of mobile devices accessing wireless networks isskyrocketing due to the rapid advancement of sensors and wireless communicationtechnology. In the upcoming years, it is anticipated that mobile datatraffic would rise even more. The development of a new cellular networkparadigm is being driven by the Internet of Things, smart homes, and moresophisticated applications with greater data rates and latency requirements.Resources are being used up quickly due to the steady growth of smartphonedevices andmultimedia apps. Computation offloading to either several distantclouds or close mobile devices has consistently improved the performance ofmobile devices. The computation latency can also be decreased by offloadingcomputing duties to edge servers with a specific level of computing power.Device-to-device (D2D) collaboration can assist in processing small-scaleactivities that are time-sensitive in order to further reduce task delays. The taskoffloading performance is drastically reduced due to the variation of differentperformance capabilities of edge nodes. Therefore, this paper addressed thisproblem and proposed a new method for D2D communication. In thismethod, the time delay is reduced by enabling the edge nodes to exchangedata samples. Simulation results show that the proposed algorithm has betterperformance than traditional algorithm.

Resource Allocation Based on SFLA Algorithm for D2D Multicast Communications

Multicast device-to-device(D2D)communication technology is considered as one of the new technologies in the fifth generation(5G)networks that directly addresses the need for content sharing among internet users.In fact,when direct communication is available between devices,the spectral efficiency is improved by reusing the licensed cellular spectrum.The current studies show that D2D communication increases network capacity and reduces latency.In order to achieve the alternate capabilities,coordination is required to implement interference management.We considered subcarrier allocation for the uplink,in addition to the power control that takes place on the underlay network.The completed data rate in single multicast communication is significantly reduced and limited by nodes with lower channel quality.In this paper,we used Shuffled Frog Leaping Algorithm(SFLA)for resource allocation(RA)in D2D multicast communications.We compared the results of the SFLA algorithm with the Firefly Algorithm(FA),Ant Colony Optimization(ACO)and Particle Swarm Optimization(PSO);in terms of D2D user throughput,Cellular User(CU)throughput,network average throughput,network interference and signal interference noise ratio(SINR)target.The simulation results show that SFLA clearly outperforms other algorithms in terms of data rate under the high pressure of infeasibility.

Design of Semipersistent Resource Allocation in LTE-V Network

Radio network access technology currently used in 4G/5G is Long Term Evolution-Advanced(LTE-A),which was developed by 3rd Generation Partnership Project(3GPP).Device-to-device(D2D)communication is a technology enabling direct communications among wireless devices without forwarding through an evolved Node B(eNB).Moreover,D2D transmission can support vehicles as a vehicle-to-vehicle(V2V)environment.It is possible to avoid accidents via exchanging movement-related information among vehicles and effectively increase driving safety(and efficiency).However,radio resources are limited in radio networks.A vehicle transmits through D2D in Long Term Evolution-Vehicle(LTE-V)mode-3 standard,and an eNB can allocate the same spectrum radio resources for cellular and V2V links simultaneously.When using the same radio resources,the probability of interference may increase.This study designed a semipersistent resource allocation algorithm based on different cycles in an LTE-V network.Moreover,resource allocation under different cycles was analyzed,and a scheme for resource selection is proposed based on cycle size.The proposed Semi Persistent Gain Aware Resource Allocation(SP-GARA)scheme selects resources based on the expected sum rate of the cycle size and analyzes and discusses the results of the total sum rate at different cycles and speeds for an improved performance.

A Robust Resource Allocation Scheme for Device-to-Device Communications Based on Q-Learning

One of the most effective technology for the 5G mobile communications is Device-to-device(D2D)communication which is also called terminal pass-through technology.It can directly communicate between devices under the control of a base station and does not require a base station to forward it.The advantages of applying D2D communication technology to cellular networks are:It can increase the communication system capacity,improve the system spectrum efficiency,increase the data transmission rate,and reduce the base station load.Aiming at the problem of co-channel interference between the D2D and cellular users,this paper proposes an efficient algorithm for resource allocation based on the idea of Q-learning,which creates multi-agent learners from multiple D2D users,and the system throughput is determined from the corresponding state-learning of the Q value list and the maximum Q action is obtained through dynamic power for control for D2D users.The mutual interference between the D2D users and base stations and exact channel state information is not required during the Q-learning process and symmetric data transmission mechanism is adopted.The proposed algorithm maximizes the system throughput by controlling the power of D2D users while guaranteeing the quality-of-service of the cellular users.Simulation results show that the proposed algorithm effectively improves system performance as compared with existing algorithms.

Energy-Efficient Resource Allocation for Heterogeneous Network with Grouping D2D

In this paper,a new communication model is built named grouping D2D(GD2D).Different from the traditional D2D coordination,we proposed GD2D communication in licensed and unlicensed spectrum simultaneously.We formulate a resource allocation problem,which aims at maximizing the energy efficiency(EE)of the system while guaranteeing the quality-of-service(Qos)of users.To efficiently solve this problem,the non-convex optimization problem is first transformed into a convex optimization problem.By transforming the fractional-form problem into an equivalent subtractive-form problem,an iterative power allocation algorithm is proposed to maximize the system EE.Moreover,the optimal closedform power allocation expressions are derived by the Lagrangian approach.Simulation results show that our algorithm achieves higher EE performance than the traditional D2D communication scheme.

Resource Allocation in D2D-Aided High-Speed Railway Wireless Communication Systems： A Matching Theory Approach

With the rapid deployment of high speed railway(HSR) worldwide,both safety operation and comfort experience can be desired to evolve into a future era of intelligent transportation system.To eliminate boredom and provide entertainment for passengers,an intranet for internal communications among passengers named as onboard social network system(SNS) is needed.In this paper,the latest progress in HSR network architectures and technology building blocks are discussed to enable the implementation of the SNS.Meanwhile,based on the device-to-device(D2 D) communication technology for proximal information interaction,SNS can be efficiently facilitated.A dynamic resource allocation algorithm is proposed to maximize the total utility of the onboard SNS,which is solved with the matching theory method.Simulation results verify the convergence and efficiency of the proposed algorithm.

Resource Allocation and Power Control Policy for Device-to-Device Communication Using Multi-Agent Reinforcement Learning

Device-to-Device(D2D)communication is a promising technology that can reduce the burden on cellular networks while increasing network capacity.In this paper,we focus on the channel resource allocation and power control to improve the system resource utilization and network throughput.Firstly,we treat each D2D pair as an independent agent.Each agent makes decisions based on the local channel states information observed by itself.The multi-agent Reinforcement Learning(RL)algorithm is proposed for our multi-user system.We assume that the D2D pair do not possess any information on the availability and quality of the resource block to be selected,so the problem is modeled as a stochastic non-cooperative game.Hence,each agent becomes a player and they make decisions together to achieve global optimization.Thereby,the multi-agent Q-learning algorithm based on game theory is established.Secondly,in order to accelerate the convergence rate of multi-agent Q-learning,we consider a power allocation strategy based on Fuzzy C-means(FCM)algorithm.The strategy firstly groups the D2D users by FCM,and treats each group as an agent,and then performs multi-agent Q-learning algorithm to determine the power for each group of D2D users.The simulation results show that the Q-learning algorithm based on multi-agent can improve the throughput of the system.In particular,FCM can greatly speed up the convergence of the multi-agent Q-learning algorithm while improving system throughput.

Optimal Resource Allocation Method for Device-to-Device Communication in 5G Networks

With the rapid development of the next-generation mobile network,the number of terminal devices and applications is growing explosively.Therefore,how to obtain a higher data rate,wider network coverage and higher resource utilization in the limited spectrum resources has become the common research goal of scholars.Device-to-Device(D2D)communication technology and other frontier communication technologies have emerged.Device-to-Device communication technology is the technology that devices in proximity can communicate directly in cellular networks.It has become one of the key technologies of the fifth-generation mobile communications system(5G).D2D communication technology which is introduced into cellular networks can effectively improve spectrum utilization,enhance network coverage,reduce transmission delay and improve system throughput,but it would also bring complicated and various interferences due to reusing cellular resources at the same time.So resource management is one of the most challenging and importing issues to give full play to the advantages of D2D communication.Optimal resource allocation is an important factor that needs to be addressed in D2D communication.Therefore,this paper proposes an optimization method based on the game-matching concept.The main idea is to model the optimization problem of the quality-of-experience based on user fairness and solve it through game-matching theory.Simulation results show that the proposed algorithm effectively improved the resource allocation and utilization as compared with existing algorithms.

A Joint Resource Allocation Algorithm for D2D Communication

The emergence of multimedia services has meant a substantial increase in the number of devices in mobile networks and driving the demand for higher data transmission rates.The result is that,cellular networks must technically evolve to support such higher rates,to be equipped with greater capacity,and to increase the spectral and energy efficiency.Compared with 4G technology,the 5G networks are being designed to transmit up to 100 times more data volume with devices whose battery life is 10 times longer.Therefore,this new generation of networks has adopted a heterogeneous and ultra-dense architecture,where different technological advances are combined such as device-to-device(D2D)communication,which is one of the key elements of 5G networks.It has immediate applications such as the distribution of traffic load(data offloading),communications for emergency services,and the extension of cellular coverage,etc.In this communication model,two devices can communicate directly if they are close to each other without using a base station or a remote access point.Thus,eliminating the interference between theD2Dand cellular communication in the network.The interference management has become a hot issue in current research.In order to address this problem,this paper proposes a joint resource allocation algorithm based on the idea of mode selection and resource assignment.Simulation results showthat the proposed algorithm effectively improves the systemperformance and reduces the interference as compared with existing algorithms.

Secure Resource Allocation in Device-to-Device Communications Underlaying Cellular Networks

With increasing the demand for transmitting secure information in wireless networks,deviceto-device(D2D)communication has great potential to improve system performance.As a well-known security risk is eavesdropping in D2D communication,ensuring information security is quite challenging.In this paper,we first obtain the closed-forms of the secrecy outage probability(SOP)and the secrecy ergodic capacity(SEC)for direct and decodeand-forward(DF)relay modes.Numerical results are presented to verify the theoretical results,and these results show the cases that the DF relay mode improves security performance compared to the direct mode at long distances between the transmitter and receiver nodes.Further,we look into the optimization problems of secure resource allocation in D2D communication to maximize the SEC and to minimize the SOP by considering the strictly positive secrecy capacity constraint as a mixed-integer non-linear programming(MINLP)problem.In the continue,we convert the MINLP to convex optimization.Finally,we solve this program with a dual method and obtain an optimal solution in the direct and DF relay modes.

Resource Allocation and Optimization in Device-to-Device Communication 5G Networks

The next-generation wireless networks are expected to provide higher capacity,system throughput with improved energy efficiency.One of the key technologies,to meet the demand for high-rate transmission,is deviceto-device(D2D)communication which allows users who are close to communicating directly instead of transiting through base stations,and D2D communication users to share the cellular user chain under the control of the cellular network.As a new generation of cellular network technology,D2D communication technology has the advantages of improving spectrum resource utilization and improving system throughput and has become one of the key technologies that have been widely concerned in the industry.However,due to the sharing of cellular network resources,D2D communication causes severe interference to existing cellular systems.One of the most important factors in D2D communication is the spectrum resources utilization and energy consumption which needs considerable attention from research scholars.To address these issues,this paper proposes an efficient algorithm based on the idea of particle swarm optimization.The main idea is to maximize the energy efficiency based on the overall link optimization of D2D user pairs by generating an allocation matrix of spectrum and power.The D2D users are enabled to reuse multiple cellular user’s resources by enhancing their total energy efficiency based on the quality of service constraints and the modification of location and speed in particle swarm.Such constraint also provides feasibility to solve the original fractional programming problem.Simulation results indicate that the proposed scheme effectively improved the energy efficiency and spectrum utilization as compared with other competing alternatives.

Resource Allocation of Agricultural Science and Technology R&D

The status quo of resource allocation of agricultural science and technology R&D(research and development)both at home and abroad,including the amount and function of agricultural science and technology research funds,human resources in the resources of agricultural science and technology R&D,the efficiency of resource allocation of agricultural science and technology R&D,the management system of agricultural scientific innovation and the operation status of scientific funds,is analyzed.The problems in the current resource allocation of agricultural science and technology R&D are put forward,including unreasonable resource allocation;low efficiency,and low efficiency of the transformation of agricultural scientific achievements.The highly effective resource allocation of agricultural science and technology R&D is analyzed from the aspects of resource allocation structure,environment,channel,spatial layout and industrial chain.

云南省R&D经费投入结构动态研究

为研究云南省“十二五”以来R&D经费投入结构变化,分析R&D经费投入现状,并与全国,东、中、西部地区及临近省份进行了对比;从资金来源和资金配置视角,运用Cobb-Douglas效用函数及其修正模型对R&D经费投入结构展开动态分析。结果表明:云南省R&D经费投入结构不尽合理,资金来源中政府资金占比较低且呈下降趋势,资金配置中基础研究和应用研究投入不足,与最优结构偏离程度较大。针对存在的问题,提出持续加大政府R&D经费投入力度、围绕产业链提升基础研究和应用研究比重的建议。

基于改进MOEA/D的车联网通信资源分配算法

为获得车联网通信资源分配的最优解,提出一种基于改进MOEA/D的车联网通信资源分配优化算法。将车联网资源请求的阻塞率和资源请求成功的总成本这2个相互冲突的网络通信资源分配要素作为网络通信资源分配的2个优化目标,根据车联网中行驶车辆的特点,对请求资源车辆和提供资源车辆设置约束条件。在此基础上,采用自适应邻域策略平衡进化过程中种群的收敛性和分布性,并将迭代次数引入自适应度,调节交叉算子和变异算子,使种群中较差的个体也具有遗传性,从而保证种群的多样性。同时,随着迭代次数的增加,种群中较差个体遗传性降低,较好个体遗传能力增强,从而保证种群的优化。仿真结果表明,该算法针对最小化阻塞率和最小化成本这2个目标能够获得满意的优化效果,在迭代次数、车辆数和资源请求数变化情况下都存在最优解,在相同迭代次数下,与基于支配的多目标算法SPEA2和NSGA-II相比具有较低的阻塞率和较好的收敛性。

闽鲁鄂豫四省企业研发补助政策比较分析

企业研发补助政策作为具有普惠性的政策工具,能够有效促进企业加大研发投入力度。近年来,福建、山东、湖北、河南积极实施企业研发补助政策,本文分析了四省份企业研发补助对象、补助依据、补助标准的异同点,剖析了四省份企业研发补助结果及研发补助政策实施过程中存在的问题,并据此提出对全国其他省市开展企业研发补助工作的建议。

基于DEA模型的宁夏科技资源配置研究

宁夏科技资源配置的规模、效率和结构受到其区域经济和社会发展的影响,存在明显的结构性矛盾。从投入-产出的视角,运用DEA-Malmquist模型,对宁夏2015—2019年科技资源配置进行分析发现,2015-2019年宁夏科技资源配置效率呈缓慢上升趋势,且宁夏地区科技创新资源配置效率整体运行效率较高,技术进步指标对全要素生产率指标促进作用更大,宁夏各市中资源配置效率最高的城市为中卫市。基于此,试图找出科技资源配置效率的制约因素,提出合理、有效的科技资源配置优化路径。

效率视角下云南省研发资源配置优化研究

基于DEA-BCC-Malmquist指数模型对云南省“十二五”以来研发(R&D)资源配置效率展开测度分析。结果表明:“十二五”以来,云南省R&D资源配置综合效率、纯技术效率均处于DEA(数据包络分析)非有效状态,与全国和临近省份差距明显,R&D产出不足是主要原因;云南省R&D资源配置效率年份间变化相对平稳,但平均值略有下降,技术效率指数是主要制约因素。建议从完善人才激励机制、优化科研管理、强化成果产出、推动产学研协同创新等方面加以改进优化。

基于MOEA/D算法的衡水市水资源多目标优化配置

水资源供需之间的矛盾日趋激化,优化配置、高效利用区域内有限水资源变得尤为重要。以衡水市水资源配置为例,综合考虑衡水市水资源优化配置需求,建立了以社会效益、经济效益和生态效益为目标函数的水资源多目标优化配置模型,给出了基于MOEA/D算法的水资源优化配置方案,并将所提方案与基于NSGA-Ⅲ算法的方案进行了对比试验。结果表明,所提方案优于文献方案,可为衡水市水资源合理配置提供依据。

水资源优化配置在枋洋水利枢纽的应用

为了能够更加高效地对有限的水资源进行开发利用,减少供需矛盾和降低水资源风险,有必要对比较先进的水资源优化调度方法展开更加深入的研究。因此,建立一种水资源优化调度模型,以供水缺额最小以及供水效益最大作为调度目标,并充分考虑水源供水能力、用水户需水限制以及实际应用中的变量非负约束,使用MOEA/D算法对模型进行计算求解,并从Pareto解集中优选得到水资源调配的最优方案。以枋洋水利枢纽为例进行实验,结果证明利用MOEA/D算法研究水资源优化调配问题是有效可行的。

Device Discovery in D2D Communication: Scenarios and Challenges

Device to Device (D2D) communication is expected to be anessential part of 5G cellular networks. D2D communication enables closeproximitydevices to establish a direct communication session. D2D communicationoffers many advantages, such as reduced latency, high data rates,range extension, and cellular offloading. The first step to establishing a D2Dsession is device discovery;an efficient device discovery will lead to efficientD2D communication. D2D device further needs to manage its mode of communication,perform resource allocation, manage its interference and mostimportantly control its power to improve the battery life of the device. Thiswork has developed six distinct scenarios in which D2D communication canbe initiated, considering their merits, demerits, limitations, and optimizationparameters. D2D communication procedures for the considered scenarioshave been formulated, based upon the signal flow, containing device discovery,resource allocation, and session teardown. Finally, latency for each scenariohas been evaluated, based on propagation and processing delays.