Optimization of resource allocation in FDD massive MIMO systems

The performance of massive MIMO systems relies heavily on the availability of Channel State Information at the Transmitter(CSIT).A large amount of work has been devoted to reducing the CSIT acquisition overhead at the pilot training and/or CsI feedback stage.In fact,the downlink communication generally includes three stages,i.e.,pilot training,CsI feedback,and data transmission.These three stages are mutually related and jointly determine the overall system performance.Unfortunately,there exist few studies on the reduction of csIT acquisition overhead from the global point of view.In this paper,we integrate the Minimum Mean Square Error(MMSE)channel estimation,Random Vector Quantization(RVQ)based limited feedback and Maximal Ratio Combining(MRC)precoding into a unified framework for investigating the resource allocation problem.In particular,we first approximate the covariance matrix of the quantization error with a simple expression and derive an analytical expression of the received Signal-to-Noise Ratio(SNR)based on the deterministic equivalence theory.Then the three performance metrics(the spectral efficiency,energy efficiency,and total energy consumption)oriented problems are formulated analytically.With practical system requirements,these three metrics can be collaboratively optimized.Finally,we propose an optimization solver to derive the optimal partition of channel coherence time.Experiment results verify the benefits of the proposed resource allocation schemes under three different scenarios and illustrate the tradeoff of resource allocation between three stages.

Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV units.However,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood.This study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the PV-ESS.First,SD and SMC models were set up.Second,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was constructed.Finally,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation.Additionally,negative electricity prices were considered during clearing processes.The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

Joint Allocation of Computing and Connectivity Resources in Survivable Inter-Datacenter Elastic Optical Networks

Inter-datacenter elastic optical networks(EON)need to provide the service for the requests of cloud computing that require not only connectivity and computing resources but also network survivability.In this paper,to realize joint allocation of computing and connectivity resources in survivable inter-datacenter EONs,a survivable routing,modulation level,spectrum,and computing resource allocation algorithm(SRMLSCRA)algorithm and three datacenter selection strategies,i.e.Computing Resource First(CRF),Shortest Path First(SPF)and Random Destination(RD),are proposed for different scenarios.Unicast and manycast are applied to the communication of computing requests,and the routing strategies are calculated respectively.Simulation results show that SRMLCRA-CRF can serve the largest amount of protected computing tasks,and the requested calculation blocking probability is reduced by 29.2%,28.3%and 30.5%compared with SRMLSCRA-SPF,SRMLSCRA-RD and the benchmark EPS-RMSA algorithms respectively.Therefore,it is more applicable to the networks with huge calculations.Besides,SRMLSCRA-SPF consumes the least spectrum,thereby exhibiting its suitability for scenarios where the amount of calculation is small and communication resources are scarce.The results demonstrate that the proposed methods realize the joint allocation of computing and connectivity resources,and could provide efficient protection for services under single-link failure and occupy less spectrum.

Joint Optimization for on-Demand Deployment of UAVs and Spectrum Allocation in UAVs-Assisted Communication

To improve the efficiency and fairness of the spectrum allocation for ground communication assisted by unmanned aerial vehicles(UAVs),a joint optimization method for on-demand deployment and spectrum allocation of UAVs is proposed,which is modeled as a mixed-integer non-convex optimization problem(MINCOP).An algorithm to estimate the minimum number of required UAVs is firstly proposed based on the pre-estimation and simulated annealing.The MINCOP is then decomposed into three sub-problems based on the block coordinate descent method,including the spectrum allocation of UAVs,the association between UAVs and ground users,and the deployment of UAVs.Specifically,the optimal spectrum allocation is derived based on the interference mitigation and channel reuse.The association between UAVs and ground users is optimized based on local iterated optimization.A particle-based optimization algorithm is proposed to resolve the subproblem of the UAVs deployment.Simulation results show that the proposed method could effectively improve the minimum transmission rate of UAVs as well as user fairness of spectrum allocation.

River width and depth as key factors of diurnal activity energy expenditure allocation for wintering Spot-billed Ducks in the Xin'an River Basin

Rivers are important habitats for wintering waterbirds.However,they are easily influenced by natural and human activities.An important approach for waterbirds to adapt to habitats is adjusting the activity time and energy expenditure allocation of diurnal behavior.The compensatory foraging hypothesis predicts that increased energy expenditure leads to longer foraging time,which in turn increases food intake and helps maintain a constant energy balance.However,it is unclear whether human-disturbed habitats result in increased energy expenditure related to safety or foraging.In this study,the scan sample method was used to observe the diurnal behavior of the wintering Spot-billed Duck(Anas poecilorhyncha) in two rivers in the Xin’an River Basin from October 2021 to March 2022.The allocation of time and energy expenditure for activity in both normal and disturbed environments was calculated.The results showed that foraging accounted for the highest percentage of time and energy expenditure.Additionally,foraging decreased in the disturbed environment than that in the normal environment.Resting behavior showed the opposite trend,while other behaviors were similar in both environments.The total diurnal energy expenditure of ducks in the disturbed environment was greater than that in the normal environment,with decreased foraging and resting time percentage and increased behaviors related to immediate safety(swimming and alert) and comfort.These results oppose the compensatory foraging hypothesis in favor of increased security.The optimal diurnal energy expenditure model included river width and water depth,which had a positive relationship;an increase in either of these two factors resulted in an increase in energy expenditure.This study provides a better understanding of energy allocation strategies underlying the superficial time allocation of wintering waterbirds according to environmental conditions.Exploring these changes can help understand the maximum fitness of wintering waterbirds in response to nature and human influences.

Online Learning-Based Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Networks

Mobile edge computing(MEC)-enabled satellite-terrestrial networks(STNs)can provide Internet of Things(IoT)devices with global computing services.Sometimes,the network state information is uncertain or unknown.To deal with this situation,we investigate online learning-based offloading decision and resource allocation in MEC-enabled STNs in this paper.The problem of minimizing the average sum task completion delay of all IoT devices over all time periods is formulated.We decompose this optimization problem into a task offloading decision problem and a computing resource allocation problem.A joint optimization scheme of offloading decision and resource allocation is then proposed,which consists of a task offloading decision algorithm based on the devices cooperation aided upper confidence bound(UCB)algorithm and a computing resource allocation algorithm based on the Lagrange multiplier method.Simulation results validate that the proposed scheme performs better than other baseline schemes.

Role Dynamic Allocation of Human-Robot Cooperation Based on Reinforcement Learning in an Installation of Curtain Wall

A real-time adaptive roles allocation method based on reinforcement learning is proposed to improve humanrobot cooperation performance for a curtain wall installation task.This method breaks the traditional idea that the robot is regarded as the follower or only adjusts the leader and the follower in cooperation.In this paper,a self-learning method is proposed which can dynamically adapt and continuously adjust the initiative weight of the robot according to the change of the task.Firstly,the physical human-robot cooperation model,including the role factor is built.Then,a reinforcement learningmodel that can adjust the role factor in real time is established,and a reward and actionmodel is designed.The role factor can be adjusted continuously according to the comprehensive performance of the human-robot interaction force and the robot’s Jerk during the repeated installation.Finally,the roles adjustment rule established above continuously improves the comprehensive performance.Experiments of the dynamic roles allocation and the effect of the performance weighting coefficient on the result have been verified.The results show that the proposed method can realize the role adaptation and achieve the dual optimization goal of reducing the sum of the cooperator force and the robot’s Jerk.

Allocation of Public Service Facilities in Villages and Towns from the Perspective of Smart Contraction: A Case Study of Zixi County, Jiangxi Province

The limitation of traditional layout system and the continuous contraction of villages and towns have brought challenges to the layout of public service facilities.It is an imperative task against this background to integrate space resources and allocate public service facilities scientifically and reasonably.This paper took the system and method of rural public service facility allocation from the perspective of smart contraction as the theoretic support,and Zixi County in Jiangxi Province for example,built the four-level life circle of“county-fundamental-basic-routine”based on the influence factors of facility allocation,village and town contraction strength,rural comprehensive assessment results,residents’trip willingness and demands on public service facilities,finally proposed the suggestions for optimizing the allocation of village and town public service facilities.

Optimal allocation method of electric/air braking force of high-speed train considering axle load transfer

Reasonable distribution of braking force is a factor for a smooth,safe,and comfortable braking of trains.A dynamic optimal allocation strategy of electric-air braking force is proposed in this paper to solve the problem of the lack of consideration of adhesion difference of train wheelsets in the existing high-speed train electric-air braking force optimal allocation strategies.In this method,the braking strategy gives priority to the use of electric braking force.The force model of a single train in the braking process is analyzed to calculate the change of adhesion between the wheel and rail of each wheelset after axle load transfer,and then the adhesion of the train is estimated in real time.Next,with the goal of maximizing the total adhesion utilization ratio of trailer/motor vehicles,a linear programming distribution function is constructed.The proportional coefficient of adhesion utilization ratio of each train and the application upper limit of braking force in the function is updated according to the change time point of wheelset adhesion.Finally,the braking force is dynamically allocated.The simulation results of Matlab/Simulink show that the proposed algorithm not only uses the different adhesion limits of each trailer to reduce the total amount of braking force undertaken by the motor vehicle,but also considers the adhesion difference of each wheelset.The strategy can effectively reduce the risk and time of motor vehicles during the braking process and improve the stability of the train braking.

Multi-Agent Deep Deterministic Policy Gradien-Based Task Offloading Resource Allocation Joint Offloading

With the advancement of technology and the continuous innovation of applications, low-latency applications such as drones, online games and virtual reality are gradually becoming popular demands in modern society. However, these applications pose a great challenge to the traditional centralized mobile cloud computing paradigm, and it is obvious that the traditional cloud computing model is already struggling to meet such demands. To address the shortcomings of cloud computing, mobile edge computing has emerged. Mobile edge computing provides users with computing and storage resources by offloading computing tasks to servers at the edge of the network. However, most existing work only considers single-objective performance optimization in terms of latency or energy consumption, but not balanced optimization in terms of latency and energy consumption. To reduce task latency and device energy consumption, the problem of joint optimization of computation offloading and resource allocation in multi-cell, multi-user, multi-server MEC environments is investigated. In this paper, a dynamic computation offloading algorithm based on Multi-Agent Deep Deterministic Policy Gradient (MADDPG) is proposed to obtain the optimal policy. The experimental results show that the algorithm proposed in this paper reduces the delay by 5 ms compared to PPO, 1.5 ms compared to DDPG and 10.7 ms compared to DQN, and reduces the energy consumption by 300 compared to PPO, 760 compared to DDPG and 380 compared to DQN. This fully proves that the algorithm proposed in this paper has excellent performance.

Research on the Balanced Development of Urban and Rural Compulsory Education Through Education Resource Allocation

With the rapid development of our country’s economy,education has gradually become the focus of social attention.The problem of unbalanced distribution of urban and rural educational resources has become increasingly prominent,urban educational resources are relatively rich,while rural educational resources are relatively scarce,and the balanced development of urban and rural compulsory education has become an urgent task.This paper mainly investigates and studies the distribution of urban and rural educational resources,discusses the unbalanced distribution of urban and rural educational resources and analyzes the reasons,and puts forward a series of corresponding solutions to promote the balanced development of urban and rural compulsory education.

Effects of Sand Burial on the Survival, Growth, and Biomass Allocation in Semi-shrub Hedysarum laeve Seedlings

Hedysarum laeve Maxim. (Leguminosae) is one of the major species used frequently in revegetation of dune_field in the sandlands of the northern part of China by means of aerial sowing. Seedlings of the species after emergence above the sand surface may be buried in sand to various depths during its establishment in late spring and early summer. A study was made to examine the effects of sand burial at different levels of 0 (control), 33%, 67%, 100% and 133% of their shoot height, on the survivorship, growth, and biomass allocation pattern of H. laeve seedlings (one and two weeks old after emergence). When burial depth was up to 100% of their shoot height, about 70% seedlings died; and the burial at depth of 133% of their shoot height led to death of all seedlings. When seedlings was buried at depth of 33% and 67% of their shoot height, respectively, after six_week growth, their biomass of whole plant, blade, and root and relative growth rate were higher than the unburied counterparts. The seedlings in both 33% and 67% sand burial treatments did not significantly change their biomass allocation pattern comparing with the unburied ones. Furthermore, the number of leaves and shoot height of the seedlings in both 33% and 67% sand burial treatments were not significantly different from those of unburied individuals, respectively. The newly born leaves of the surviving seedlings, in 33%, 67%, and 100% burial treatments, during the period of experiment, were significantly more than those in control.

Assessment of Climate for Agricultural Suitability and Optimal Allocation of Agricultural Production in the Guanzhong Region, Shaanxi Province

Based on spatial climatic data of agriculture and the experiment data, the models of agro-ecological assessment of climate for agricultural suitability in this study were developed using the fuzzy mathematical method. Three coefficients, in- cluding the resource coefficient （Cr）, the efficiency coefficient （Ce）, and the utility co- efficient （K）, were used in the models, which were calculated based on temperature, moisture, and sunshine duration data of Guanzhong region, Shaanxi Province. The results indicated that resource coefficient was higher in west of the region than that in east, and higher in south （especially in the Central Shaanxi Plain） than that in the Weibei plateau. The value of Cr changed from 6.5 to 9.2 from north to plain area. Spatial change of efficiency coefficient was obvious, lower in the northeast than in the central plain, and the value of Ce changed from 2.3 to 6.5 from the northeast to the central plain. As for utility coefficient, it was lower in northeastern part of the Weibei plateau and in southern mountain areas than that in the central plain, showing significant latitudinal zonality. Furthermore, the value of K increased from 0.35 to 0.78 from northeast to the central plain, and decreased from 0.78 to 0.53 from the central plain to southern mountain areas. These indicated that climate resource in the central plain region was more abundant and potential, compared with other regions. GuanZhong region was classified into three larger agricultural zones and three small independent zones, according to agro-ecological assessment. Light, heat and water resources should be made use of in an efficient way in spatial allo- cation of agricultural production. For example, water facilities should also be im- proved in Weibei plateau region where highly-qualified fruit should be enhanced and fruit processing industrial chain should be shaped. Large-scale production area of wheat should be increased in central irrigation region and more vegetable bases should be developed around large and medium-scale cities. Thanks for outstanding water conservation function, the three-dimensional agriculture including medicine and other sideline production should be developed in Qinling Mountains and the special- ized commercial agriculture should be accelerated in independent small zones, ac- cording to local conditions. In the research, different crop varieties were developed in corresponding regions as per current eco-climatic conditions.

Optimized Allocation Model for Regional Agricultural Fertilizer Resources in Southern Xinjiang from the Perspective of Sustainable Development

[Objective] This study was to establish an optimized model for the allocation of agricultural fertilizer resources in Southern Xinjiang from the perspective of sustainable development.[Method] An optimized model for the allocation of agricultural fertilizer resources was established based on their allocation structure.Combined with the actual agricultural production in Aksu areas of Southern Xinjiang,by establishing a rational evaluation index system,under the premise of considering the planting area constraints,the total water resources constraints and the security constraints of food production,we established the empirical optimal allocation model of the regional agricultural fertilizer resources in Aksu area of Southern Xinjiang.Moreover,we solved the model by using the search algorithm of computer and lingo programming.[Result] The increased economic benefit was near to 1.8 billion Yuan by adopting the optimal allocation methods,with a relative increment of about 34.4%.[Conclusion] Our results provided theoretical basis for achieving the sustainable development of agricultural economy in Southern Xinjiang.

Resource allocation based on fairness and QoS provisioning for OFDMA-WLAN system

To satisfy different service requirements of multiple users in the orthogo nal frequency division multiple access wireless local area network OFDMA-WLAN system downlink transmission a resource allocation algorithm based on fairness and quality of service QoS provisioning is proposed. Different QoS requirements are converted into different rate requirements to calculate the QoSs atisfaction level.The optimization object is revised as a fairness-driven resource optimization function to provide fairness. The complex resource allocation problem is divided into channel allocation and power assignment sub-problems. The sub-problems are solved by the bipartite graph matching and water-filling based method.Compared with other algorithms the proposed algorithm sacrifices less data rate for higher fairnes and QoS satisfaction.The sim ulation results show that the proposed algorithm is capableo fp rovi ding QoS and fairness and performs better in a tradeoff among QoS fairness and data rate.

The Operation Mechanism of Agricultural Products Supply Chain and Profit Allocation Model in the Context of Asymmetric Information

The research performed analysis on causes of asymmetric information of agricultural product supply chain and made conclusion on operation mechanism and characteristics of supply chain based on asymmetric information. Finally, the research detailed profit sharing of agricultural product supply chain in the context of asymmetric information and proposed suggestions, providing references of pricing and profit sharing of supply chains of agricultural products.

Dynamic software allocation algorithm for saving power in pervasive computing

A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communication and migration of software components, a power consumption model of component assignments between a mobile device and a server is set up. Also, the mobility of components and the mobility relationships between components are taken into account in software allocation. By using network flow theory, the optimization problem of power conservation is transformed into the optimal bipartition problem of a flow network which can be partitioned by the max-flow rain-cut algorithm. Simulation results show that the proposed algorithm can save si^nificantlv more energy than existing algorithms.

Qo E-based resource allocation protocols in cognitive OFDMA network with hybrid model

A resource allocation protocol is presented in an orthogonal frequency division multiple access （OFDMA） cognitive radio （CR） network with a hybrid model which combines overlay and underlay models. Without disrupting the primary user （PU） transmissions, the overlay model allows the secondary user （SU） to utilize opportunistically the idle sub-channels; the underlay model allows the SU to occupy the same sub-channels with PU. The proposed protocols are designed for maximizing the quality of experience （QoE） of CR users and switching dynamically between the overlay and underlay models. QoE is measured by the mean opinion score （MOS） rather than simply fulfilling the physical and medium access control （MAC） layer requirements. The simulations considering the file transfer and video stream services show that the proposed resource allocation strategy is spectrum efficient.

Quantitative Allocation Analysis of "Raising by Planting" System Combining Fruits and Poultry for Mountainous Region in Headwaters of Dongjiang River

[Objective] The aim was to promote nutrient cycling and utilization in the mountain＇s system combining fruits and poultry and to control non-point source pollution produced from swine raising and navel orange planting in headwaters of Dongjiang River. [Method] The quantitative analysis was mainly conducted for the so called ＂raising by planting＂ which is about material cycle in ＂pig-methane-fruit-fish＂ model and energy cascade utilization, based on relationship between excreted amount by livestock and the utilized quantity in Xinlin Farm in Longtang Town, Dingnan County, Jiangxi Province. [Result] Considering N requirement by fruit trees, a navel orange orchard （1 mu） could support about 2.72 pigs, the equipped biogas pool （1.88 m3） could support 1 166.67 kg of duckweeds and a fish pond could support 25.57 grass carps. In contrast, a satsuma orchard （1 mu） could support about 1.96 pigs, the equipped biogas pool （1.35 m3） could support 841.53 kg duckweeds and the fish pond could support 18.44 grass carps. [Conclusion] The results provided scientific references for quantitative allocation of members in ＂pig-methane-fruit-fish＂ model when popularized in headwaters of Dongjiang River.

Optimal subcarrier allocation for cognitive radio with multi-user OFDM and distributed antenna

The subcarrier allocation problem in cognitive radio（CR）networks with multi-user orthogonal frequency-division multiplexing（OFDM）and distributed antenna is analyzed and modeled for the flat fading channel and the frequency selective channel,where the constraint on the secondary user（SU）to protect the primary user（PU）is that the total throughput of each PU must be above the given threshold instead of the ＂interference temperature＂.According to the features of different types of channels,the optimal subcarrier allocation schemes are proposed to pursue efficiency（or maximal throughput）,using the branch and bound algorithm and the 0-1 implicit enumeration algorithm.Furthermore,considering the tradeoff between efficiency and fairness,the optimal subcarrier allocation schemes with fairness are proposed in different fading channels,using the pegging algorithm.Extensive simulation results illustrate the significant performance improvement of the proposed subcarrier allocation schemes compared with the existing ones in different scenarios.