Dynamic resource allocation scheme for multiuser OFDM–UWB systems based on user's rate by Chao CHENG, Zhi-hong QIAN, Chun-lan LI, Xue WANG

“…According to original dynamic resource allocation algorithms,a new dynamic resource allocation algorithm for multiuser OFDM-UWB system based on users'rates was proposed to minimize the total transmitting power whil sa-tisfy requests for QoS and data rate of all users.Qual ty of the system was improved running the subcarrier allocation and bit allocation algorithms based on fairness of users.In subcarrier allocation process,rate impact factor was used to com-pare influence of different subcarriers to a user.In allocation process,bits were allocated to each user's subcarriers first,then bits on each subcarriers were adjusted according to rate request of each user.In or to reduce the complexity system of the furthermore,a subcarrier and bit allocation scheme is employed through subcarrier grouping.Simulation results indicate that the algorithm can lower power consume,BER and operation complexity.…”
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Service aware base station processing resource allocation for centralized radio access network by Xinping ZHANG, Yuanyuan WANG, Lin TIAN, Shuliang HAO

“…Current research on resource allocation algorithmsmainly focuses on data centers,and cloud computing environments.These resource allocation algorithms did not consideRthe diversity of processing resources(CPU,memory,network bandwidth,FPGA,DSP)and the diversity of service types in the centralized base station,resulting in the low processing resource utilization.In ordeRto solve this problem,a service oriented base station processing resource allocation algorithm was proposed.Firstly,the Fisher partitionmethod was used to classify the base station’s processing resource requirements according to the user’s service request.Then,the resource allocation balancing strategy was used to allocate the base station processing resources.Experimental results show that the algorithm is effective to reduce the number of physi cal servers and improves the resource utilization of the servers,realizing energy conservation and communications.…”
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Cross-layer scheduling and dynamic resource allocation for MIMO-OFDMA/SDMA systems with multi-service by ZHONG Chong-xian1, LI Chun-guo1, YANG Lv-xi1

“…Cross-layer scheduling and dynamic resource allocation problems were investigated for downlink MIMO-OFDMA/SDMA systems with multi-service.Firstly,a mathematical formulation of the optimization problem was provided with the objective of maximizing the total system throughput under various constraints.Secondly,a user group-ing scheme was proposed utilizing clustering analysis method based on the type of services and the spatial compatibility of multiple users with multiple receive antennas.Thirdly,a new cross-layer scheduling and dynamic resource allocation algorithm was developed based on the proposed user grouping scheme combined with the priorities of different service,which maximizes the total system throughput by maximizing the throughput of each subcarrier.Simulation results show that compared with the existing schemes,the proposed algorithms obtain reasonable throughput performance while provide better QoS requirement for each user of different services.…”
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Adaptive resource allocation in multiuser OFDM system based on fairness threshold by ZHANG Chun-fa, ZHAO Xiao-hui

“…In traditional sub-carrier allocation process,user with the highest priority can choose best sub-carrier,which will result in low utilization of sub-carriers.Current improved algorithms can im-prove system capacity and reduce algorithm complexity by sacrificing certain fairness,but they may not achieve fairness requirement among users.In order to solve this problem,a new adaptive resource allo-cation algorithm based on fairness threshold was proposed,in which the priority of the sub-carrier allo-cation was determined by fairness threshold to achieve a rough tradeoff between capacity and fairness.Then power allocation base on particle swarm optimization（PSO） was introduced to realize the required fairness.Experimental results show that the proposed adaptive resource allocation algorithm can satisfy the fairness requirement threshold and improve system capacity.…”
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Joint Radio Resource Allocation and Base Station Location Selection in OFDMA Based Private Wireless Access Networks for Smart Grid by Peng Du, Yuan Zhang

“…Specifically, the combination of power control based resource allocation algorithm and PSO based location selection algorithm is recommended.…”
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Deep reinforcement learning-based resource joint optimization for millimeter-wave massive MIMO systems by LIU Qingli, LI Xiaoyu, LI Rui

“…Experimental results show that the proposed joint optimization method significantly improves the throughput and energy efficiency of the system compared with the single-stage all-digital precoding and hybrid precoding equal resource allocation methods and the particle swarm optimization-based resource allocation algorithm.…”
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A Stackelberg game based content caching algorithm in energy-harvesting small cell networks by Xueting WANG, Qi ZHU, Han HU

“…To improve the users' satisfaction of download files, a caching based resource allocation algorithm in energy-harvesting small cell networks was proposed, which was established as a Stackelberg game that jointly optimized user accessing and small cells' content updating. …”
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Multi-values discrete particle swarm optimization for cross layer resource allocation in cooperative OFDMA systems by Wei LI, Chun-lin XIONG, De-gang WANG, Xiao-ying ZHANG, Ji-bo WEI

“…In order to maximize the sum utility of all MS under per-relay power constraint(PPC), an asymptotic optimal resource allocation algorithm based on multi-values discrete particle swarm optimization (MDPSO) was pro-posed. …”
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Secure communication approach for Internet of things based on C-RAN fronthaul compression by Yong WANG, Mu ZHOU, Zengshan TIAN, Jinjun WU

“…A resource allocation algorithm was proposed for downlink C-RAN secure communication system.This algorithm jointly optimized the parameters of base station (BS) mode,quantized noise and beamforming under the constraints of SINR requirements of Internet of things information receiver,eavesdropped receiver and fronthaul link capacity.Such a design was a non-convex optimization problem,and a step-by step optimization algorithm was proposed to decompose the original optimization problem efficiently.Semi-definite technique and function smoothing approach were adopted,and the local optimization solution of the original problem was obtained by the iterative different of convex method.Bi-section approach was further proposed to determine BS mode,and the transmitting power of the BSs were finally optimized.Simulation results indicate that the proposed joint optimization algorithm achieves better performance than group sparse optimization algorithm and baseline algorithm,and it has approximate optimal performance as the exhaustive search algorithm.…”
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Dual time scale network slicing algorithm based on D3QN for B5G multi-service scenarios by Geng CHEN, Shuhu QI, Fei SHEN, Qingtian ZENG

“…To effectively meet the differentiated quality of service (QoS) requirements of different slices, a dual time scale network slicing resource allocation algorithm based on dueling double DQN (D3QN) was proposed for B5G multi-service scenarios.The joint resource slicing and scheduling problem was formulated, with the weighted sum of the normalized spectral efficiency (SE) and the QoS of users indices of different slices as the optimization objective.On large time scale, the SDN controller used the D3QN algorithm to pre-allocate resources to different slices based on the resource requirements of each service, and then performed BS-level resource updating based on the load status of BS.On small time scale, the BS scheduled resources to end-users by using the round-robin scheduling algorithm.The simulation results show that the proposed algorithm has excellent performance in ensuring the QoS requirements of slice users, SE and system utility.Compared with the other 4 baseline algorithms, the system utility is improved by 3.22%, 3.81%, 7.48% and 21.14%, respectively.…”
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Opportunistic spectrum sharing protocol and optimal resource allocation based on OFDM cooperation relaying by Wei-dang LU, Xuan-li WU, Xue-jun SHA, Nai-tong ZHANG

“…An opportunistic spectrum sharing protocol based on OFDM cooperation relaying was proposed.When the primary user experiences weak channel conditions,it could not achieve its target rate.If the cognitive user could help the primary user achieve its target rate,it accessed the pectrum of the primary user in the cooperation way.In this access way,the cognitive user used a fraction of the subcarriers to amplify-and-forward the signal of the primary user,to help the primary user achieve its target rate.And uses the remained subcarriers to transmit its own signal.The resource allocation was analyzed in this cooperation way.An optimal resource allocation algorithm based on dual ethod was proposed,which maximized the rate of the cognitive user while g anteeing the primary user achieve its target rate.If the cognitive user could not help the primary user achieve its target rate,to make use the spectrum efficiently,the cognitive user accessed the spectrum of the primary user in the non-cooperation way,and uses the whole accessed spectrum to transmit its own signal.The simulation demonstrates the efficiency of the proposed spectrum sharing protocol as well as its benefit to both primary and cognitive user.…”
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Resource allocation strategies for improved mayfly algorithm in cognitive heterogeneous cellular network by Damin ZHANG, Yi WANG, Chengcheng ZOU, Peiwen ZHAO, Linna ZHANG

“…Aiming at the optimization of uplink resource allocation in cognitive heterogeneous cellular networks, a resource allocation algorithm based on improved discrete mayfly algorithm was proposed.In the cognitive heterogeneous cellular network model, the power control strategy was introduced to control the interference suppression of transmitted power, and the improved discrete mayfly algorithm was used to optimize and solve the optimal distribution scheme based on the user’s quality of service (QoS) requirements and interference threshold constraints to maximize the energy efficiency (EE).In order to improve the convergence rate and search ability of the mayfly algorithm, the dynamic adaptive weights of incomplete Gamma and Beta distribution functions and the golden sine position updating strategy were introduced.The simulation results show that the closed-loop power control based on SINR can dynamically adjust the transmitting power of users and effectively restrain the interference between users.The GSWBMA has good optimization efficiency and convergence performance to solve the resource allocation problem, effectively improve the energy efficiency of the system and the transmission rate of users, and ensure the QoS requirements of users.…”
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Study on multi-satellite cooperative spectrum cognitive method integrating Stackelberg game and federated learning by Xiaojin DING, Yehui XU, Wen BAO, Gengxin ZHANG

“…To solve the problem of the weak spectrum-cognitive ability caused by monitoring angle, direction resolution, limited processing ability and peak power for a low-earth-orbit (LEO) satellite, a multi-satellite cooperative spectrum cognitive method integrating Stackelberg game and federated learning was proposed.Firstly, considering the available computing resource, cognitive performance, processing and transmission delay of each spectrum cognitive satellite, a cooperative-satellite selection and computing-resource allocation algorithm was built for multiple spectrum-cognitive tasks.Secondly, based on the selected satellites and the allocated computing resources, a low-complexity multi-satellite cooperative spectrum cognitive strategy was further designed, which could automatically sense the spectrum holes, and detect interference as well as identify the modulation mode.Simulation results demonstrate that compared to the single-node cognitive method, the designed multi-satellite cooperative spectrum cognitive strategy can obtain a better cognitive performance.Moreover, comparing with the existing model, the model utilized in the designed strategy can effectively achieve 96.69% and 93.32% lower number of parameters and required floating point operations per second, whilst maintaining the performance.…”
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Optimal resource allocation for two-stage connectionless access with collision detection by Xin JIAN, Fang WANG, Jian SONG, Shu FU, Xiaoheng TAN, Xiaoping ZENG

“…Connectionless access allows massive machine type communication (mMTC) devices to transmit small packets without establishment of radio bearers,significantly reducing device power consumption and control signaling overhead.Two-stage connectionless access (TSCLA) improves throughput and resource efficiency by optimally allocating resources between scheduling request (SR) phase and data transmission phase,which can be used for bigger packets and high traffic load.Based on this,a comprehensive theoretical analysis of one kind of TSCLA with collision detection was conducted to investigate its performance limit and devise its optimal resource allocation scheme.In addition,to avoid the complexity of user number estimation,a dynamic resource allocation algorithm with feedback control was proposed.Numerical results are provided to validate the effectiveness of aforementioned theoretical results and show that comparing with the genie aided algorithm known exactly the number of users,the performance loss of the proposed algorithm is within 4%.These works together provide good references for appropriate resource dimensioning for mMTC related protocols.…”
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A Multiconstrained Grid Scheduling Algorithm with Load Balancing and Fault Tolerance by P. Keerthika, P. Suresh

“…This work attempts to design a resource allocation algorithm which is budget constrained and also targets load balancing, fault tolerance, and user satisfaction by considering the above requirements. …”
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Energy-Efficient Resource Allocation in Uplink Multiuser Massive MIMO Systems by Ying Hu, Baofeng Ji, Yongming Huang, Fei Yu, Luxi Yang

“…By transforming the originally fractional optimization problem into an equivalent subtractive form using the properties of fractional programming, we develop another efficient iterative resource allocation algorithm. Simulation results have validated the effectiveness of the proposed two algorithms and have shown that both algorithms can fast converge to a near-optimal solution in a small number of iterations.…”
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Flexible beam scheduling and resource allocation strategies for satellite Internet of things by LI Fulin, WANG Jingchao, DONG Yanjie, WANG Wei, MA Xiao

“…The beam scheduling algorithm based on separated swarm optimization (SSO-BSA) was proposed to solve the flexible beam pointing coordinates, and an on-demand resource allocation algorithm based on service value degree (ORAA-SVD) was designed to provide flexible resource allocation for beams and IoT terminals. …”
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Network slicing resource allocation strategy based on joint optimization by Zaijian WANG, Huimin GU

“…To improve network resource utilization that was decreased by different applications with different requirements in 5G networks, a network slicing resource allocation strategy based on joint optimization was proposed, which was utilized to maximize both network resource utilization and network revenue by comprehensively considering in tra-slice and inter-slice resource schedule.Firstly, the user’s average satisfaction function was defined in the inter-slicing resource allocation problem.Furthermore, in terms of the number of users, slicing schedule delay and priority, a proportional fair resource allocation algorithm based on quality of service (QoS) was proposed, which was employed to achieve the best tradeoff between fairness and the users’ requirements among slices.Secondly, after two functions (service degradation and resource migration) were introduced in the inter-slice resource schedule problem, two price models were established for internal access users and external access users respectively, where congestion and non-congestion conditions were analyzed.According to the proposed price models, a Stackelberg game between the base station and users was constructed, and a global search algorithm with low complexity was leveraged to obtain the best response of the game, where the best tradeoff between the base station revenue and user utility was obtained.Simulation results show that the proposed strategy can effectively improve resource utilization and network revenue while reducing network congestion.Therefore, it can better realize fairness in resource allocation.…”
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Cloud edge end network resource allocation for thermostatically controlled load aggregation regulation by Yi LIU, Xin WU

“…Thermostatically controlled load is a flexible load that controls temperature regulation, such as air conditioning and electric water heaters.As a crucial demand side resource, flexible aggregation and regulation of load clusters can fully mobilize clean energy consumption capacity and ensure the balance between supply and demand of the power grid.Due to the common occurrence of thermostatically controlled loads in commercial office buildings and residential areas, a relatively stable control and transmission method can be adopted.Therefore, an efficient hierarchical transmission network is introduced to achieve data transmission and information interaction between loads and the power grid, and to flexibly, real-time, and accurately utilize the adjustable potential of load clusters.Firstly, an information interaction architecture of load IoT which structured “central cloud-edge cloud-regional load controller-thermostatically controlled load”was proposed.Then, for the “end edge”part, considering the requirements of different aggregation control tasks, an improved clustering algorithm was used to classify the tasks and reduce transmission overhead.For the “end-side” part, an improved clustering algorithm was used to optimize the transmission distance.For the edge-cloud collaboration part, a subchannel resource allocation algorithm was designed based on stable matching and water injection algorithms.The binary particle swarm optimization algorithm was used to solve the task upload decision problem.Finally, the effectiveness of the proposed model and algorithm is verified through simulation, and comparative experiments are also conducted.…”
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Adaptive Computing Resource Allocation for Mobile Cloud Computing by Hongbin Liang, Tianyi Xing, Lin X. Cai, Dijiang Huang, Daiyuan Peng, Yan Liu

“…Extensive simulations are conducted to demonstrate that our proposed model can achieve higher system reward and lower service blocking probability compared to traditional approaches based on greedy resource allocation algorithm. Performance comparisons with various MCC resource allocation schemes are also provided.…”
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