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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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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A Gain-Computation Enhancements Resource Allocation for Heterogeneous Service Flows in IEEE 802.16 m Mobile Networks by Wafa Ben Hassen, Meriem Afif

“…In a single service access, we propose a dynamic resource allocation algorithm at the physical layer aiming to maximize the cell data rate while ensuring fairness among users. …”
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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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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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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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A detailed reinforcement learning framework for resource allocation in non‐orthogonal multiple access enabled‐B5G/6G networks by Nouri Omheni, Anis Amiri, Faouzi Zarai

“…Next, the Q‐Learning algorithm is used to design a resource allocation algorithm based on RL. The results of the simulation confirm that the proposed scheme is feasible and efficient.…”
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Resource allocation in cognitive radio network with energy harvesting by Yan LONG, Xiaoqian ZHANG, Xuming FANG, Rong HE

“…Considering the diversity of energy harvesting capability and spectrum sensing accuracy of SU,as well as dynamic channel quality,under the constraint of energy causality,the secondary network throughput maximization problem in single-hop cognitive radio networks with energy harvesting was studied.The transmission channel selection,transmission power control and transmission time allocation of SU were jointly optimized.Since the optimization problem was non-convex,by converting it into a series of convex optimization sub-problems,the optimize transmission power and transmission time algorithm (OPTA) was obtained.Compared with the existing resource allocation algorithms,such as,hybrid differential evolution algorithm (HDEA),optimized transmission algorithm (OTA),and random assignment channel algorithm (RA),the simulation results verify the correctness and effectiveness of the proposed algorithm.For example,under the same maximum transmission power constraint,the throughput of the proposed OPTA scheme could increase by around 6%,37% and 50% than that of HDEA,OTA and RA schemes respectively.Under the same channel gain diversity,the throughput of the proposed OPTA scheme could increase by around 30%,60% and 94% than that of HDEA,OTA and RA schemes respectively.Under the same energy harvesting efficiency diversity,the throughput of the proposed OPTA scheme could increase by around 27%,50% and 92% than that of HDEA,OTA and RA schemes respectively.…”
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Optimizing TCP Performance in Multi-AP Residential Broadband Connections via Minislot Access by Domenico Giustiniano, Eduard Goma, Alberto Lopez Toledo, George Athanasiou

“…We then introduce a simple analytical model that accurately predicts the TCP round-trip time (RTT) with a multi-AP TDMA policy and propose a resource allocation algorithm to reduce the observed TCP RTT with a very low computational cost. …”
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Energy-Efficient Resource Allocation in Mobile Edge Computing Using NOMA and Massive MIMO by Qusay Alghazali, Husam Al-Amaireh, Tibor Cinkler

“…This paper introduces a comprehensive framework for reducing energy consumption in MEC environments by leveraging advanced optimization techniques and energy-efficient resource allocation algorithms. We propose a novel approach that dynamically adjusts the computational resources based on the current network load and the type of services requested, thus minimizing unnecessary energy consumption. …”
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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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Intelligent Beam-Hopping-Based Grant-Free Random Access in Secure IoT-Oriented Satellite Networks by Zhongliang Deng, Yicheng Liao

“…This technique utilizes orthogonal resource allocation algorithms to facilitate efficient resource sharing, effectively tackling the irregular and dynamic traffic. …”
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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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Spectrum-efficient user grouping and resource allocation based on deep reinforcement learning for mmWave massive MIMO-NOMA systems by Minghao Wang, Xin Liu, Fang Wang, Yang Liu, Tianshuang Qiu, Minglu Jin

“…Moreover, a deep deterministic policy gradient (DDPG)-based power resource allocation algorithm is designed to avoid the performance loss caused by power quantization and improve the system’s achievable sum-rate. …”
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Deep Reinforcement Learning Based Joint Allocation Scheme in a TWDM-PON-Based mMIMO Fronthaul Network by Yuansen Cheng, Yingjie Shao, Shifeng Ding, Chun-Kit Chan

“…The proposed scheme couples the heuristic radio resource allocation algorithm with the RL-based wavelength allocation model to optimize the fronthaul bandwidth, radio resource, and wavelength utilization efficiencies jointly in the downstream direction. …”
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Bit Rate Optimization with MMSE Detector for Multicast LP-OFDM Systems by Ali Maiga, Jean-Yves Baudais, Jean-François Hélard

“…We propose a new resource allocation algorithm with minimum mean square error (MMSE) detector for multicast linear precoded orthogonal frequency division multiplexing (LP-OFDM) systems. …”
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A traffic-awareness dynamic resource allocation scheme based on multi-objective optimization in multi-beam mobile satellite communication systems by YuanZhi He, YiZhen Jia, XuDong Zhong

“…Additionally, it is shown that the new multi-objective programming scheme, based on the traffic-awareness dynamic resource allocation algorithm, can rapidly achieve the Pareto-front solutions and reduce the computing complexity to a large extent.…”
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Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In order to solve the mixed integer nonlinear problem (MINLP), a data offloading selection strategy based on proximity discovery and an iterative method-based resource allocation algorithm (IRA) are proposed. In addition, the closed-form solutions of the optimized variables are obtained. …”
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