The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation.Sixth-Generation(6G)networks,utilizing Cognitive Radio(CR)technology within CR Network(CRN),can enhan...The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation.Sixth-Generation(6G)networks,utilizing Cognitive Radio(CR)technology within CR Network(CRN),can enhance spectrum utilization by accessing unused spectrum when licensed Primary Mobile Equipment(PME)is inactive or served by a Primary Base Station(PrBS).Secondary Mobile Equipment(SME)accesses this spectrum through a Secondary Base Station(SrBS)using opportunistic access,i.e.,spectrum sensing.Hybrid Multiple Access(HMA),combining Orthogonal Multiple Access(OMA)and Non-Orthogonal Multiple Access(NOMA),can enhance Energy Efficiency(EE).Additionally,SME Clustering(SMEC)reduces inter-cluster interference,enhancing EE further.Despite these advancements,the integration of CR technology,HMA,and SMEC in CRN for better bandwidth utilization and EE remains unexplored.This paper introduces a new CRassisted SMEC-based Downlink HMA(CR-SMEC-DHMA)method for 6G CRN,aimed at jointly optimizing SME admission,SME association,sum rate,and EE subject to imperfect sensing,collision,and Quality of Service(QoS).A novel optimization problem,formulated as a non-linear fractional programming problem,is solved using the Charnes-Cooper Transformation(CCT)to convert into a concave optimization problem,and an ε-optimal Outer Approximation Algorithm(OAA)is employed to solve the concave optimization problem.Simulations demonstrate the effectiveness of the proposed CR-SMEC-DHMA,surpassing the performance of current OMAenabled CRN,NOMA-enabled CRN,SMEC-OMA enabled CRN,and SMEC-NOMA enabled CRN methods,with ε-optimal results obtained at ε=10^(−3),while satisfying Performance Measures(PMs)including SME admission in SMEC,SME association with SrBS,SME-channel opportunistic allocation through spectrum sensing,sum rate and overall EE within the 6G CRN.展开更多
When deploying Reconfigurable Intelligent Surface(RIS)to improve System Sum-Rate(SSR),the timeliness and accuracy of SSR optimization methods are difficult to achieve simultaneously through a single algorithm.Some alg...When deploying Reconfigurable Intelligent Surface(RIS)to improve System Sum-Rate(SSR),the timeliness and accuracy of SSR optimization methods are difficult to achieve simultaneously through a single algorithm.Some algorithms focus on timeliness,while some focus on accuracy.In this paper,in order to take into account the timeliness and accuracy of the system comprehensively,we construct SSR analysis model of RIS-assisted multiuser downlink communication system and propose several new optimization methods.The goal is to maximize SSR by using the proposed algorithms to jointly optimize power allocation and reflection coefficients.To solve this comprehensive problem,two sets of Alternating Optimization(AO)-based timeliness algorithms and one set of Monotonic Optimization(MO)-based accuracy algorithms are proposed separately to jointly optimize system performance.First,the Water-Filling(WF)-based and penalty-based low complexity algorithms are developed to optimize power allocation and reflection coefficients respectively.To improve the reality of the calculation,penalty-based algorithm cleverly considers residual noise that is difficult to calculate.Then,for further improve the timeliness,a new Successive Convex Approximation(SCA)-based low complexity algorithm is designed to further optimize reflection coefficients and its convergence is proved.Third,in order to verify the effectiveness of the proposed timeliness algorithms,we further propose MO-based accuracy algorithms,in which,the Polyblock Outer Approximation(POA)algorithm,the Semidefinite Relaxation(SDR)method,and the bisection search algorithm are combined in a novel way.Numerical results confirm the timeliness of AO-based algorithms and the accuracy of MO-based algorithms.They supervise and complement each other.展开更多
In this paper, a branch-and-bound method for solving multi-dimensional quadratic 0-1 knapsack problems was studied. The method was based on the Lagrangian relaxation and the surrogate constraint technique for finding ...In this paper, a branch-and-bound method for solving multi-dimensional quadratic 0-1 knapsack problems was studied. The method was based on the Lagrangian relaxation and the surrogate constraint technique for finding feasible solutions. The Lagrangian relaxations were solved with the maximum-flow algorithm and the Lagrangian bounds was determined with the outer approximation method. Computational results show the efficiency of the proposed method for multi-dimensional quadratic 0-1 knapsack problems.展开更多
In this paper,a combined optimization of a coupled electricity and gas system is presented.For the electricity network a unit commitment problem with optimization of energy and reserves under a power pool,considering ...In this paper,a combined optimization of a coupled electricity and gas system is presented.For the electricity network a unit commitment problem with optimization of energy and reserves under a power pool,considering all system operational and unit technical constraints is solved.The gas network subproblem is a medium-scale mixed-integer nonconvex and nonlinear programming problem.The coupling constraints between the two networks are nonlinear as well.The resulting mixed-integer nonlinear program is linearized with the extended incremental method and an outer approximation technique.The resulting model is evaluated using the Greek power and gas system comprising fourteen gas-fired units under four different approximation accuracy levels.The results indicate the efficiency of the proposed mixed-integer linear program model and the interplay between computational requirements and accuracy.展开更多
文摘The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation.Sixth-Generation(6G)networks,utilizing Cognitive Radio(CR)technology within CR Network(CRN),can enhance spectrum utilization by accessing unused spectrum when licensed Primary Mobile Equipment(PME)is inactive or served by a Primary Base Station(PrBS).Secondary Mobile Equipment(SME)accesses this spectrum through a Secondary Base Station(SrBS)using opportunistic access,i.e.,spectrum sensing.Hybrid Multiple Access(HMA),combining Orthogonal Multiple Access(OMA)and Non-Orthogonal Multiple Access(NOMA),can enhance Energy Efficiency(EE).Additionally,SME Clustering(SMEC)reduces inter-cluster interference,enhancing EE further.Despite these advancements,the integration of CR technology,HMA,and SMEC in CRN for better bandwidth utilization and EE remains unexplored.This paper introduces a new CRassisted SMEC-based Downlink HMA(CR-SMEC-DHMA)method for 6G CRN,aimed at jointly optimizing SME admission,SME association,sum rate,and EE subject to imperfect sensing,collision,and Quality of Service(QoS).A novel optimization problem,formulated as a non-linear fractional programming problem,is solved using the Charnes-Cooper Transformation(CCT)to convert into a concave optimization problem,and an ε-optimal Outer Approximation Algorithm(OAA)is employed to solve the concave optimization problem.Simulations demonstrate the effectiveness of the proposed CR-SMEC-DHMA,surpassing the performance of current OMAenabled CRN,NOMA-enabled CRN,SMEC-OMA enabled CRN,and SMEC-NOMA enabled CRN methods,with ε-optimal results obtained at ε=10^(−3),while satisfying Performance Measures(PMs)including SME admission in SMEC,SME association with SrBS,SME-channel opportunistic allocation through spectrum sensing,sum rate and overall EE within the 6G CRN.
基金supported in part by Natural Science Foundation of China(92367102)in part by National Science and Technology Major Project(2024ZD1300400).
文摘When deploying Reconfigurable Intelligent Surface(RIS)to improve System Sum-Rate(SSR),the timeliness and accuracy of SSR optimization methods are difficult to achieve simultaneously through a single algorithm.Some algorithms focus on timeliness,while some focus on accuracy.In this paper,in order to take into account the timeliness and accuracy of the system comprehensively,we construct SSR analysis model of RIS-assisted multiuser downlink communication system and propose several new optimization methods.The goal is to maximize SSR by using the proposed algorithms to jointly optimize power allocation and reflection coefficients.To solve this comprehensive problem,two sets of Alternating Optimization(AO)-based timeliness algorithms and one set of Monotonic Optimization(MO)-based accuracy algorithms are proposed separately to jointly optimize system performance.First,the Water-Filling(WF)-based and penalty-based low complexity algorithms are developed to optimize power allocation and reflection coefficients respectively.To improve the reality of the calculation,penalty-based algorithm cleverly considers residual noise that is difficult to calculate.Then,for further improve the timeliness,a new Successive Convex Approximation(SCA)-based low complexity algorithm is designed to further optimize reflection coefficients and its convergence is proved.Third,in order to verify the effectiveness of the proposed timeliness algorithms,we further propose MO-based accuracy algorithms,in which,the Polyblock Outer Approximation(POA)algorithm,the Semidefinite Relaxation(SDR)method,and the bisection search algorithm are combined in a novel way.Numerical results confirm the timeliness of AO-based algorithms and the accuracy of MO-based algorithms.They supervise and complement each other.
基金Project supported by the National Natural Science Foundation of China （Grant No.10571116）
文摘In this paper, a branch-and-bound method for solving multi-dimensional quadratic 0-1 knapsack problems was studied. The method was based on the Lagrangian relaxation and the surrogate constraint technique for finding feasible solutions. The Lagrangian relaxations were solved with the maximum-flow algorithm and the Lagrangian bounds was determined with the outer approximation method. Computational results show the efficiency of the proposed method for multi-dimensional quadratic 0-1 knapsack problems.
基金funding through the DFG SFB/Transregio 154, Subprojects A05 and Z01
文摘In this paper,a combined optimization of a coupled electricity and gas system is presented.For the electricity network a unit commitment problem with optimization of energy and reserves under a power pool,considering all system operational and unit technical constraints is solved.The gas network subproblem is a medium-scale mixed-integer nonconvex and nonlinear programming problem.The coupling constraints between the two networks are nonlinear as well.The resulting mixed-integer nonlinear program is linearized with the extended incremental method and an outer approximation technique.The resulting model is evaluated using the Greek power and gas system comprising fourteen gas-fired units under four different approximation accuracy levels.The results indicate the efficiency of the proposed mixed-integer linear program model and the interplay between computational requirements and accuracy.
