In Beyond the Fifth Generation(B5G)heterogeneous edge networks,numerous users are multiplexed on a channel or served on the same frequency resource block,in which case the transmitter applies coding and the receiver u...In Beyond the Fifth Generation(B5G)heterogeneous edge networks,numerous users are multiplexed on a channel or served on the same frequency resource block,in which case the transmitter applies coding and the receiver uses interference cancellation.Unfortunately,uncoordinated radio resource allocation can reduce system throughput and lead to user inequity,for this reason,in this paper,channel allocation and power allocation problems are formulated to maximize the system sum rate and minimum user achievable rate.Since the construction model is non-convex and the response variables are high-dimensional,a distributed Deep Reinforcement Learning(DRL)framework called distributed Proximal Policy Optimization(PPO)is proposed to allocate or assign resources.Specifically,several simulated agents are trained in a heterogeneous environment to find robust behaviors that perform well in channel assignment and power allocation.Moreover,agents in the collection stage slow down,which hinders the learning of other agents.Therefore,a preemption strategy is further proposed in this paper to optimize the distributed PPO,form DP-PPO and successfully mitigate the straggler problem.The experimental results show that our mechanism named DP-PPO improves the performance over other DRL methods.展开更多
This paper studies a dual-hop Simultaneous Wireless Information and Power Transfer(SWIPT)-based multi-relay network with a direct link.To achieve high throughput in the network,a novel protocol is first developed,in w...This paper studies a dual-hop Simultaneous Wireless Information and Power Transfer(SWIPT)-based multi-relay network with a direct link.To achieve high throughput in the network,a novel protocol is first developed,in which the network can switch between a direct transmission mode and a Single-Relay-Selection-based Cooperative Transmission(SRS-CT)mode that employs dynamic decode-and-forward relaying accomplished with Rateless Codes(RCs).Then,under this protocol,an optimization problem is formulated to jointly optimize the network operation mode and the resource allocation in the SRS-CT mode.The formulated problem is difficult to solve because not only does the noncausal Channel State Information(CSI)cause the problem to be stochastic,but also the energy state evolution at each relay is complicated by network operation mode decision and resource allocation.Assuming that noncausal CSI is available,the stochastic optimization issue is first to be addressed by solving an involved deterministic optimization problem via dynamic programming,where the complicated energy state evolution issue is addressed by a layered optimization method.Then,based on a finite-state Markov channel model and assuming that CSI statistical properties are known,the stochastic optimization problem is solved by extending the result derived for the noncausal CSI case to the causal CSI case.Finally,a myopic strategy is proposed to achieve a tradeoff between complexity and performance without the knowledge of CSI statistical properties.The simulation results verify that our proposed SRS-and-RC-based design can achieve a maximum of approximately 40%throughput gain over a simple SRS-and-RC-based baseline scheme in SWIPT-based multi-relay networks.展开更多
A new acknowledgment-type slotted-ALOHA code division multiple access （ACK-ALOHA-CDMA） channel which can be used in the inbound channels of very small aperture terminal（VSAT） networks is proposed in order to simpl...A new acknowledgment-type slotted-ALOHA code division multiple access （ACK-ALOHA-CDMA） channel which can be used in the inbound channels of very small aperture terminal（VSAT） networks is proposed in order to simplify the synchronization equipment of networks in the slotted-ALOHA- CDMA systems. By dividing all VSAT stations into M subsystems and sending out periodic inquiry signals from the Hub station to the VSAT station, the channel model is established. By the means of deriving multi-access interference（MAI） and packet detecting probability, steady-state throughput is calculated. By applying diffusion process theory to the analysis of the stability of the ACK-ALOHA-CDMA channel, the drift parameter a（r）, the diffusion parameter b（r） and the steady transition probability density p （r） are investigated. Simulation results indicate that significant performance improvement and high-bandwidth efficiency can be gained and one or two steady equilibrium points can be obtained by using this channel. Consequently, the ACK- ALOHA-CDMA channel is very suitable for cutting down on the expense of satellite VSAT systems and distributed packet radio networks.展开更多
To study the throughput scheduling problem under interference temperature in cognitive radio networks, an immune algorithm-based suboptimal method was proposed based on its NP-hard feature. The problem is modeled as a...To study the throughput scheduling problem under interference temperature in cognitive radio networks, an immune algorithm-based suboptimal method was proposed based on its NP-hard feature. The problem is modeled as a constrained optimization problem to maximize the total throughput of the secondary users（ SUs）. The mapping between the throughput scheduling problems and the immune algorithm is given. Suitable immune operators are designed such as binary antibody encoding, antibody initialization based on pre-knowledge, a proportional clone to its affinity and an adaptive mutation operator associated with the evolutionary generation. The simulation results showthat the proposed algorithm can obtain about 95% of the optimal throughput and operate with much lower liner computational complexity.展开更多
基金supported by the Key Research and Development Program of China(No.2022YFC3005401)Key Research and Development Program of China,Yunnan Province(No.202203AA080009,202202AF080003)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX21_0482).
文摘In Beyond the Fifth Generation(B5G)heterogeneous edge networks,numerous users are multiplexed on a channel or served on the same frequency resource block,in which case the transmitter applies coding and the receiver uses interference cancellation.Unfortunately,uncoordinated radio resource allocation can reduce system throughput and lead to user inequity,for this reason,in this paper,channel allocation and power allocation problems are formulated to maximize the system sum rate and minimum user achievable rate.Since the construction model is non-convex and the response variables are high-dimensional,a distributed Deep Reinforcement Learning(DRL)framework called distributed Proximal Policy Optimization(PPO)is proposed to allocate or assign resources.Specifically,several simulated agents are trained in a heterogeneous environment to find robust behaviors that perform well in channel assignment and power allocation.Moreover,agents in the collection stage slow down,which hinders the learning of other agents.Therefore,a preemption strategy is further proposed in this paper to optimize the distributed PPO,form DP-PPO and successfully mitigate the straggler problem.The experimental results show that our mechanism named DP-PPO improves the performance over other DRL methods.
基金supported in part by the National Natural Science Foundation of China under Grant 61872098 and Grant 61902084the Natural Science Foundation of Guangdong Province under Grant 2017A030313363.
文摘This paper studies a dual-hop Simultaneous Wireless Information and Power Transfer(SWIPT)-based multi-relay network with a direct link.To achieve high throughput in the network,a novel protocol is first developed,in which the network can switch between a direct transmission mode and a Single-Relay-Selection-based Cooperative Transmission(SRS-CT)mode that employs dynamic decode-and-forward relaying accomplished with Rateless Codes(RCs).Then,under this protocol,an optimization problem is formulated to jointly optimize the network operation mode and the resource allocation in the SRS-CT mode.The formulated problem is difficult to solve because not only does the noncausal Channel State Information(CSI)cause the problem to be stochastic,but also the energy state evolution at each relay is complicated by network operation mode decision and resource allocation.Assuming that noncausal CSI is available,the stochastic optimization issue is first to be addressed by solving an involved deterministic optimization problem via dynamic programming,where the complicated energy state evolution issue is addressed by a layered optimization method.Then,based on a finite-state Markov channel model and assuming that CSI statistical properties are known,the stochastic optimization problem is solved by extending the result derived for the noncausal CSI case to the causal CSI case.Finally,a myopic strategy is proposed to achieve a tradeoff between complexity and performance without the knowledge of CSI statistical properties.The simulation results verify that our proposed SRS-and-RC-based design can achieve a maximum of approximately 40%throughput gain over a simple SRS-and-RC-based baseline scheme in SWIPT-based multi-relay networks.
基金The Key Laboratory Foundation of Geographical Information Science of Jiangsu Province (No.JK20050304)the Key Laboratory Foundation of Virtual Geographical Environments of Ministry of Education(No.NS206005)
文摘A new acknowledgment-type slotted-ALOHA code division multiple access （ACK-ALOHA-CDMA） channel which can be used in the inbound channels of very small aperture terminal（VSAT） networks is proposed in order to simplify the synchronization equipment of networks in the slotted-ALOHA- CDMA systems. By dividing all VSAT stations into M subsystems and sending out periodic inquiry signals from the Hub station to the VSAT station, the channel model is established. By the means of deriving multi-access interference（MAI） and packet detecting probability, steady-state throughput is calculated. By applying diffusion process theory to the analysis of the stability of the ACK-ALOHA-CDMA channel, the drift parameter a（r）, the diffusion parameter b（r） and the steady transition probability density p （r） are investigated. Simulation results indicate that significant performance improvement and high-bandwidth efficiency can be gained and one or two steady equilibrium points can be obtained by using this channel. Consequently, the ACK- ALOHA-CDMA channel is very suitable for cutting down on the expense of satellite VSAT systems and distributed packet radio networks.
基金The National Natural Science Foundation of China(No.U150461361202099+2 种基金61201175U1204618)China Postdoctoral Science Foundation(No.2013M541586)
文摘To study the throughput scheduling problem under interference temperature in cognitive radio networks, an immune algorithm-based suboptimal method was proposed based on its NP-hard feature. The problem is modeled as a constrained optimization problem to maximize the total throughput of the secondary users（ SUs）. The mapping between the throughput scheduling problems and the immune algorithm is given. Suitable immune operators are designed such as binary antibody encoding, antibody initialization based on pre-knowledge, a proportional clone to its affinity and an adaptive mutation operator associated with the evolutionary generation. The simulation results showthat the proposed algorithm can obtain about 95% of the optimal throughput and operate with much lower liner computational complexity.
