Non-orthogonal multiple access(NOMA)technique is an expert on channel differences exploiting.In this paper,a dual-hop NOMA-based cooperative relaying network where a best relay is selected as an active node to accompl...Non-orthogonal multiple access(NOMA)technique is an expert on channel differences exploiting.In this paper,a dual-hop NOMA-based cooperative relaying network where a best relay is selected as an active node to accomplish the communication between a source and a destination is discussed.We assume that both decode-and-forward(DF)and amplify-and-forward(AF)protocols are applied to the selected relay.The metrics that ergodic sum-rate and outage probability are investigated,and the closed-form expressions of the latter for DF and AF protocols are derived.Numerical and simulation results are conducted to verify the validity of the theoretical analysis,in which we can see that the NOMA based DF relaying is better than the NOMA based AF relaying and other existing NOMA-based cooperative communication schemes.展开更多
Even though various wireless Net- work Access Technologies （NATs） with dif- ferent specifications and applications have been developed in the recent years, no single wireless technology alone can satisfy the any- ti...Even though various wireless Net- work Access Technologies （NATs） with dif- ferent specifications and applications have been developed in the recent years, no single wireless technology alone can satisfy the any- time, anywhere, and any service wire- less-access needs of mobile users. A real seamless wireless mobile environment is only realized by considering vertical and horizontal handoffs together. One of the major design issues in heterogeneous wireless networks is the support of Vertical Handoff （VHO）. VHO occurs when a multi-interface enabled mobile terminal changes its Point of Attachment （PoA） from one type of wireless access technology to another, while maintaining an active session. In this paper we present a novel multi-criteria VHO algorithm, which chooses the target NAT based on several factors such as user preferences, system parameters, and traf- tic-types with varying Quality of Service （QoS） requirements. Two modules i.e., VHO Neces- sity Estimation （VHONE） module and target NAT selection module, are designed. Both modules utilize several ＂weighted＂ users＇ and system＇s parameters. To improve the robust- ness of the proposed algorithm, the weighting system is designed based on the concept of fuzzy linguistic variables.展开更多
Artificial immune systems （AIS） are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clona...Artificial immune systems （AIS） are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clonal selection algorithm, to solve the multi-user detection problem in code-division multipleaccess communications system based on the maximum-likelihood decision rule. Through proportional cloning, hypermutation, clonal selection and clonal death, the new method performs a greedy search which reproduces individuals and selects their improved maturated progenies after the affinity maturation process. Theoretical analysis indicates that the clonal selection algorithm is suitable for solving the multi-user detection problem. Computer simulations show that the proposed approach outperforms some other approaches including two genetic algorithm-based detectors and the matched filters detector, and has the ability to find the most likely combinations.展开更多
We investigate the resource allocation problem of a cell-free massive multiple-input multiple-output system under the condition of colluding eavesdropping by multiple passive eavesdroppers.To address the problem of li...We investigate the resource allocation problem of a cell-free massive multiple-input multiple-output system under the condition of colluding eavesdropping by multiple passive eavesdroppers.To address the problem of limited pilot resources,a scheme is proposed to allocate the pilot with the minimum pollution to users based on access point selection and optimize the pilot transmission power to improve the accuracy of channel estimation.Aiming at the secure transmission problem under a colluding eavesdropping environment by multiple passive eavesdroppers,based on the local partial zero-forcing precoding scheme,a transmission power optimization scheme is formulated to maximize the system’s minimum security spectral efficiency.Simulation results show that the proposed scheme can effectively reduce channel estimation error and improve system security.展开更多
Fog Radio Access Networks(F-RANs)have been considered a groundbreaking technique to support the services of Internet of Things by leveraging edge caching and edge computing.However,the current contributions in computa...Fog Radio Access Networks(F-RANs)have been considered a groundbreaking technique to support the services of Internet of Things by leveraging edge caching and edge computing.However,the current contributions in computation offloading and resource allocation are inefficient;moreover,they merely consider the static communication mode,and the increasing demand for low latency services and high throughput poses tremendous challenges in F-RANs.A joint problem of mode selection,resource allocation,and power allocation is formulated to minimize latency under various constraints.We propose a Deep Reinforcement Learning(DRL)based joint computation offloading and resource allocation scheme that achieves a suboptimal solution in F-RANs.The core idea of the proposal is that the DRL controller intelligently decides whether to process the generated computation task locally at the device level or offload the task to a fog access point or cloud server and allocates an optimal amount of computation and power resources on the basis of the serving tier.Simulation results show that the proposed approach significantly minimizes latency and increases throughput in the system.展开更多
基金supported in part by the National Natural Science Foundation of China under Grants 61971149,61431005,and 61971198in part by the Natural Science Foundation of Guangdong Province under Grant 2016A030308006+1 种基金in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2019A1515011040in part by the Young Innovative Talents Project of Guangdong Province under Grant 2018GkQNCX118.
文摘Non-orthogonal multiple access(NOMA)technique is an expert on channel differences exploiting.In this paper,a dual-hop NOMA-based cooperative relaying network where a best relay is selected as an active node to accomplish the communication between a source and a destination is discussed.We assume that both decode-and-forward(DF)and amplify-and-forward(AF)protocols are applied to the selected relay.The metrics that ergodic sum-rate and outage probability are investigated,and the closed-form expressions of the latter for DF and AF protocols are derived.Numerical and simulation results are conducted to verify the validity of the theoretical analysis,in which we can see that the NOMA based DF relaying is better than the NOMA based AF relaying and other existing NOMA-based cooperative communication schemes.
文摘Even though various wireless Net- work Access Technologies （NATs） with dif- ferent specifications and applications have been developed in the recent years, no single wireless technology alone can satisfy the any- time, anywhere, and any service wire- less-access needs of mobile users. A real seamless wireless mobile environment is only realized by considering vertical and horizontal handoffs together. One of the major design issues in heterogeneous wireless networks is the support of Vertical Handoff （VHO）. VHO occurs when a multi-interface enabled mobile terminal changes its Point of Attachment （PoA） from one type of wireless access technology to another, while maintaining an active session. In this paper we present a novel multi-criteria VHO algorithm, which chooses the target NAT based on several factors such as user preferences, system parameters, and traf- tic-types with varying Quality of Service （QoS） requirements. Two modules i.e., VHO Neces- sity Estimation （VHONE） module and target NAT selection module, are designed. Both modules utilize several ＂weighted＂ users＇ and system＇s parameters. To improve the robust- ness of the proposed algorithm, the weighting system is designed based on the concept of fuzzy linguistic variables.
基金Supported by the National Natural Science Foundation of China (Grant Nos. 60703107, 60703108)the National High-Tech Research & Develop-ment Program of China (Grant No. 2009AA12Z210)+1 种基金the Program for New Century Excellent Talents in University (Grant No. NCET-08-0811)the Program for Cheung Kong Scholars and Innovative Research Team in University (Grant No. IRT-06-45)
文摘Artificial immune systems （AIS） are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clonal selection algorithm, to solve the multi-user detection problem in code-division multipleaccess communications system based on the maximum-likelihood decision rule. Through proportional cloning, hypermutation, clonal selection and clonal death, the new method performs a greedy search which reproduces individuals and selects their improved maturated progenies after the affinity maturation process. Theoretical analysis indicates that the clonal selection algorithm is suitable for solving the multi-user detection problem. Computer simulations show that the proposed approach outperforms some other approaches including two genetic algorithm-based detectors and the matched filters detector, and has the ability to find the most likely combinations.
基金supported by the National Natural Science Foundation of China(Nos.62071485,61671472,and 62271503)the Natural Science Foundation of Jiangsu Province,China(Nos.20201334 and 20181335)。
文摘We investigate the resource allocation problem of a cell-free massive multiple-input multiple-output system under the condition of colluding eavesdropping by multiple passive eavesdroppers.To address the problem of limited pilot resources,a scheme is proposed to allocate the pilot with the minimum pollution to users based on access point selection and optimize the pilot transmission power to improve the accuracy of channel estimation.Aiming at the secure transmission problem under a colluding eavesdropping environment by multiple passive eavesdroppers,based on the local partial zero-forcing precoding scheme,a transmission power optimization scheme is formulated to maximize the system’s minimum security spectral efficiency.Simulation results show that the proposed scheme can effectively reduce channel estimation error and improve system security.
文摘Fog Radio Access Networks(F-RANs)have been considered a groundbreaking technique to support the services of Internet of Things by leveraging edge caching and edge computing.However,the current contributions in computation offloading and resource allocation are inefficient;moreover,they merely consider the static communication mode,and the increasing demand for low latency services and high throughput poses tremendous challenges in F-RANs.A joint problem of mode selection,resource allocation,and power allocation is formulated to minimize latency under various constraints.We propose a Deep Reinforcement Learning(DRL)based joint computation offloading and resource allocation scheme that achieves a suboptimal solution in F-RANs.The core idea of the proposal is that the DRL controller intelligently decides whether to process the generated computation task locally at the device level or offload the task to a fog access point or cloud server and allocates an optimal amount of computation and power resources on the basis of the serving tier.Simulation results show that the proposed approach significantly minimizes latency and increases throughput in the system.
