A dense heterogeneous cellular network can effectively increase the system capacity and enhance the network coverage.It is a key technology for the new generation of the mobile communication system.The dense deploymen...A dense heterogeneous cellular network can effectively increase the system capacity and enhance the network coverage.It is a key technology for the new generation of the mobile communication system.The dense deployment of small base stations not only improves the quality of network service,but also brings about a significant increase in network energy consumption.This paper mainly studies the energy efficiency optimization of the Macro-Femto heterogeneous cellular network.Considering the dynamic random changes of the access users in the network,the sleep process of the Femto Base Stations(FBSs)is modeled as a Semi-Markov Decision Process(SMDP)model in order to save the network energy consumption.And further,this paper gives the dynamic sleep algorithm of the FBS based on the value iteration.The simulation results show that the proposed SMDP-based adaptive sleep strategy of the FBS can effectively reduce the network energy consumption.展开更多
In recent times, Aerial Base Stations(AeBSs) are being investigated to provide wireless coverage to terrestrial radio terminals. There are many advantages of using aerial platforms to provide wireless coverage, includ...In recent times, Aerial Base Stations(AeBSs) are being investigated to provide wireless coverage to terrestrial radio terminals. There are many advantages of using aerial platforms to provide wireless coverage, including larger coverage in remote areas and better line-of-sight conditions, etc. Energy is a scarce resource for the AeBSs, hence the wise management of energy is quite beneficial for the aerial network. In this context, we study the means of reducing the total energy consumption by designing and implementing an energy efficient AeBSs as presented in this paper. Implementing the sleep mode in the Base Stations (BSs) has been proven to be a very good approach for improving the energy efficiency and we propose a novel strategy for further improving energy efficiency by considering ternary state transceivers for AeBSs. Using the three state model, we propose a Markov Decision Process (MDP) based algorithm, which intelligently switches among three states of the transceivers based on the offered traffic meanwhile maintaining a prescribed minimum channel rate per user. We define a reward function for the MDP, which helps us to get an optimal policy for selecting a particular mode for the transceivers of the AeBS. Considering an AeBS with transceivers whose states are changeable, we perform simulations to analyse the performance of the algorithm. Our results show that, compared with the always active model, around 40% gain in the energy efficiency is achieved by using our proposed MDP algorithm together with the three-state transceivers model. We also show the energy-delay tradeoff in order to design an efficient AeBS.展开更多
基金This work was supported by the Program for the National Science Foundation of China(61671096)the Chongqing Research Program of Basic Science and Frontier Technology(cstc2017jcyjBX0005)+1 种基金Chongqing Science and Technology Innovation Leading Talent Support Program(CSTCCXLJRC201710)Venture and Innovation Support Program for Chongqing Overseas Returnee.
文摘A dense heterogeneous cellular network can effectively increase the system capacity and enhance the network coverage.It is a key technology for the new generation of the mobile communication system.The dense deployment of small base stations not only improves the quality of network service,but also brings about a significant increase in network energy consumption.This paper mainly studies the energy efficiency optimization of the Macro-Femto heterogeneous cellular network.Considering the dynamic random changes of the access users in the network,the sleep process of the Femto Base Stations(FBSs)is modeled as a Semi-Markov Decision Process(SMDP)model in order to save the network energy consumption.And further,this paper gives the dynamic sleep algorithm of the FBS based on the value iteration.The simulation results show that the proposed SMDP-based adaptive sleep strategy of the FBS can effectively reduce the network energy consumption.
文摘In recent times, Aerial Base Stations(AeBSs) are being investigated to provide wireless coverage to terrestrial radio terminals. There are many advantages of using aerial platforms to provide wireless coverage, including larger coverage in remote areas and better line-of-sight conditions, etc. Energy is a scarce resource for the AeBSs, hence the wise management of energy is quite beneficial for the aerial network. In this context, we study the means of reducing the total energy consumption by designing and implementing an energy efficient AeBSs as presented in this paper. Implementing the sleep mode in the Base Stations (BSs) has been proven to be a very good approach for improving the energy efficiency and we propose a novel strategy for further improving energy efficiency by considering ternary state transceivers for AeBSs. Using the three state model, we propose a Markov Decision Process (MDP) based algorithm, which intelligently switches among three states of the transceivers based on the offered traffic meanwhile maintaining a prescribed minimum channel rate per user. We define a reward function for the MDP, which helps us to get an optimal policy for selecting a particular mode for the transceivers of the AeBS. Considering an AeBS with transceivers whose states are changeable, we perform simulations to analyse the performance of the algorithm. Our results show that, compared with the always active model, around 40% gain in the energy efficiency is achieved by using our proposed MDP algorithm together with the three-state transceivers model. We also show the energy-delay tradeoff in order to design an efficient AeBS.
