With the further reduction in cost and the increase in bandwidth, as well as the increase in internet applications, satellite communications are gradually shifting from a complementary role to becoming a fully integra...With the further reduction in cost and the increase in bandwidth, as well as the increase in internet applications, satellite communications are gradually shifting from a complementary role to becoming a fully integrated component of terrestrial communications networks. This paper firstly introduces the development of satellite communications, mobile communications and the global space-terrestrial integrated network. We then propose the functional architecture and network architecture for the integration of satellite communications and terrestrial mobile communications based on 5 G core networks. Finally, in order to support the network of the future, four key technologies are presented, a space-terrestrial integrated air interface design, a multi-band space-terrestrial integrated transmission waveform design, space-terrestrial integrated switching and routing technology, along with spectrum sharing and interference coordination technology, all necessary for the development of space-terrestrial integrated networks.展开更多
In this paper,we investigate the resource slicing and scheduling problem in the space-terrestrial integrated vehicular networks to support both delay-sensitive services(DSSs)and delay-tolerant services(DTSs).Resource ...In this paper,we investigate the resource slicing and scheduling problem in the space-terrestrial integrated vehicular networks to support both delay-sensitive services(DSSs)and delay-tolerant services(DTSs).Resource slicing and scheduling are to allocate spectrum resources to different slices and determine user association and bandwidth allocation for individual vehicles.To accommodate the dynamic network conditions,we first formulate a joint resource slicing and scheduling(JRSS)problem to minimize the long-term system cost,including the DSS requirement violation cost,DTS delay cost,and slice reconfiguration cost.Since resource slicing and scheduling decisions are interdependent with different timescales,we decompose the JRSS problem into a large-timescale resource slicing subproblem and a small-timescale resource scheduling subproblem.We propose a two-layered reinforcement learning(RL)-based JRSS scheme to find the solutions to the subproblems.In the resource slicing layer,spectrum resources are pre-allocated to different slices via a proximal policy optimization-based RL algorithm.In the resource scheduling layer,spectrum resources in each slice are scheduled to individual vehicles based on dynamic network conditions and service requirements via matching-based algorithms.We conduct extensive trace-driven experiments to demonstrate that the proposed scheme can effectively reduce the system cost while satisfying service quality requirements.展开更多
文摘With the further reduction in cost and the increase in bandwidth, as well as the increase in internet applications, satellite communications are gradually shifting from a complementary role to becoming a fully integrated component of terrestrial communications networks. This paper firstly introduces the development of satellite communications, mobile communications and the global space-terrestrial integrated network. We then propose the functional architecture and network architecture for the integration of satellite communications and terrestrial mobile communications based on 5 G core networks. Finally, in order to support the network of the future, four key technologies are presented, a space-terrestrial integrated air interface design, a multi-band space-terrestrial integrated transmission waveform design, space-terrestrial integrated switching and routing technology, along with spectrum sharing and interference coordination technology, all necessary for the development of space-terrestrial integrated networks.
文摘In this paper,we investigate the resource slicing and scheduling problem in the space-terrestrial integrated vehicular networks to support both delay-sensitive services(DSSs)and delay-tolerant services(DTSs).Resource slicing and scheduling are to allocate spectrum resources to different slices and determine user association and bandwidth allocation for individual vehicles.To accommodate the dynamic network conditions,we first formulate a joint resource slicing and scheduling(JRSS)problem to minimize the long-term system cost,including the DSS requirement violation cost,DTS delay cost,and slice reconfiguration cost.Since resource slicing and scheduling decisions are interdependent with different timescales,we decompose the JRSS problem into a large-timescale resource slicing subproblem and a small-timescale resource scheduling subproblem.We propose a two-layered reinforcement learning(RL)-based JRSS scheme to find the solutions to the subproblems.In the resource slicing layer,spectrum resources are pre-allocated to different slices via a proximal policy optimization-based RL algorithm.In the resource scheduling layer,spectrum resources in each slice are scheduled to individual vehicles based on dynamic network conditions and service requirements via matching-based algorithms.We conduct extensive trace-driven experiments to demonstrate that the proposed scheme can effectively reduce the system cost while satisfying service quality requirements.
