| The upcoming satellite Internet of Things(S-Io T)would enable massive machine type communication(m MTC)anywhere and anytime by integrating satellites with terrestrial Io T together.Therefore,S-Io T will prompt ever-growing needs for the wide coverage applications like location-based services,smart agriculture,remote healthcare,environmental monitoring,geologic disaster forecasting.However,compared with the base station(BS)in terrestrial network,the power and storage resources on the satellite are extremely limited,and the satellite-to-ground channel is very complex and changeable.Therefore,an appropriate resource allocation scheme for the NOMA-based S-Io T downlink network considering the long-term system performance is well worth studying.On one hand,paper proposes a resource allocation scheme that jointly considers user fairness and energy utility,which achieves high user fairness while approaches the maximum energy utility.On other hand,in systems that appear increasing needs for the timeliness of status updates,such as forest fire prevention,intelligent transportation system,the information freshness is of paramount importance,since the obsolete information may lead to unpredictable or even disaster result.In such systems,optimizing the traditional end-to-end latency can sometimes be trivial.Therefore,to optimize the information freshness in S-Io T network,we introduce the age of information(Ao I)into S-Io T network and utilize the List Net algorithm to derive an optimized power allocation order with linear time complexity.Finally,a power allocation scheme to minimize expected weighted sum age of information(EWSAOI)is proposed,named NOMA-AM scheme.The specific research content of this paper is as follows:In the existing resource allocation schemes that aim at maximizing energy utility,some UEs with poor channel conditions may only be allocated little or no power,thus affecting the fairness of the entire system.To ensure the quality of service(Qo S)of each UE and optimize user fairness,we introduce a minimum data rate constraint for each UE.Based on the minimum data rate constraint,we further derive the minimum power threshold constraint and formulate a complex multi-slot optimization problem.We utilize the Lyapunov optimization theory to convert the long-term multi-slot stochastic optimization problem into a series of single time slot deterministic optimization problems,and then use the particle swarm optimization(PSO)algorithm to derive the power allocation scheme,named NOMA-Qo S scheme.Simulation results show that NOMA-Qo S scheme achieve high user fairness while approach the maximum energy utility.Therefore,NOMA-Qo S scheme achieves a good balance between user fairness and energy utility.Then,to keep the information freshness in NOMA-based S-Io T downlink,we introduce the Ao I into S-Io T network to effectively characterize the information freshness of status updates.In comparison with end-to-end transmission latency,Ao I jointly considers transmission interval and transmission latency,so it can better characterize the information freshness of the S-Io T system.Moreover,we leverage the List Net algorithm to derive the weights of the queue backlog and channel conditions to obtain an optimized power allocation order with linear complexity.Finally,we utilize the PSO to derive a power allocation scheme to minimize EWSAo I with a practical complexity,named NOMA-AM scheme.Simulation results show that NOMA-AM scheme has the lowest EWSAo I in comparison with several benchmark schemes. |
