This paper considers link scheduling in a wireless network comprising of two types of nodes:(i)hybrid access points(HAPs)that harvest solar en-ergy,and(ii)devices that harvest radio frequency(RF)energy whenever HAPs t...This paper considers link scheduling in a wireless network comprising of two types of nodes:(i)hybrid access points(HAPs)that harvest solar en-ergy,and(ii)devices that harvest radio frequency(RF)energy whenever HAPs transmit.Our aim is to de-rive the shortest possible link schedule that determines the transmission time of inter-HAPs links,and uplinks from devices to HAPs.We first outline a mixed in-teger linear program(MILP),which can be run by a central node to determine the optimal schedule and transmit power of HAPs and devices.We then out-line a game theory based protocol called Distributed Schedule Minimization Protocol(DSMP)that is run by HAPs and devices.Advantageously,it does not require causal energy arrivals and channel gains in-formation.Our results show that DSMP produces schedule lengths that are at most 1.99x longer than the schedule computed by MILP.展开更多
基金This research is partially supported by Guangzhou Science and Technology Foundation Committee,Grant No.202201010394the National Natural Science Foundation of China,Grant No.61902146。
文摘This paper considers link scheduling in a wireless network comprising of two types of nodes:(i)hybrid access points(HAPs)that harvest solar en-ergy,and(ii)devices that harvest radio frequency(RF)energy whenever HAPs transmit.Our aim is to de-rive the shortest possible link schedule that determines the transmission time of inter-HAPs links,and uplinks from devices to HAPs.We first outline a mixed in-teger linear program(MILP),which can be run by a central node to determine the optimal schedule and transmit power of HAPs and devices.We then out-line a game theory based protocol called Distributed Schedule Minimization Protocol(DSMP)that is run by HAPs and devices.Advantageously,it does not require causal energy arrivals and channel gains in-formation.Our results show that DSMP produces schedule lengths that are at most 1.99x longer than the schedule computed by MILP.
