13 research outputs found
Joint Access and Backhaul Resource Management in Satellite-Drone Networks: A Competitive Market Approach
In this paper, the problem of user association and resource allocation is
studied for an integrated satellite-drone network (ISDN). In the considered
model, drone base stations (DBSs) provide downlink connectivity,
supplementally, to ground users whose demand cannot be satisfied by terrestrial
small cell base stations (SBSs). Meanwhile, a satellite system and a set of
terrestrial macrocell base stations (MBSs) are used to provide resources for
backhaul connectivity for both DBSs and SBSs. For this scenario, one must
jointly consider resource management over satellite-DBS/SBS backhaul links,
MBS-DBS/SBS terrestrial backhaul links, and DBS/SBS-user radio access links as
well as user association with DBSs and SBSs. This joint user association and
resource allocation problem is modeled using a competitive market setting in
which the transmission data is considered as a good that is being exchanged
between users, DBSs, and SBSs that act as "buyers", and DBSs, SBSs, MBSs, and
the satellite that act as "sellers". In this market, the quality-of-service
(QoS) is used to capture the quality of the data transmission (defined as
good), while the energy consumption the buyers use for data transmission is the
cost of exchanging a good. According to the quality of goods, sellers in the
market propose quotations to the buyers to sell their goods, while the buyers
purchase the goods based on the quotation. The buyers profit from the
difference between the earned QoS and the charged price, while the sellers
profit from the difference between earned price and the energy spent for data
transmission. The buyers and sellers in the market seek to reach a Walrasian
equilibrium, at which all the goods are sold, and each of the devices' profit
is maximized. A heavy ball based iterative algorithm is proposed to compute the
Walrasian equilibrium of the formulated market
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User grouping and power allocation algorithm for UAV-aided NOMA network
Copyright © 2020 The Author(s). To improve the transmission flexibility of emergency communication scenarios, a joint user grouping and power allocation algorithm was proposed for UAV-aided non-orthogonal multiple access (NOMA) system. A sum-rate maximization resource allocation algorithm was formulated under the constraints of the maximum transmit power and the user grouping. To solve the non-convex problem, a graph-based user grouping algorithm was proposed to minimize the relative distance between the UAV and users. Based on the grouping result, the power allocation sub-problem was transformed into a convex one by using the auxiliary-variable approach. Simulation results demonstrate that the proposed algorithm has better performance in terms of sum rates.The National Key Research and Development Program of China(2019YFC1511300);The Natural Science Foundation of Chongqing(cstc2019jcyj-msxmX0666);The Natural Science Foundation of Chongqing(cstc2019jcyj-xfkxX0002);The Open Project of Shaanxi Key Laboratory of Information Communication Network and Security(ICNS201904
UAV-assisted time-efficient data collection via uplink NOMA
Due to the mobility and line-of-sight conditions, unmanned aerial vehicle (UAV) is deemed as a promising solution to sensor data collection. On the other hand, it is vital to guarantee the timeliness of information for UAV-assisted data collection. In this paper, we propose a time-efficient data collection scheme, in which multiple ground devices upload their data to the UAV via uplink non-orthogonal multiple access (NOMA). The total flight time of the UAV is equally divided into N time slots. The duration of each time slot is minimized by jointly optimizing the straight-line trajectory, device scheduling, and transmit power. To solve this mixed integer non-convex optimization problem, we decompose it into two steps. In the first step, we study the device scheduling strategy based on the UAV trajectory and the channel gains between the UAV and ground devices, through which the original problem can be greatly simplified. In the second step, the duration of each time slot is minimized by optimizing the transmit power and the UAV trajectory. An iterative algorithm based on alternating optimization is proposed, where each subproblem can be alternatively solved by applying successive convex approximation with the device scheduling updated at the end of each iteration. Numerical results are presented to evaluate the effectiveness of the proposed scheme