Resource Allocation Strategy Based on Matching Game

doi:10.12142/ZTECOM.202004003

ZTE Communications ›› 2020, Vol. 18 ›› Issue (4): 10-17.DOI: 10.12142/ZTECOM.202004003

收稿日期:2020-05-18 出版日期:2020-12-25 发布日期:2021-01-13

Resource Allocation Strategy Based on Matching Game

DENG Xu(), ZHU Lidong

National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China

Received:2020-05-18 Online:2020-12-25 Published:2021-01-13
About author:DENG Xu (1143555752@qq.com) is currently pursuing the M.S. degree at University of Electronic Science and Technology of China. His research interests include wireless and mobile communication system.|ZHU Lidong received his Ph.D. degree from University of Electronic Science and Technology of China in 2003. Now he is a professor of National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China. His research interests include satellite communications and networking, communication signal processing, and radio resource management.
Supported by:
National Natural Science Foundation of China(61871422)

摘要/Abstract

Abstract:

With the development of satellite communication technology, the traditional resource allocation strategies are difficult to meet the requirements of resource utilization efficiency. In order to solve the optimization problem of resource allocation for multi-layer satellite networks in multi-user scenarios, we propose a new resource allocation scheme based on the many-to-many matching game. This scheme is different from the traditional resource allocation strategies that just consider a trade-off between the new call blocking probability and the handover call failure probability. Based on different preference lists among different layers of medium earth orbit (MEO) satellites, low earth orbit (LEO) satellites, base stations and users, we propose the corresponding algorithms from the perspective of quality of experience (QoE). The simulation results show that the many-to-many matching game scheme can effectively improve both the resource utilization efficiency and QoE, compared with the one-to-one and many-to-one matching algorithms.

Key words: satellite network, resource allocation, many-to-many matching game, preference lists, quality of experience

. [J]. ZTE Communications, 2020, 18(4): 10-17.

DENG Xu, ZHU Lidong. Resource Allocation Strategy Based on Matching Game[J]. ZTE Communications, 2020, 18(4): 10-17.

图/表 8

Figure 1 Model of network based on matching game.

Figure 2 The matching framework.

Figure 3 Sum of data rates varying with different MEONum.

Figure 4 Sum of data ratesvarying with different LEONum.

Figure 5 Sum of data rates varying with different BSNum.

Figure 6 Sum of data rate versus different number of LEO satellites among the three algorithms.

Figure 7 Sum of dataversus different number of base stations among the three algorithms.

Figure 8 Sum of data rates versus different user numbers with the three matching algorithms.

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