Journal of Computer Applications ›› 2024, Vol. 44 ›› Issue (3): 863-868.DOI: 10.11772/j.issn.1001-9081.2023030322

• Network and communications • Previous Articles     Next Articles

Channel access and resource allocation algorithm for adaptive p-persistent mobile ad hoc network

Xintong QIN1, Zhengyu SONG1(), Tianwei HOU1, Feiyue WANG1, Xin SUN1, Wei LI2   

  1. 1.School of Electronic and Information Engineering,Beijing Jiaotong University,Beijing 100044,China
    2.Chongqing Jinmei Communication Company Limited,Chongqing 400030,China
  • Received:2023-03-29 Revised:2023-05-29 Accepted:2023-06-08 Online:2023-06-30 Published:2024-03-10
  • Contact: Zhengyu SONG
  • About author:QIN Xintong, born in 1999, Ph. D. candidate. His research interests include wireless communication, mobile Ad Hoc network, resource allocation.
    HOU Tianwei, born in 1991, Ph. D., associate professor. His research interests include UAV communication, large scale reflective array, non-orthogonal multiple access.
    WANG Feiyue, born in 1999, M. S. candidate. His research interests include wireless communication, mobile Ad Hoc network, resource allocation.
    SUN Xin, born in 1967, Ph. D., professor. Her research interests include professional mobile communication, satellite communication, internet of things.
    LI Wei, born in 1988, Ph. D., senior engineer. His research interests include wireless communication electromagnetic spectrum sensing, electromagnetic interference countermeasures, next-generation mobile communication key technologies.
  • Supported by:
    National Natural Science Foundation of China(61901027)


秦鑫彤1, 宋政育1(), 侯天为1, 王飞越1, 孙昕1, 黎伟2   

  1. 1.北京交通大学 电子信息工程学院,北京 100044
    2.重庆金美通信有限责任公司,重庆 400030
  • 通讯作者: 宋政育
  • 作者简介:秦鑫彤(1999—),男,山西长治人,博士研究生,主要研究方向:无线通信、移动自组网、资源分配
  • 基金资助:


For the channel access and resource allocation problem in the p-persistent Mobile Ad hoc NETwork (MANET), an adaptive channel access and resource allocation algorithm with low complexity was proposed. Firstly, considering the characteristics of MANET, the optimization problem was formulated to maximize the channel utility of each node. Secondly, the formulated problem was then transformed into a Markov decision process and the state, action, as well as the reward function were defined. Finally, the network parameters were trained based on policy gradient to optimize the competition probability, priority growth factor, and the number of communication nodes. Simulation experiment results indicate that the proposed algorithm can significantly improve the performance of p-persistent CSMA (Carrier Sense Multiple Access) protocol. Compared with the scheme with fixed competition probability and predefined p-value, the proposed algorithm can improve the channel utility by 45% and 17%, respectively. The proposed algorithm can also achieve higher channel utility compared to the scheme with fixed number of communication nodes when the total number of nodes is less than 35. Most importantly, with the increase of packet arrival rate, the proposed algorithm can fully utilize the channel resource to reduce the idle period of time slot.

Key words: Mobile Ad hoc NETwork (MANET), Carrier Sense Multiple Access (CSMA), deep reinforcement learning, channel utility, resource allocation



关键词: 移动自组网, 载波侦听多址接入, 深度强化学习, 信道利用率, 资源分配

CLC Number: