A multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels
Abstract This paper investigates the problem of multi‐user anti‐jamming channel access with partially overlapping channels (POC). Compared with traditional anti‐jamming systems that use non‐overlapping channels, POC improve the spectral efficiency. However, the partial overlap of channels also bring...
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Wiley
2021
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oai:doaj.org-article:716c2bfc6cb54f7fb96952de4eb04ea12021-11-09T04:19:38ZA multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels1751-86361751-862810.1049/cmu2.12288https://doaj.org/article/716c2bfc6cb54f7fb96952de4eb04ea12021-12-01T00:00:00Zhttps://doi.org/10.1049/cmu2.12288https://doaj.org/toc/1751-8628https://doaj.org/toc/1751-8636Abstract This paper investigates the problem of multi‐user anti‐jamming channel access with partially overlapping channels (POC). Compared with traditional anti‐jamming systems that use non‐overlapping channels, POC improve the spectral efficiency. However, the partial overlap of channels also brings more serious interference. For this, physical distance and channel separation on the interference intensity under partially overlapping channels are first considered and the malicious jamming and interference among users are formulated as a hierarchical binary model. Secondly, to cope with multi‐user decisions under dynamic jamming conditions, the Markov game framework is adopted to analyse the problem. Thirdly, a multi‐user collaborative anti‐jamming channel selection algorithm based on reinforcement learning is proposed as well as the optimal anti‐jamming strategy can be obtained. Finally, the simulation results validate that the proposed algorithm helps users cope with jamming and eliminate mutual interference. Compared with the non‐overlapping channel access scheme, the POC access scheme achieves higher network throughput.Yunpeng ZhangLuliang JiaNan QiYifan XuXueqiang ChenWileyarticleTelecommunicationTK5101-6720ENIET Communications, Vol 15, Iss 19, Pp 2461-2468 (2021) |
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DOAJ |
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DOAJ |
| language |
EN |
| topic |
Telecommunication TK5101-6720 |
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Telecommunication TK5101-6720 Yunpeng Zhang Luliang Jia Nan Qi Yifan Xu Xueqiang Chen A multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels |
| description |
Abstract This paper investigates the problem of multi‐user anti‐jamming channel access with partially overlapping channels (POC). Compared with traditional anti‐jamming systems that use non‐overlapping channels, POC improve the spectral efficiency. However, the partial overlap of channels also brings more serious interference. For this, physical distance and channel separation on the interference intensity under partially overlapping channels are first considered and the malicious jamming and interference among users are formulated as a hierarchical binary model. Secondly, to cope with multi‐user decisions under dynamic jamming conditions, the Markov game framework is adopted to analyse the problem. Thirdly, a multi‐user collaborative anti‐jamming channel selection algorithm based on reinforcement learning is proposed as well as the optimal anti‐jamming strategy can be obtained. Finally, the simulation results validate that the proposed algorithm helps users cope with jamming and eliminate mutual interference. Compared with the non‐overlapping channel access scheme, the POC access scheme achieves higher network throughput. |
| format |
article |
| author |
Yunpeng Zhang Luliang Jia Nan Qi Yifan Xu Xueqiang Chen |
| author_facet |
Yunpeng Zhang Luliang Jia Nan Qi Yifan Xu Xueqiang Chen |
| author_sort |
Yunpeng Zhang |
| title |
A multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels |
| title_short |
A multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels |
| title_full |
A multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels |
| title_fullStr |
A multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels |
| title_full_unstemmed |
A multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels |
| title_sort |
multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels |
| publisher |
Wiley |
| publishDate |
2021 |
| url |
https://doaj.org/article/716c2bfc6cb54f7fb96952de4eb04ea1 |
| work_keys_str_mv |
AT yunpengzhang amultiagentreinforcementlearningantijammingmethodwithpartiallyoverlappingchannels AT luliangjia amultiagentreinforcementlearningantijammingmethodwithpartiallyoverlappingchannels AT nanqi amultiagentreinforcementlearningantijammingmethodwithpartiallyoverlappingchannels AT yifanxu amultiagentreinforcementlearningantijammingmethodwithpartiallyoverlappingchannels AT xueqiangchen amultiagentreinforcementlearningantijammingmethodwithpartiallyoverlappingchannels AT yunpengzhang multiagentreinforcementlearningantijammingmethodwithpartiallyoverlappingchannels AT luliangjia multiagentreinforcementlearningantijammingmethodwithpartiallyoverlappingchannels AT nanqi multiagentreinforcementlearningantijammingmethodwithpartiallyoverlappingchannels AT yifanxu multiagentreinforcementlearningantijammingmethodwithpartiallyoverlappingchannels AT xueqiangchen multiagentreinforcementlearningantijammingmethodwithpartiallyoverlappingchannels |
| _version_ |
1718441306019069952 |