{"title":"Q-learning Based Random Access with Collision free RACH Interactions for Cellular M2M","authors":"L. Bello, P. Mitchell, D. Grace, Tautvydas Mickus","doi":"10.1109/NGMAST.2015.22","DOIUrl":null,"url":null,"abstract":"This paper investigates the coexistence of M2M and H2H based traffic sharing the RACH of an existing cellular network. Q-learning is applied to control the RACH access of the M2M devices which enables collision free access amongst the M2M user group. Frame ALOHA for a Q-learning RACH access (FA-QL-RACH) is proposed to realise a collision free RACH access between the H2H and M2M user groups. The scheme introduces a separate frame for H2H and M2M to use in the RACH access. Simulation results show that applying Q-learning to realise the proposed FA-QL-RACH scheme resolves the RACH overload problem and improves the RACH-throughput. Finally the improved RACH-throughput performance indicates that the FA-QL-RACH scheme has eliminated the collision between the H2H and M2M user groups.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NGMAST.2015.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
This paper investigates the coexistence of M2M and H2H based traffic sharing the RACH of an existing cellular network. Q-learning is applied to control the RACH access of the M2M devices which enables collision free access amongst the M2M user group. Frame ALOHA for a Q-learning RACH access (FA-QL-RACH) is proposed to realise a collision free RACH access between the H2H and M2M user groups. The scheme introduces a separate frame for H2H and M2M to use in the RACH access. Simulation results show that applying Q-learning to realise the proposed FA-QL-RACH scheme resolves the RACH overload problem and improves the RACH-throughput. Finally the improved RACH-throughput performance indicates that the FA-QL-RACH scheme has eliminated the collision between the H2H and M2M user groups.
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