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Genetic Algorithm for Mode Selection in Device-to-Device (D2D) Communication for 5G Cellular Networks

Received: 5 February 2024    Accepted: 23 February 2024    Published: 7 March 2024
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Abstract

The widespread use of smart devices and mobile applications is leading to a massive growth of wireless data traffic. With the rapidly growing of the customers’ data traffic demand, improving the system capacity and increasing the user throughput have become essential concerns for the future fifth-generation (5G) wireless communication network. In a conventional cellular system, devices are not allowed to directly communicate with each other in the licensed cellular spectrum and all communications take place through the base stations (BS) and core network. Device-to-Device (D2D) communication refers to a technology that enables devices to communicate directly with each other, without sending data to the base station and the core network. This technology has the potential to improve system performance, enhance the user experience, increase spectral efficiency, reduce the terminal transmitting power, reduce the burden of the cellular network, and reduce end to end latency. In D2D communication user equipment’s (UEs) are enabled to select among different modes of communication which are defined based on the frequency resource sharing. Dedicated mode where D2D devices directly transmit by using dedicated resources. Reuse mode where D2D devices reuse some resources of the cellular network. Outband mode where D2D communication uses unlicensed spectrum (e.g. the free 2.4 GHz Industrial Scientific and Medical (ISM) band or the 38 GHz millimetre wave band) where cellular communication does not take place. Cellular mode where the D2D communication is relayed via gNode B (gNB) and it is treated as cellular users. In this work, the target was to reach the optimal mode selection policy and genetic algorithm method was used with the objective of maximizing the total fitness function. Optimal mode selection policy was presented and analysed amongst cellular, dedicated, reused and outband mode. In the present study of mode selection issues in D2D enabled networks, genetic algorithm was proposed for the case when the cellular user equipment (UE) moves in the network. Quality of service (QoS) parameters, mobility parameters and Analytic Hierarchy Process (AHP) method were used to define the mode selection algorithm. To evaluate the performance of the proposed genetic algorithm, a study of the convergence of the algorithm and the signal-to-interference plus noise ratio (SINR) was done.

Published in American Journal of Networks and Communications (Volume 13, Issue 1)
DOI 10.11648/j.ajnc.20241301.13
Page(s) 30-43
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

D2D Communication, 5G Cellular Network, Mode Selection, Genetic Algorithm

References
[1] Rafay IQBAL Ansari, Chrysostomos Chrysostomou, Syed Ali Hassan, Mohsen Guizani. “5G D2D Networks: Techniques, Challenges, and Future Prospects”, December 2018.
[2] Demia Dela Penda, “Device-to-Device Communication in Future Cellular Networks”. 2018.
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[7] Andrews, Jeffrey G., et al. "What will 5G be?." IEEE Journal on selected areas in communications 32.6 (2014): 1065-1082.
[8] Hassan, Najmul, Kok-Lim Alvin Yau, and Celimuge Wu. "Edge computing in 5G: A review." IEEE Access 7 (2019): 127276-127289.
[9] S. Mumtaz and J. Rodriguez, Smart device to smart device communication. SpringerVerlag, 2014.
[10] A. Asadi, Q. Wang, and V. Mancuso, “A survey on device-to-device communication in cellular networks,” IEEE Communications Surveys Tutorials, vol. 16, pp. 1801–1819, Fourthquarter, 2014.
[11] S. Research, “Prose (proximity services) for lte & 5g networks: 2017 - 2030 opportunities, challenges, strategies & forecasts,” tech. rep., Social networking service (SNC) Telecom & IT, Jan. 2017.
[12] Eric Deussom, Michael Sone, Ivan Basile Kabiena ,“A Game Theory Approach for D2D Communication Mode Selection for Terminals under a cell”. July 2022. http://dx.doi.org/10.14738/aivp.103.12585
[13] P. Phunchongharn, E. Hossain, and D. I. Kim, “Resource allocation for device-todevice communications underlaying lte-advanced networks,” IEEE Wireless Communications, vol. 20, no. 4, pp. 91–100, 2013.
[14] Jun Li, Guanglin Lei, Gunasekaran Manogaran, George Mastorakis, and Constandinos X. Mavromoustakis “D2D Communication Mode Selection and Resource Optimization Algorithm with Optimal Throughput in 5G Network”, 2019.
[15] Mohamed Kamel BENBRAIKA ,“Device-to-Device control in 5G networks”, 2020.
[16] Maryam HABIBOMAREKANI “Mode Selection in Device-to-Device Communications”, November 2018.
[17] Levie, Ron, et al. "Pathloss prediction using deep learning with applications to cellular optimization and efficient D2D link scheduling." ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020.
[18] Hassan, Yeakub, et al. "Interference minimization in D2D communication underlaying cellular networks." IEEE Access 5 (2017): 22471-22484.
[19] Deussom Eric and Tonye Emmanuel, "New Propagation Model Optimization Approach based on Particles Swarm Optimization Algorithm," International Journal of Computer Applications, Vol 118 - Number (10), pages: 39-47, May 2015. http://dx.doi.org/10.5120/20785-3430
[20] Deussom Eric, E. Tonye and B. Kabiena, "Propagation model optimization based on Artificial Bee Colony algorithm: Application to Yaoundé town, Cameroon," IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), Volume 15, Issue 2 Ser. II (Mar – Apr 2020), PP 14-26. http://dx.doi.org/10.9790/1676-1502021426
[21] Deussom Eric, Souop Koagne Gloire De Dieu, Feudjio Cyrille , Tonye Emmanuel, Michael Ekonde Sone, 2022, Social Spider Algorithm-based Approach for Propagation Model Optimization. Application to Yaounde Town, International Journal of Engineering Research & Technology (IJERT) Volume 11, Issue 01 (January 2022)
[22] DEUSSOM Eric, TSAGUE Beldine and Tonye Emmanuel, (2022) Propagation Model Optimization Based on Ion Motion Optimization Algorithm for Efficient Deployment of eLTE Network. Journal of Computer and Communications, 10, 171-196. https://doi: 10.4236/jcc.2022.1011012.
[23] Deussom Djomadji, E. M., Basile, K. I., Thierry, F. S. and Emanuel, T. (2023) COST 231-Hata Propagation Model Optimization in 1800 MHz Band Based on Magnetic Optimization Algorithm: Application to the City of Limbé. Journal of Computer and Communications, 11, 57-74. https://doi: 10.4236/jcc.2023.112005
[24] Deussom Eric and Tonye Emmanuel; New Approach for Determination of Propagation Model Adapted To an Environment Based On Genetic Algorithms: Application to the City Of Yaoundé, Cameroon; IOSR Journal of Electrical and Electronics Engineering 10 (1), 48-59. http://dx.doi.org/10.9790/1676-10134859
[25] Emmanuel Tonye and Eric DEUSSOM; Optimisation de modèles de propagation à partir des données de mesures radio de la ville de Yaoundé; Journal of the Cameroon Academy of Sciences 12 (3), 180-205. http://dx.doi.org/10.9790/1676-10134859
[26] Eric Michel Deussom Djomadji, NDJE BIHOLONG Evelyne Noelle, & TONYE Emmanuel. (2022). Artificial Bee Colonies Solution for Load Sharing in a Cloud RAN. European Journal of Applied Sciences, 10(2), 33–50. https://doi.org/10.14738/aivp.102.11935
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Cite This Article
  • APA Style

    Djomadji, E. M. D., Garga, M., Fouba, B. A. R., Bouetou, T. B. (2024). Genetic Algorithm for Mode Selection in Device-to-Device (D2D) Communication for 5G Cellular Networks. American Journal of Networks and Communications, 13(1), 30-43. https://doi.org/10.11648/j.ajnc.20241301.13

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    ACS Style

    Djomadji, E. M. D.; Garga, M.; Fouba, B. A. R.; Bouetou, T. B. Genetic Algorithm for Mode Selection in Device-to-Device (D2D) Communication for 5G Cellular Networks. Am. J. Netw. Commun. 2024, 13(1), 30-43. doi: 10.11648/j.ajnc.20241301.13

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    AMA Style

    Djomadji EMD, Garga M, Fouba BAR, Bouetou TB. Genetic Algorithm for Mode Selection in Device-to-Device (D2D) Communication for 5G Cellular Networks. Am J Netw Commun. 2024;13(1):30-43. doi: 10.11648/j.ajnc.20241301.13

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  • @article{10.11648/j.ajnc.20241301.13,
      author = {Eric Michel Deussom Djomadji and Maniba Garga and Bienvenue Arsene Roger Fouba and Thomas Bouetou Bouetou},
      title = {Genetic Algorithm for Mode Selection in Device-to-Device (D2D) Communication for 5G Cellular Networks},
      journal = {American Journal of Networks and Communications},
      volume = {13},
      number = {1},
      pages = {30-43},
      doi = {10.11648/j.ajnc.20241301.13},
      url = {https://doi.org/10.11648/j.ajnc.20241301.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.20241301.13},
      abstract = {The widespread use of smart devices and mobile applications is leading to a massive growth of wireless data traffic. With the rapidly growing of the customers’ data traffic demand, improving the system capacity and increasing the user throughput have become essential concerns for the future fifth-generation (5G) wireless communication network. In a conventional cellular system, devices are not allowed to directly communicate with each other in the licensed cellular spectrum and all communications take place through the base stations (BS) and core network. Device-to-Device (D2D) communication refers to a technology that enables devices to communicate directly with each other, without sending data to the base station and the core network. This technology has the potential to improve system performance, enhance the user experience, increase spectral efficiency, reduce the terminal transmitting power, reduce the burden of the cellular network, and reduce end to end latency. In D2D communication user equipment’s (UEs) are enabled to select among different modes of communication which are defined based on the frequency resource sharing. Dedicated mode where D2D devices directly transmit by using dedicated resources. Reuse mode where D2D devices reuse some resources of the cellular network. Outband mode where D2D communication uses unlicensed spectrum (e.g. the free 2.4 GHz Industrial Scientific and Medical (ISM) band or the 38 GHz millimetre wave band) where cellular communication does not take place. Cellular mode where the D2D communication is relayed via gNode B (gNB) and it is treated as cellular users. In this work, the target was to reach the optimal mode selection policy and genetic algorithm method was used with the objective of maximizing the total fitness function. Optimal mode selection policy was presented and analysed amongst cellular, dedicated, reused and outband mode. In the present study of mode selection issues in D2D enabled networks, genetic algorithm was proposed for the case when the cellular user equipment (UE) moves in the network. Quality of service (QoS) parameters, mobility parameters and Analytic Hierarchy Process (AHP) method were used to define the mode selection algorithm. To evaluate the performance of the proposed genetic algorithm, a study of the convergence of the algorithm and the signal-to-interference plus noise ratio (SINR) was done.
    },
     year = {2024}
    }
    

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  • TY  - JOUR
    T1  - Genetic Algorithm for Mode Selection in Device-to-Device (D2D) Communication for 5G Cellular Networks
    AU  - Eric Michel Deussom Djomadji
    AU  - Maniba Garga
    AU  - Bienvenue Arsene Roger Fouba
    AU  - Thomas Bouetou Bouetou
    Y1  - 2024/03/07
    PY  - 2024
    N1  - https://doi.org/10.11648/j.ajnc.20241301.13
    DO  - 10.11648/j.ajnc.20241301.13
    T2  - American Journal of Networks and Communications
    JF  - American Journal of Networks and Communications
    JO  - American Journal of Networks and Communications
    SP  - 30
    EP  - 43
    PB  - Science Publishing Group
    SN  - 2326-8964
    UR  - https://doi.org/10.11648/j.ajnc.20241301.13
    AB  - The widespread use of smart devices and mobile applications is leading to a massive growth of wireless data traffic. With the rapidly growing of the customers’ data traffic demand, improving the system capacity and increasing the user throughput have become essential concerns for the future fifth-generation (5G) wireless communication network. In a conventional cellular system, devices are not allowed to directly communicate with each other in the licensed cellular spectrum and all communications take place through the base stations (BS) and core network. Device-to-Device (D2D) communication refers to a technology that enables devices to communicate directly with each other, without sending data to the base station and the core network. This technology has the potential to improve system performance, enhance the user experience, increase spectral efficiency, reduce the terminal transmitting power, reduce the burden of the cellular network, and reduce end to end latency. In D2D communication user equipment’s (UEs) are enabled to select among different modes of communication which are defined based on the frequency resource sharing. Dedicated mode where D2D devices directly transmit by using dedicated resources. Reuse mode where D2D devices reuse some resources of the cellular network. Outband mode where D2D communication uses unlicensed spectrum (e.g. the free 2.4 GHz Industrial Scientific and Medical (ISM) band or the 38 GHz millimetre wave band) where cellular communication does not take place. Cellular mode where the D2D communication is relayed via gNode B (gNB) and it is treated as cellular users. In this work, the target was to reach the optimal mode selection policy and genetic algorithm method was used with the objective of maximizing the total fitness function. Optimal mode selection policy was presented and analysed amongst cellular, dedicated, reused and outband mode. In the present study of mode selection issues in D2D enabled networks, genetic algorithm was proposed for the case when the cellular user equipment (UE) moves in the network. Quality of service (QoS) parameters, mobility parameters and Analytic Hierarchy Process (AHP) method were used to define the mode selection algorithm. To evaluate the performance of the proposed genetic algorithm, a study of the convergence of the algorithm and the signal-to-interference plus noise ratio (SINR) was done.
    
    VL  - 13
    IS  - 1
    ER  - 

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Author Information
  • Department of Electrical and Electronic Engineering, College of Technology, University of Buea, Buea, Cameroon; Division of Information and Communication Technology, National Advanced School of Post, Telecommunication and ICT, University of Yaounde I, Yaoundé, Cameroon

  • Division of Information and Communication Technology, National Advanced School of Post, Telecommunication and ICT, University of Yaounde I, Yaoundé, Cameroon

  • Division of Information and Communication Technology, National Advanced School of Post, Telecommunication and ICT, University of Yaounde I, Yaoundé, Cameroon; Department of Computer Science, National Advanced School of Engineering of Yaoundé, University of Yaounde I, Yaoundé, Cameroon

  • Division of Information and Communication Technology, National Advanced School of Post, Telecommunication and ICT, University of Yaounde I, Yaoundé, Cameroon

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