Efficient transmission strategy selection algorithm for M2M communications

An evolutionary game approach

Safa Hamdoun, Abderrezak Rachedi, Tembine Hamidou, Yacine Ghamri-Doudane

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Device-to-device (D2D) communications, one of the major component of the evolving 5G networks, is showing promising advantages on supporting machine-to-machine (M2M) communications. In this paper, we consider the design of efficient transmission strategy selection algorithm for M2M communications underlaying cellular networks. First, a group of machine type-devices (MTDs) is matched with a particular user equipment (UE). MTDs belonging to the same group can access the same spectrum within its matched UE while the latter quality of service (QoS) is maintained. Next, we propose an efficient evolutionary game based transmission strategy selection algorithm for M2M communications using D2D mode. Specifically, MTDs switch opportunistically from a non-cooperative strategy to a cooperative strategy. Initially, we consider a non-cooperative scenario due to the selfish behavior of devices. In case the latter QoS is not satisfied, MTDs switch to a cooperative game. In a cooperative game, we propose two alternative power control schemes: a fixed mixed-strategy power control scheme where each MTD willing to play cooperatively selects the power strategy from a discrete level of powers and an adaptive mixed-strategy power control scheme. The latter technique enables to set efficiently the discrete power levels using a fuzzy logic and a proportional-integral-derivative (PID) controllers aiming to assure the desired QoS of UEs while maximizing the efficiency of M2M communications. Simulation results show that the evolutionary game based transmission strategy selection algorithm avoids significant degradation of traditional human-to-human (H2H) services in terms of throughput and fairness compared to a single non-cooperative game strategy. Besides, the adaptive mixed-strategy power control scheme outperforms the fixed mixed-strategy power control scheme by saving the battery life of MTDs while guaranteeing the latter QoS.

    Original languageEnglish (US)
    Title of host publicationProceedings - 2016 IEEE 15th International Symposium on Network Computing and Applications, NCA 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages286-293
    Number of pages8
    ISBN (Electronic)9781509032167
    DOIs
    StatePublished - Dec 8 2016
    Event15th IEEE International Symposium on Network Computing and Applications, NCA 2016 - Cambridge, United States
    Duration: Oct 30 2016Nov 2 2016

    Other

    Other15th IEEE International Symposium on Network Computing and Applications, NCA 2016
    CountryUnited States
    CityCambridge
    Period10/30/1611/2/16

    Fingerprint

    Power control
    Quality of service
    Switches
    Fuzzy logic
    Throughput
    Machine-to-machine communication
    Derivatives
    Degradation
    Controllers
    Communication

    Keywords

    • D2D communications
    • Evolutionary game
    • Fuzzy logic
    • M2M communications
    • PID controller
    • QoS

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Computer Science Applications
    • Hardware and Architecture

    Cite this

    Hamdoun, S., Rachedi, A., Hamidou, T., & Ghamri-Doudane, Y. (2016). Efficient transmission strategy selection algorithm for M2M communications: An evolutionary game approach. In Proceedings - 2016 IEEE 15th International Symposium on Network Computing and Applications, NCA 2016 (pp. 286-293). [7778632] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NCA.2016.7778632

    Efficient transmission strategy selection algorithm for M2M communications : An evolutionary game approach. / Hamdoun, Safa; Rachedi, Abderrezak; Hamidou, Tembine; Ghamri-Doudane, Yacine.

    Proceedings - 2016 IEEE 15th International Symposium on Network Computing and Applications, NCA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 286-293 7778632.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Hamdoun, S, Rachedi, A, Hamidou, T & Ghamri-Doudane, Y 2016, Efficient transmission strategy selection algorithm for M2M communications: An evolutionary game approach. in Proceedings - 2016 IEEE 15th International Symposium on Network Computing and Applications, NCA 2016., 7778632, Institute of Electrical and Electronics Engineers Inc., pp. 286-293, 15th IEEE International Symposium on Network Computing and Applications, NCA 2016, Cambridge, United States, 10/30/16. https://doi.org/10.1109/NCA.2016.7778632
    Hamdoun S, Rachedi A, Hamidou T, Ghamri-Doudane Y. Efficient transmission strategy selection algorithm for M2M communications: An evolutionary game approach. In Proceedings - 2016 IEEE 15th International Symposium on Network Computing and Applications, NCA 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 286-293. 7778632 https://doi.org/10.1109/NCA.2016.7778632
    Hamdoun, Safa ; Rachedi, Abderrezak ; Hamidou, Tembine ; Ghamri-Doudane, Yacine. / Efficient transmission strategy selection algorithm for M2M communications : An evolutionary game approach. Proceedings - 2016 IEEE 15th International Symposium on Network Computing and Applications, NCA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 286-293
    @inproceedings{3300aca5ce0445bab1471201da060cc5,
    title = "Efficient transmission strategy selection algorithm for M2M communications: An evolutionary game approach",
    abstract = "Device-to-device (D2D) communications, one of the major component of the evolving 5G networks, is showing promising advantages on supporting machine-to-machine (M2M) communications. In this paper, we consider the design of efficient transmission strategy selection algorithm for M2M communications underlaying cellular networks. First, a group of machine type-devices (MTDs) is matched with a particular user equipment (UE). MTDs belonging to the same group can access the same spectrum within its matched UE while the latter quality of service (QoS) is maintained. Next, we propose an efficient evolutionary game based transmission strategy selection algorithm for M2M communications using D2D mode. Specifically, MTDs switch opportunistically from a non-cooperative strategy to a cooperative strategy. Initially, we consider a non-cooperative scenario due to the selfish behavior of devices. In case the latter QoS is not satisfied, MTDs switch to a cooperative game. In a cooperative game, we propose two alternative power control schemes: a fixed mixed-strategy power control scheme where each MTD willing to play cooperatively selects the power strategy from a discrete level of powers and an adaptive mixed-strategy power control scheme. The latter technique enables to set efficiently the discrete power levels using a fuzzy logic and a proportional-integral-derivative (PID) controllers aiming to assure the desired QoS of UEs while maximizing the efficiency of M2M communications. Simulation results show that the evolutionary game based transmission strategy selection algorithm avoids significant degradation of traditional human-to-human (H2H) services in terms of throughput and fairness compared to a single non-cooperative game strategy. Besides, the adaptive mixed-strategy power control scheme outperforms the fixed mixed-strategy power control scheme by saving the battery life of MTDs while guaranteeing the latter QoS.",
    keywords = "D2D communications, Evolutionary game, Fuzzy logic, M2M communications, PID controller, QoS",
    author = "Safa Hamdoun and Abderrezak Rachedi and Tembine Hamidou and Yacine Ghamri-Doudane",
    year = "2016",
    month = "12",
    day = "8",
    doi = "10.1109/NCA.2016.7778632",
    language = "English (US)",
    pages = "286--293",
    booktitle = "Proceedings - 2016 IEEE 15th International Symposium on Network Computing and Applications, NCA 2016",
    publisher = "Institute of Electrical and Electronics Engineers Inc.",

    }

    TY - GEN

    T1 - Efficient transmission strategy selection algorithm for M2M communications

    T2 - An evolutionary game approach

    AU - Hamdoun, Safa

    AU - Rachedi, Abderrezak

    AU - Hamidou, Tembine

    AU - Ghamri-Doudane, Yacine

    PY - 2016/12/8

    Y1 - 2016/12/8

    N2 - Device-to-device (D2D) communications, one of the major component of the evolving 5G networks, is showing promising advantages on supporting machine-to-machine (M2M) communications. In this paper, we consider the design of efficient transmission strategy selection algorithm for M2M communications underlaying cellular networks. First, a group of machine type-devices (MTDs) is matched with a particular user equipment (UE). MTDs belonging to the same group can access the same spectrum within its matched UE while the latter quality of service (QoS) is maintained. Next, we propose an efficient evolutionary game based transmission strategy selection algorithm for M2M communications using D2D mode. Specifically, MTDs switch opportunistically from a non-cooperative strategy to a cooperative strategy. Initially, we consider a non-cooperative scenario due to the selfish behavior of devices. In case the latter QoS is not satisfied, MTDs switch to a cooperative game. In a cooperative game, we propose two alternative power control schemes: a fixed mixed-strategy power control scheme where each MTD willing to play cooperatively selects the power strategy from a discrete level of powers and an adaptive mixed-strategy power control scheme. The latter technique enables to set efficiently the discrete power levels using a fuzzy logic and a proportional-integral-derivative (PID) controllers aiming to assure the desired QoS of UEs while maximizing the efficiency of M2M communications. Simulation results show that the evolutionary game based transmission strategy selection algorithm avoids significant degradation of traditional human-to-human (H2H) services in terms of throughput and fairness compared to a single non-cooperative game strategy. Besides, the adaptive mixed-strategy power control scheme outperforms the fixed mixed-strategy power control scheme by saving the battery life of MTDs while guaranteeing the latter QoS.

    AB - Device-to-device (D2D) communications, one of the major component of the evolving 5G networks, is showing promising advantages on supporting machine-to-machine (M2M) communications. In this paper, we consider the design of efficient transmission strategy selection algorithm for M2M communications underlaying cellular networks. First, a group of machine type-devices (MTDs) is matched with a particular user equipment (UE). MTDs belonging to the same group can access the same spectrum within its matched UE while the latter quality of service (QoS) is maintained. Next, we propose an efficient evolutionary game based transmission strategy selection algorithm for M2M communications using D2D mode. Specifically, MTDs switch opportunistically from a non-cooperative strategy to a cooperative strategy. Initially, we consider a non-cooperative scenario due to the selfish behavior of devices. In case the latter QoS is not satisfied, MTDs switch to a cooperative game. In a cooperative game, we propose two alternative power control schemes: a fixed mixed-strategy power control scheme where each MTD willing to play cooperatively selects the power strategy from a discrete level of powers and an adaptive mixed-strategy power control scheme. The latter technique enables to set efficiently the discrete power levels using a fuzzy logic and a proportional-integral-derivative (PID) controllers aiming to assure the desired QoS of UEs while maximizing the efficiency of M2M communications. Simulation results show that the evolutionary game based transmission strategy selection algorithm avoids significant degradation of traditional human-to-human (H2H) services in terms of throughput and fairness compared to a single non-cooperative game strategy. Besides, the adaptive mixed-strategy power control scheme outperforms the fixed mixed-strategy power control scheme by saving the battery life of MTDs while guaranteeing the latter QoS.

    KW - D2D communications

    KW - Evolutionary game

    KW - Fuzzy logic

    KW - M2M communications

    KW - PID controller

    KW - QoS

    UR - http://www.scopus.com/inward/record.url?scp=85010402335&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=85010402335&partnerID=8YFLogxK

    U2 - 10.1109/NCA.2016.7778632

    DO - 10.1109/NCA.2016.7778632

    M3 - Conference contribution

    SP - 286

    EP - 293

    BT - Proceedings - 2016 IEEE 15th International Symposium on Network Computing and Applications, NCA 2016

    PB - Institute of Electrical and Electronics Engineers Inc.

    ER -