A learning approach for traffic offloading in stochastic heterogeneous cellular networks

Xianfu Chen, Celimuge Wu, Yifan Zhou, Honggang Zhang

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    9 Citations (Scopus)


    This paper addresses energy-aware traffic offloading in stochastic heterogeneous cellular networks (HCNs). The objective is to minimize energy consumption of the HCN while maintaining Quality-of-Service experienced by the mobile users. For each cell, the energy consumption depends on its associated system load, which is coupled with system loads in other cells due to the sharing over a common spectrum band. Such a traffic offloading problem is modeled by a discrete-time Markov decision process (DTMDP). Based on the traffic observations and the traffic offloading operations, the network controller learns to solve the optimal traffic offloading strategy with no prior knowledge of the DTMDP statistics. To deal with the curse of dimensionality, we design a centralized Q-learning with compact state representation algorithm, which is named as QC-learning. Moreover, a decentralized QC-learning algorithm is developed such that the macro-cell base stations (BSs) can independently manage the operations of small-cell BSs by making use of the network information obtained from the network controller. Simulations validate the proposed studies.
    Original languageEnglish
    Title of host publicationCommunications (ICC), 2015 IEEE International Conference on
    PublisherIEEE Institute of Electrical and Electronic Engineers
    ISBN (Electronic)978-1-4673-6432-4, 978-1-4673-6431-7
    Publication statusPublished - 10 Sept 2015
    MoE publication typeA4 Article in a conference publication
    EventIEEE International Conference on Communications, ICC 2015: Smart City & Smart World - London, United Kingdom
    Duration: 8 Jun 201512 Jun 2015


    ConferenceIEEE International Conference on Communications, ICC 2015
    Abbreviated titleICC
    Country/TerritoryUnited Kingdom


    • heterogeneous cellular networks
    • HCN


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