Smallcells have great potential to enhance cellular networks, complementing macrocells. Severe interference may occur, as smallcells are expected to be deployed and operated uncoordinatedly. However, existing resource management methods require significant overhead to suppress interference. We propose a new resource management approach which is able to mitigate the cross-tier and co-tier interference with substantially reduced overhead. The key idea is to categorize the smallcells into two regions based on a judiciously designed cross-tier interference criterion. Smallcells in the high-interference zone occupy orthogonal radio resources with the macrocell; smallcells in the other zone can reuse the resources that the macrocell is using. Another crucial aspect is that we formulate the resource sharing between the macrocell and smallcells in the low-interference zone to a multi-agent Q-learning process which assigns adequate transmit power levels in a decentralized manner to suppress the co/cross-tier interference. As a result, our approach is able to reduce the outage probabilities of macrocell users significantly to 0%, respectively, in a dense smallcell deployment (200 smallcells), as evidenced by simulation results.


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    Title :

    Radio Resource Management for Ultra-Dense Smallcell Networks: A Hybrid Spectrum Reuse Approach


    Contributors:
    Lin, ShangJing (author) / Yu, JianGuo (author) / Ni, Wei (author) / Liu, RenPing (author)


    Publication date :

    2017-06-01


    Size :

    423099 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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