Coordinated Multi-Point (CoMP) processing is one of the promising methods to mitigate the intra- cluster interference in cellular systems, to improve the average Signal-to-Interference-plus- Noise Ratio (SINR), and to increase the overall spectral efficiency. Such method, however, does not take any action to mitigate the inter-cluster interference, which leads to poor performance for cluster-edge Mobile Stations (MSs) and, consequently, to unfairness in service provision. In the context of Cloud Radio Access Network (C- RAN) - a new centralized paradigm for wireless cellular networks in which Base Stations (BSs) are physically unbundled into Virtual Base Stations (VBSs) and Remote Radio Heads (RRHs) - an innovative solution, called Dynamic Joint Processing (DJP), is proposed to mitigate both intra- and inter-cluster interference so to improve performance of cluster-edge MSs. A dynamic clustering approach is presented in which, for each subcarrier, a virtual cluster is defined, and its size is dynamically changed based on the position of the MSs. Simulation results confirm the validity of our approach.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    DJP: Dynamic Joint Processing for Interference Cancellation in Cloud Radio Access Networks


    Contributors:


    Publication date :

    2015-09-01


    Size :

    531532 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Joint Scheduling and Beamforming via Cloud-Radio Access Networks Coordination

    Douik, Ahmed / Dahrouj, Hayssam / Al-Naffouri, Tareq Y. et al. | IEEE | 2018


    Joint Hybrid Backhaul and Access Links Design in Cloud-Radio Access Networks

    Dhifallah, Oussama / Dahrouj, Hayssam / Al-Naffouri, Tareq Y. et al. | IEEE | 2015


    Joint Clusterization and Power Allocation for Cloud Radio Access Networks

    Tsou, Yao-Chun / Li, Pei-Rong / Chu, Jui-Hung et al. | IEEE | 2015