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Neural Networks based Adaptive Small Cell Base Station Transmit Power Control for Interference Mitigation in Heterogeneous Networks


Affiliations
1 Department of Electronics and Communication, Muthayammal Engineering College, India
2 Department of Electronics and Communication, Sri Eshwar College of Engineering, India
     

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Heterogeneous networking of small cells such as pico/femtocells over the existing macrocell network is believed to augment the data rate requirement in forthcoming years. Closed access operation of femtocell base station (FBS) and shared spectrum assignment in the two-tier macro-femtocell network leads to unacceptable deterioration in achieved data rate of femtocell users. In this work, application of computationally efficient neural network to perform adaptive FBS transmit power control is proposed for mitigation of interference in two-tier heterogeneous network formed by macro-femtocells and to improve the Quality of Service perceived by femtocell users. A Neuro-controller is designed to regulate the FBS transmission power based on the channel quality indicator measurement report sent by user equipment. Since the proposed power control strategy employs the channel side information already available in the existing network, there would not be any signaling overhead to mitigate the co-tier interference. Simulation results validate the effectiveness of the proposed power control strategy which provides significant improvement in achieved data rate of femtocell users and prevents them from outage.

Keywords

Heterogeneous Networks, Small Cells, LTE, Neural Networks, Interference Management, Power Control.
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  • Neural Networks based Adaptive Small Cell Base Station Transmit Power Control for Interference Mitigation in Heterogeneous Networks

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Authors

Padmaloshani Palanisamy
Department of Electronics and Communication, Muthayammal Engineering College, India
Nirmala Sivaraj
Department of Electronics and Communication, Sri Eshwar College of Engineering, India

Abstract


Heterogeneous networking of small cells such as pico/femtocells over the existing macrocell network is believed to augment the data rate requirement in forthcoming years. Closed access operation of femtocell base station (FBS) and shared spectrum assignment in the two-tier macro-femtocell network leads to unacceptable deterioration in achieved data rate of femtocell users. In this work, application of computationally efficient neural network to perform adaptive FBS transmit power control is proposed for mitigation of interference in two-tier heterogeneous network formed by macro-femtocells and to improve the Quality of Service perceived by femtocell users. A Neuro-controller is designed to regulate the FBS transmission power based on the channel quality indicator measurement report sent by user equipment. Since the proposed power control strategy employs the channel side information already available in the existing network, there would not be any signaling overhead to mitigate the co-tier interference. Simulation results validate the effectiveness of the proposed power control strategy which provides significant improvement in achieved data rate of femtocell users and prevents them from outage.

Keywords


Heterogeneous Networks, Small Cells, LTE, Neural Networks, Interference Management, Power Control.

References