ICTACT Journal on Communication Technology

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

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
     

   Subscribe/Renew Journal


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.
Subscription Login to verify subscription
User
Notifications
Font Size

  • V. Chandrasekhar, J.G. Andrews and A. Gatherer, “Femtocell Networks: A Survey”, IEEE Communications Magazine, Vol. 46, No. 9, pp. 59-67, 2008.

  • D.L Opez-Perez, A. Valcarce, G. De La Roche and J. Zhang, “OFDMA femtocells: A Roadmap on Interference Avoidance”, IEEE Communications Magazine, Vol. 47, No. 9, pp. 41-48, 2009.

  • Femtoforum, “Interference Management in OFDMA Femtocells”, Available at: www.femtoforum.org, Accessed on 2010.

  • V. Chandrasekhar, J. Andrews, T. Muharemovic, Z. Shen and A. Gatherer, “Power Control in Two-Tier Femtocell Networks”, IEEE Transactions on Wireless Communications, Vol. 8, No. 8, pp. 4316-4328, 2009.

  • 3GPP, “Evolved Universal Terrestrial Radio Access (E-UTRA); FDD Home eNode B (HeNB) Radio Frequency (RF) Requirements Analysis”, Available at: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=2586, Accessed on 2010.

  • Hae Beom Jung and Duk Kyung Kim, “Power Control of Femtocells Based on Max-Min Fairness in Heterogeneous Networks”, IEEE Communication Letters, Vol. 17, No. 7, pp. 1372-1375, 2013.

  • T.U. Hassan, F. Gao, B. Jalal and S. Arif, “Interference Management in Femtocells by the Adaptive Network Sensing Power Control Technique”, Future Internet, Vol. 10, No. 3, pp. 1-9, 2018.

  • S. Alotaibi and R. Akl, “Range-Based Scheme for Adjusting Transmission Power of Femtocell in Co-Channel Deployment”, International Journal of Interdisciplinary Telecommunications and Networking, Vol. 10, pp. 14-24, 2018.

  • H. Zhang, W. Zheng, X. Chu, X. Wen, M. Tao, A. Nallanathan and D. Lopez-Perez, “Joint Subchannel and Power Allocation in Interference Limited OFDMA Femtocells with Heterogeneous QoS Guarantee”, Proceedings of IEEE International Conference on Global Telecommunication, pp. 4794-4799, 2013.

  • Roohollah Amiri, Mojtaba Ahmadi Almasi, Jeffrey G. Andrews and Hanib Mehrpouyan, “Reinforcement Learning for Self Organization and Power Control of Two-Tier Heterogeneous Networks”, IEEE Transactions on Wireless Communications, Vol. 18, No. 8, pp. 3933-3947, 2019.

  • T. Leanh, N.H. Tran, S. Lee, E.N. Huh, Z. Han and C.S. Hong, “Distributed Power and Channel Allocation for Cognitive Femtocell Network Using a Coalitional Game in Partition-Form Approach”, IEEE Transactions on Vehicular Technology, Vol. 66, No. 4, pp. 3475-3490, 2017.

  • Sundeep Rangan and Ritesh Madan, “Belief Propagation Methods for Intercell Interference Coordination in Femtocell Networks”, IEEE Journal on Selected Areas in Communications, Vol. 30, No. 3, pp. 631-640, 2012.

  • S. Park, W. Seo, S. Choi and D. Hong, “A Beamforming Codebook Restriction for Cross-Tier Interference Coordination in Two-Tier Femtocell Networks”, IEEE Transactions on Vehicular Technology, Vol. 60, No. 4, pp. 1651-1663, 2011.

  • S. Park, W. Seo, Y. Kim, S. Lim and D. Hong, “Beam Subset Selection Strategy for Interference Reduction in Two Tier Femtocell Networks”, IEEE Transactions on Wireless Communications, Vol. 9, No. 11, pp. 3440-3449, 2010.

  • Nirmala Sivaraj and Padmaloshani Palanisamy, “Downlink Interference Analysis in LTE-Femtocell Networks”, Journal of Networks, Vol. 10, No. 5, pp. 294-301, 2015.

  • Houman Zarrinkoub, “Understanding LTE with MATLAB from Mathematical Modeling to Simulation and Prototyping”, 1st Edition, John Wiley Publications, 2014.

  • David B. Fogel, Derong Liu and James M. Keller, “Fundamentals of Computational Intelligence: Neural Networks, Fuzzy Systems, and Evolutionary Computation”, 1st Edition, John Wiley Publications, 2016.


Abstract Views: 261

PDF Views: 0




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

Abstract Views: 261  |  PDF Views: 0

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