Femtocell Selection Scheme for Reducing Unnecessary Handover and Enhancing Downlink QoS in Cognitive Femtocell Networks

  • Hoang Nhu Dong Viettel R&D Institute, Hanoi
  • Hoang Nam Nguyen University of Engineering and Technology, Vietnam National University Hanoi
  • Hoang Trong Minh Post and Telecommunications Institute of Technology
  • Takahiko Saba Chiba Institute of Technology
Keywords: Cognitive radio, femtocell selection, femtocell handover, Quality of Service (QoS).


Femtocell networks have been proposed for indoor communications as the extension of cellular networks for enhancing coverage performance. Because femtocells have small coverage radius, typically from 15 to 30 meters, a femtocell user (FU) walking at low speed can still make several femtocell-to-femtocell handovers during its connection. When performing a femtocell-to-femtocell handover, femtocell selection used to select the target handover femtocell has to be able not only to reduce unnecessary handovers and but also to support FU’s quality of service (QoS). In the paper, we propose a femtocell selection scheme for femtocell-tofemtocell handover, named Mobility Prediction and Capacity Estimation based scheme (MPCE-based scheme), which has the advantages of the mobility prediction and femtocell’s available capacity estimation methods. Performance results obtained by computer simulation show that the proposed MPCE-based scheme can reduce unnecessary femtocell-tofemtocell handovers, maintain low data delay and improve the throughput of femtocell users.

DOI: 10.32913/rd-ict.vol3.no14.536


Nokia Siemens Networks, 2020: Beyond 4G Radio Evolution for the Gigabit Experience. White Paper, 2011.

S. Al-Rubaye, A. Al-Dulaimi, and J. Cosmas, “Cognitive femtocell: Future wireless network for indoor application,” IEEE Vehicular Technology Magazine, vol. 6, no. 1, pp. 44–51, 2011.

G. Horn, 3GPP Femtocells: Architecture and Protocols. QUALCOMM Incorporated, 2010.

QUALCOMM, Femtocell. [Online]. Available: http://www.qualcomm.com/media/documents/files/femtocells-the-nextperformance-leap.pdf

3GPP-Evolved Universal Terrestrial Radio Access Network (E-UTRAN), “Self-configuring and self-optimizing network (SON) use cases and solutions,” TR 36.902, (Release 9), Tech. Rep., 2011.

Q.-P. Yang, J.-W. Kim, and T.-H. Kim, “Mobility prediction and load balancing based adaptive handovers for LTE systems,” International Journal on Computer Science and Engineering, vol. 4, no. 4, pp. 665–674, 2012.

P. Fazio and S. Marano, “A new Markov-based mobility prediction scheme for wireless networks with mobile hosts,” in Proceedings of the 2012 international symposium on Performance evaluation of computer and telecommunication systems (SPECTS). IEEE, 2012, pp. 1–5.

M. Rajabizadeh and J. Abouei, “An efficient femtocell-tofemtocell handover decision algorithm in LTE femtocell networks,” in Proceedings of the 23rd Iranian Conference on Electrical Engineering (ICEE), 2015, pp. 213–218.

D. Barth, S. Bellahsene, and L. Kloul, “Mobility prediction using mobile user profiles,” in Proceedings of the IEEE 19th International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS). IEEE, 2011, pp. 286–294.

T.-H. Kim and J.-W. Kim, “Handover optimization with user mobility prediction for femtocell-based wireless networks,” International Journal of Engineering and Technology (IJET), vol. 5, no. 2, pp. 1829–1837, 2013.

N.-D. Hoang, N.-H. Nguyen, and K. Sripimanwat, “Cell selection schemes for femtocell-to-femtocell handover deploying mobility prediction and downlink capacity monitoring in cognitive femtocell networks,” in IEEE Region 10 Conference (TENCON 2014). IEEE, 2014, pp. 1–5.

K. D. Nguyen, H. N. Nguyen, and H. Morino, “Performance study of channel allocation schemes for beyond 4G cognitive femtocell-cellular mobile networks,” in Proceedings of the IEEE Eleventh International Symposium on Autonomous Decentralized Systems (ISADS). IEEE, 2013, pp. 1–6.

D.-C. Oh, H.-C. Lee, and Y.-H. Lee, “Cognitive radio based femtocell resource allocation,” in Proceedings of the 2010 International Conference on Information and Communication Technology Convergence (ICTC), 2010, pp. 274–279.

R. G. Brown, “Exponential smoothing for predicting demand,” 1956. [Online]. Available: http://legacy.library.ucsf.edu/tid/dae94e00

Intermational Telecommunication Union, “ITU-R Recommendations P. 1238: Propagation data and prediction models for the planning of indoor radio communications systems and radio local area networks in the frequency range 900MHz to 100GHz,” 1977.

Femto forum, “Interference Management in UMTS Femtocells,” Tech. Rep., Dec. 2010.

Regular Articles