Integrated Grey Rational Analysis-Standard Deviation Method for Handover in Heterogeneous Networks
The dense deployment of small cells is a promising
solution to enhance the coverage and capacity of the
heterogeneous networks (HetNets). However, the unplanned
deployment could bring new challenges to the network ranging
from interference, unnecessary handovers and handover failures.
This will cause a degradation in the quality of service (QoS)
delivered to the end user. In this paper, we propose an integrated
Grey Rational Analysis Standard Deviation based handover
method (GRA-SD) for HetNet. The proposed method integrates
the Standard Deviation (SD) technique to acquire the weight of
the handover metrics and the GRA method to select the best
handover base station. The performance of the GRA-SD method
is evaluated and compared with the traditional Multiple Attribute
Decision Making (MADM) methods including Simple Additive
Weighting (SAW) and VIKOR methods. Results reveal that the
proposed method has outperformed the other methods in terms of
minimizing the number of frequent unnecessary handovers and
handover failures, in addition to improving the energy efficiency.
[1] A. M. Akhtar, X. Wang, and L. Hanzo, “Synergistic spectrum
sharing in 5g hetnets: A harmonized sdn-enabled approach,” IEEE
Communications Magazine, vol. 54, no. 1, pp. 40–47, 2016.
[2] X. Chu, D. L´opez-P´erez, Y. Yang, and F. Gunnarsson, Heterogeneous
Cellular Networks: Theory, Simulation and Deployment. Cambridge
University Press, 2013.
[3] G. T. 36.839, “Evolved universal terrestrial radio access (eutra); mobility
enhancements in heterogeneous networks,” 2013.
[4] M. Alhabo and L. Zhang, “Unnecessary handover minimization in
two-tier heterogeneous networks,” in Wireless On-demand Network
Systems and Services (WONS), 2017 13th Annual Conference on. IEEE,
2017, pp. 160–164.
[5] M. Alhabo, L. Zhang, and N. Nawaz, “A trade-off between unnecessary
handover and handover failure for heterogeneous networks,” in European
Wireless 2017; 23th European Wireless Conference; Proceedings of.
VDE, 2017.
[6] M. Alhabo, L. Zhang, and O. Oguejiofor, “Inbound handover
interference-based margin for load balancing in heterogeneous
networks,” in Wireless Communication Systems (ISWCS), 2017
International Symposium on. IEEE, 2017, pp. 1–6.
[7] K. Aghababaiyan and B. Maham, “Qos-aware downlink radio
resource management in ofdma-based small cells networks,” IET
Communications, vol. 12, no. 4, pp. 441–448, 2017.
[8] M. Yassin, S. Lahoud, M. Ibrahim, K. Khawam, D. Mezher, and
B. Cousin, “Cooperative resource management and power allocation for
multiuser ofdma networks,” IET Communications, vol. 11, no. 16, pp.
2552–2559, 2017.
[9] S. Wu, Z. Zeng, and H. Xia, “Coalition-based sleep mode and power
allocation for energy efficiency in dense small cell networks,” IET
Communications, vol. 11, no. 11, pp. 1662–1670, 2017.
[10] M. Alhabo and L. Zhang, “Load-dependent handover margin for
throughput enhancement and load balancing in hetnets,” IEEE Access,
vol. 6, pp. 67 718–67 731, 2018.
[11] A. Huszak and S. Imre, “Eliminating rank reversal phenomenon in
gra-based network selection method,” in Communications (ICC), 2010
IEEE International Conference on. IEEE, 2010, pp. 1–6.
[12] H. A. Al-Kashoash, H. M. Amer, L. Mihaylova, and A. H.
Kemp, “Optimization based hybrid congestion alleviation for 6lowpan
networks,” IEEE Internet of Things Journal, 2017.
[13] L. Wang and G.-S. G. Kuo, “Mathematical modeling for network
selection in heterogeneous wireless networksa tutorial,” IEEE
Communications Surveys & Tutorials, vol. 15, no. 1, pp. 271–292,
2013.
[14] R. Tawil, G. Pujolle, and O. Salazar, “A vertical handoff decision scheme
in heterogeneous wireless systems,” in Vehicular Technology Conference,
2008. VTC Spring 2008. IEEE. IEEE, 2008, pp. 2626–2630.
[15] C.-H. Yeh, “A problem-based selection of multi-attribute
decision-making methods,” International Transactions in Operational
Research, vol. 9, no. 2, pp. 169–181, 2002.
[16] L. Mohamed, C. Leghris, and A. Abdellah, “A hybrid approach
for network selection in heterogeneous multi-access environments,”
in New Technologies, Mobility and Security (NTMS), 2011 4th IFIP
International Conference on. IEEE, 2011, pp. 1–5.
[17] M. Alhabo and L. Zhang, “Multi-criteria handover using modified
weighted topsis methods for heterogeneous networks,” IEEE Access,
vol. 6, pp. 40 547–40 558, 2018.
[18] J. Ariyakhajorn, P. Wannawilai, and C. Sathitwiriyawong, “A
comparative study of random waypoint and gauss-markov mobility
models in the performance evaluation of manet,” in Communications and
Information Technologies, 2006. ISCIT’06. International Symposium on.
IEEE, 2006, pp. 894–899.
[19] J. Zhang and G. De la Roche, Femtocells: technologies and deployment.
John Wiley & Sons, 2011.
[20] Q. Europe, “Hnb and hnb-macro propagation models,” 3GPP
R4–071617, Oct, 2007.
[21] G. L. St¨uber, Principles of mobile communication. Springer Science
& Business Media, 2011.
[22] S. Singh and J. G. Andrews, “Rate distribution in heterogeneous
cellular networks with resource partitioning and offloading,” in Global
Communications Conference (GLOBECOM), 2013 IEEE. IEEE, 2013,
pp. 3796–3801.
[23] Y.-M. Wang and Y. Luo, “Integration of correlations with standard
deviations for determining attribute weights in multiple attribute decision
making,” Mathematical and Computer Modelling, vol. 51, no. 1, pp.
1–12, 2010.
[24] MathWorks, “Counting the floating point operations (flops),” 2015.
[Online]. Available: https://uk.mathworks.com
[25] D. Lopez-Perez, I. Guvenc, and X. Chu, “Mobility management
challenges in 3gpp heterogeneous networks,” IEEE Communications
Magazine, vol. 50, no. 12, 2012.
[26] X. Xiao, X. Tao, Y. Jia, and J. Lu, “An energy-efficient hybrid
structure with resource allocation in ofdma networks,” in Wireless
Communications and Networking Conference (WCNC), 2011 IEEE.
IEEE, 2011, pp. 1466–1470.
[1] A. M. Akhtar, X. Wang, and L. Hanzo, “Synergistic spectrum
sharing in 5g hetnets: A harmonized sdn-enabled approach,” IEEE
Communications Magazine, vol. 54, no. 1, pp. 40–47, 2016.
[2] X. Chu, D. L´opez-P´erez, Y. Yang, and F. Gunnarsson, Heterogeneous
Cellular Networks: Theory, Simulation and Deployment. Cambridge
University Press, 2013.
[3] G. T. 36.839, “Evolved universal terrestrial radio access (eutra); mobility
enhancements in heterogeneous networks,” 2013.
[4] M. Alhabo and L. Zhang, “Unnecessary handover minimization in
two-tier heterogeneous networks,” in Wireless On-demand Network
Systems and Services (WONS), 2017 13th Annual Conference on. IEEE,
2017, pp. 160–164.
[5] M. Alhabo, L. Zhang, and N. Nawaz, “A trade-off between unnecessary
handover and handover failure for heterogeneous networks,” in European
Wireless 2017; 23th European Wireless Conference; Proceedings of.
VDE, 2017.
[6] M. Alhabo, L. Zhang, and O. Oguejiofor, “Inbound handover
interference-based margin for load balancing in heterogeneous
networks,” in Wireless Communication Systems (ISWCS), 2017
International Symposium on. IEEE, 2017, pp. 1–6.
[7] K. Aghababaiyan and B. Maham, “Qos-aware downlink radio
resource management in ofdma-based small cells networks,” IET
Communications, vol. 12, no. 4, pp. 441–448, 2017.
[8] M. Yassin, S. Lahoud, M. Ibrahim, K. Khawam, D. Mezher, and
B. Cousin, “Cooperative resource management and power allocation for
multiuser ofdma networks,” IET Communications, vol. 11, no. 16, pp.
2552–2559, 2017.
[9] S. Wu, Z. Zeng, and H. Xia, “Coalition-based sleep mode and power
allocation for energy efficiency in dense small cell networks,” IET
Communications, vol. 11, no. 11, pp. 1662–1670, 2017.
[10] M. Alhabo and L. Zhang, “Load-dependent handover margin for
throughput enhancement and load balancing in hetnets,” IEEE Access,
vol. 6, pp. 67 718–67 731, 2018.
[11] A. Huszak and S. Imre, “Eliminating rank reversal phenomenon in
gra-based network selection method,” in Communications (ICC), 2010
IEEE International Conference on. IEEE, 2010, pp. 1–6.
[12] H. A. Al-Kashoash, H. M. Amer, L. Mihaylova, and A. H.
Kemp, “Optimization based hybrid congestion alleviation for 6lowpan
networks,” IEEE Internet of Things Journal, 2017.
[13] L. Wang and G.-S. G. Kuo, “Mathematical modeling for network
selection in heterogeneous wireless networksa tutorial,” IEEE
Communications Surveys & Tutorials, vol. 15, no. 1, pp. 271–292,
2013.
[14] R. Tawil, G. Pujolle, and O. Salazar, “A vertical handoff decision scheme
in heterogeneous wireless systems,” in Vehicular Technology Conference,
2008. VTC Spring 2008. IEEE. IEEE, 2008, pp. 2626–2630.
[15] C.-H. Yeh, “A problem-based selection of multi-attribute
decision-making methods,” International Transactions in Operational
Research, vol. 9, no. 2, pp. 169–181, 2002.
[16] L. Mohamed, C. Leghris, and A. Abdellah, “A hybrid approach
for network selection in heterogeneous multi-access environments,”
in New Technologies, Mobility and Security (NTMS), 2011 4th IFIP
International Conference on. IEEE, 2011, pp. 1–5.
[17] M. Alhabo and L. Zhang, “Multi-criteria handover using modified
weighted topsis methods for heterogeneous networks,” IEEE Access,
vol. 6, pp. 40 547–40 558, 2018.
[18] J. Ariyakhajorn, P. Wannawilai, and C. Sathitwiriyawong, “A
comparative study of random waypoint and gauss-markov mobility
models in the performance evaluation of manet,” in Communications and
Information Technologies, 2006. ISCIT’06. International Symposium on.
IEEE, 2006, pp. 894–899.
[19] J. Zhang and G. De la Roche, Femtocells: technologies and deployment.
John Wiley & Sons, 2011.
[20] Q. Europe, “Hnb and hnb-macro propagation models,” 3GPP
R4–071617, Oct, 2007.
[21] G. L. St¨uber, Principles of mobile communication. Springer Science
& Business Media, 2011.
[22] S. Singh and J. G. Andrews, “Rate distribution in heterogeneous
cellular networks with resource partitioning and offloading,” in Global
Communications Conference (GLOBECOM), 2013 IEEE. IEEE, 2013,
pp. 3796–3801.
[23] Y.-M. Wang and Y. Luo, “Integration of correlations with standard
deviations for determining attribute weights in multiple attribute decision
making,” Mathematical and Computer Modelling, vol. 51, no. 1, pp.
1–12, 2010.
[24] MathWorks, “Counting the floating point operations (flops),” 2015.
[Online]. Available: https://uk.mathworks.com
[25] D. Lopez-Perez, I. Guvenc, and X. Chu, “Mobility management
challenges in 3gpp heterogeneous networks,” IEEE Communications
Magazine, vol. 50, no. 12, 2012.
[26] X. Xiao, X. Tao, Y. Jia, and J. Lu, “An energy-efficient hybrid
structure with resource allocation in ofdma networks,” in Wireless
Communications and Networking Conference (WCNC), 2011 IEEE.
IEEE, 2011, pp. 1466–1470.
@article{"International Journal of Electrical, Electronic and Communication Sciences:80280", author = "Mohanad Alhabo and Naveed Nawaz and Mahmoud Al-Faris", title = "Integrated Grey Rational Analysis-Standard Deviation Method for Handover in Heterogeneous Networks", abstract = "The dense deployment of small cells is a promising
solution to enhance the coverage and capacity of the
heterogeneous networks (HetNets). However, the unplanned
deployment could bring new challenges to the network ranging
from interference, unnecessary handovers and handover failures.
This will cause a degradation in the quality of service (QoS)
delivered to the end user. In this paper, we propose an integrated
Grey Rational Analysis Standard Deviation based handover
method (GRA-SD) for HetNet. The proposed method integrates
the Standard Deviation (SD) technique to acquire the weight of
the handover metrics and the GRA method to select the best
handover base station. The performance of the GRA-SD method
is evaluated and compared with the traditional Multiple Attribute
Decision Making (MADM) methods including Simple Additive
Weighting (SAW) and VIKOR methods. Results reveal that the
proposed method has outperformed the other methods in terms of
minimizing the number of frequent unnecessary handovers and
handover failures, in addition to improving the energy efficiency.", keywords = "Energy efficiency, handover, HetNets, MADM, small cells.", volume = "15", number = "5", pages = "118-7", }
