Abstract
Effective scheduling in Heterogeneous Networks is key to realising the benefits from enhanced Inter-Cell Interference Coordination. In this paper we address the problem using Grammar-based Genetic Programming. Our solution executes on a millisecond timescale so it can track with changing network conditions. Furthermore, the system is trained using only those measurement statistics that are attainable in real networks. Finally, the solution generalises well with respect to dynamic traffic and variable cell placement. Superior results are achieved relative to a benchmark scheme from the literature, illustrating an opportunity for the further use of Genetic Programming in software-defined autonomic wireless communications networks.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
Note that the constants have been obfuscated to protect intellectual property.
References
3Gpp, December 2014. http://www.3gpp.org/
Google Maps, December 2014
Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2014–2019. Cisco, White Paper (2015)
Small Cell Solutions. Alcatel-Lucent (2015). https://www.alcatel-lucent.com/solutions/small-cells
Alfaro-Cid, E., Sharman, K., Esparcia-Alcázar, A.I.: Genetic programming and serial processing for time series classification. Evol. Comput. 22(2), 265–285 (2014)
Bader-El-Den, M., Fatima, S.: Genetic programming for auction based scheduling. In: Esparcia-Alcázar, A.I., Ekárt, A., Silva, S., Dignum, S., Uyar, A.Ş. (eds.) EuroGP 2010. LNCS, vol. 6021, pp. 256–267. Springer, Heidelberg (2010)
Bhushan, N., Li, J., Malladi, D., Gilmore, R., Brenner, D., Damnjanovic, A., Sukhavasi, R., Patel, C., Geirhofer, S.: Network densification: the dominant theme for wireless evolution into 5G. IEEE Commun. Mag. 52(2), 82–89 (2014)
Bian, Y.Q., Rao, D.: Small Cells Big Opportunities. Global Business Consulting. Huawei Technologies Co., Ltd. (2014)
Brabazon, A., O’Neill, M., McGarraghy, S.: Natural Computing Algorithms. Springer, Berlin (2015)
Conrads, M., Nordin, P., Banzhaf, W.: Speech sound discrimination with genetic programming. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds.) EuroGP 1998. LNCS, vol. 1391, pp. 113–129. Springer, Heidelberg (1998)
Damnjanovic, A., Montojo, J., Wei, Y., Ji, T., Luo, T., Vajapeyam, M., Yoo, T., Song, O., Malladi, D.: A survey on 3GPP heterogeneous networks. IEEE Wirel. Commun. 18(3), 10–21 (2011)
Deb, S., Monogioudis, P., Miernik, J., Seymour, J.P.: Algorithms for enhanced inter-cell interference coordination (eICIC) in LTE HetNets. IEEE/ACM Trans. Netw. (TON) 22(1), 137–150 (2014)
Dempsey, I., O’Neill, M., Brabazon, A.: Grammatical evolution. In: Dempsey, I., O’Neill, M., Brabazon, A. (eds.) Foundations in Grammatical Evolution for Dynamic Environments. SCI, vol. 194, pp. 9–24. Springer, Heidelberg (2009)
Ernst, A.T., Jiang, H., Krishnamoorthy, M., Sier, D.: Staff scheduling and rostering: a review of applications, methods and models. Eur. J. Oper. Res. 153(1), 3–27 (2004)
Fenton, M., Lynch, D., Kucera, S., Claussen, H., O’Neill, M.: Evolving coverage optimisation functions for heterogeneous networks using grammatical genetic programming. In: Proceedings of the 19th International Conference on the Applications of Evolutionary Computation, EvoCOMNET 2016. Springer (2016)
Hansen, J.V.: Genetic search methods in air traffic control. Comput. Oper. Res. 31(3), 445–459 (2004)
Hemberg, E., Ho, L., O’Neill, M., Claussen, H.: A symbolic regression approach to manage femtocell coverage using grammatical genetic programming. In: Proceedings of the 13th Annual Conference Companion on Genetic and Evolutionary Computation, pp. 639–646. ACM (2011)
Hemberg, E., Ho, L., O’Neill, M., Claussen, H.: Evolving femtocell algorithms with dynamic and stationary training scenarios. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds.) PPSN 2012, Part II. LNCS, vol. 7492, pp. 518–527. Springer, Heidelberg (2012)
Hemberg, E., Ho, L., O’Neill, M., Claussen, H.: A comparison of grammatical genetic programming grammars for controlling femtocell network coverage. Genet. Program Evolvable Mach. 14(1), 65–93 (2013)
Ho, L.T., Ashraf, I., Claussen, H.: Evolving femtocell coverage optimization algorithms using genetic programming. In: 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 2132–2136. IEEE (2009)
Jakobović, D., Marasović, K.: Evolving priority scheduling heuristics with genetic programming. Appl. Soft Comput. 12(9), 2781–2789 (2012)
Jiang, L., Lei, M.: Resource allocation for eICIC scheme in heterogeneous networks. In: 2012 IEEE 23rd International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC), pp. 448–453. IEEE (2012)
Jones, A., Rabelo, L.C., Sharawi, A.T.: Survey of job shop scheduling techniques In: Wiley Encyclopedia of Electrical and Electronics Engineering (1999)
López-Pérez, D., Claussen, H.: Duty cycles and load balancing in hetnets with eICIC almost blank subframes. In: 2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops), pp. 173–178. IEEE (2013)
Mckay, R.I., Hoai, N.X., Whigham, P.A., Shan, Y., O’Neill, M.: Grammar-based genetic programming: a survey. Genet. Program Evolvable Mach. 11(3–4), 365–396 (2010)
Pang, J., Wang, J., Wang, D., Shen, G., Jiang, Q., Liu, J.: Optimized time-domain resource partitioning for enhanced inter-cell interference coordination in heterogeneous networks. In: 2012 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1613–1617. IEEE (2012)
Shannon, C.E.: Communication in the presence of noise. Proc. IRE 37(1), 10–21 (1949)
Sun, J., Modiano, E., Zheng, L.: Wireless channel allocation using an auction algorithm. IEEE J. Sel. Areas Commun. 24(5), 1085–1096 (2006)
Tall, A., Altman, Z., Altman, E.: Self organizing strategies for enhanced ICIC (eICIC). In: 2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), pp. 318–325. IEEE (2014)
Weber, A., Stanze, O.: Scheduling strategies for HetNets using eICIC. In: 2012 IEEE International Conference on Communications (ICC), pp. 6787–6791. IEEE (2012)
Yang, S., Ong, Y.S., Jin, Y.: Evolutionary Computation in Dynamic and Uncertain Environments. Springer Science & Business Media, New York (2007)
Acknowledgement
This research is based upon works supported by the Science Foundation Ireland under grant 13/IA/1850.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Lynch, D., Fenton, M., Kucera, S., Claussen, H., O’Neill, M. (2016). Scheduling in Heterogeneous Networks Using Grammar-Based Genetic Programming. In: Heywood, M., McDermott, J., Castelli, M., Costa, E., Sim, K. (eds) Genetic Programming. EuroGP 2016. Lecture Notes in Computer Science(), vol 9594. Springer, Cham. https://doi.org/10.1007/978-3-319-30668-1_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-30668-1_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30667-4
Online ISBN: 978-3-319-30668-1
eBook Packages: Computer ScienceComputer Science (R0)