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Reseach Article
Neural-encoded Fuzzy Models for Load Balancing in 3GPP LTE
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 4 - Number 1 |
| Year of Publication: 2012 |
| Authors: Aderemi A. Atayero, Matthew K. Luka, Adeyemi A. Alatishe |
10.5120/ijais12-450628
|
Aderemi A. Atayero, Matthew K. Luka, Adeyemi A. Alatishe . Neural-encoded Fuzzy Models for Load Balancing in 3GPP LTE. International Journal of Applied Information Systems. 4, 1 ( September 2012), 34-40. DOI=10.5120/ijais12-450628
Abstract
Post third generation (3G) broadband mobile networks such as HSPA+, LTE and LTE-Advanced offer improved spectral efficiency and higher data rates using innovative technologies such as relay nodes and femto cells. In addition, these networks are normally deployed for parallel operation with existing heterogeneous networks. This increases the complexity of network management and operations, which reflects in higher operational and capital cost. In order to address these challenges, self-organizing network operations were envisioned for these next generation networks. For LTE in particular, Self-organizing networks operations were built into the specifications for the radio access network. Load balancing is a key self-organizing operation aimed at ensuring an equitable distribution of users in the network. Several iterative techniques have been adopted for load balancing. However, these iterative techniques require precision, rigor and certainty, which carry a computational cost. Retrospect, these techniques use load indicators to achieve load balancing. This paper proposes two neural encoded fuzzy models, developed from network simulation for load balancing. The two models use both load indicators and key performance indicators for a more informed and intuitive load balancing. The result of the model checking and testing satisfactorily validates the model.
References
- Chandrasekhar V. , Andrews J. , and Gatherer A. , 2008. "Femtocell networks: a survey," IEEE Communications Magazine, Vol. 46, No. 9, pg. 59-67.
- Cheolhee Park et al. 2012. "LTE-advanced modem design: challenges and perspectives," IEEE Communications Magazine, Vol. 50, No. 2, pg. 178-186
- Radio-Electronics. 2012. Self-Organizing Networks [online]. Available: http://www. radio-electronics. com.
- 3GPP TS 36. 300 version, 2011. "LTE; Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Overall description; Stage 2", Technical Specification, version 10. 4. 0 Release 10
- Stefania Sesia, Issam Toufik and Matthew Baker, 2009. "LTE – The UMTS Long Term Evolution: From Theory to Practice", 1st edition, John Wiley & Sons, Ltd. , West Sussex, UK.
- ETSI TR 136 902, 2010. "LTE; Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Self-configuring and self-optimizing network (SON) use cases and solutions," Technical Specification, version 9. 0. 0 Release 9.
- Andreas Lobinger, Szymon Stefanski, 2010. Thomas Jansen and Irina Balan, "Load Balancing in Downlink LTE Self-Optimizing Networks," IEEE 71st VTC 2010, Taipei, Taiwan.
- Hao Wang et al. 2010. "Dynamic Load Balancing in 3GPP LTE Multi-Cell Networks with Heterogenous services", ICST Conference, Beijing.
- H. Wang, 2010. "Dynamic Load Balancing and Throughput Optimization in 3GPP LTE Networks", IWCMC 2010, Caen, France.
- Manfred R. , Jakob B. , Paul A. , and Wilfried W. , 2009. "Ruled-based Algorithms for Self-x Functionalities in Radio Access Networks," Conference Proceedings of ICT-Mobile Summit.
- Rodriguez J. , de la Bandera I. , Munoz P. , and Barco R. , 2011. "Load Balancing in a Realistic Urban Scenario for LTE Networks," IEEE 73rd Vehicular Technology Conference (VTC Spring), pp. 1-5
- Klaus Wehrle, Mesut Gunes and James Gross, 2010. "Modelling and tools for Network Simulation," Springer-Verlag, Germany, pg. 173-190.
- ETSI TR 136 211, 2012. "LTE; Evolved Universal Terrestrial Radio Access (E-UTRA); Radio Frequency (RF) system scenarios," Technical Report Version 8. 2. 0, Retrieved Feb. , 20, 2012, from http://www. 3gpp. org.
- Aderemi A. Atayero and Matthew K. Luka, 2012. "Adaptive Neuro-Fuzzy Inference System for Load Balancing In 3GPP LTE," (IJARAI) International Journal of Advanced Research in Artificial Intelligence, Vol. 1, No. 1, pp. 11-16.
- Andreas Lobinger, Szymon Stefanski, 2010. Thomas Jansen and Irina Balan, "Load Balancing in Downlink LTE Self-Optimizing Networks," IEEE 71st VTC 2010, Taipei, Taiwan.
- Lin Zhang et al. 2011. "A Two-layer Mobility Load Balancing in LTE Self-Organization Networks," 13th IEEE Conf. on Information Technology, pp. 925-929.
- Ingo Viering, Andreas Lobinger and Szymon Stefanski, 2010. "Efficient Uplink Modeling for Dynamic System-Level Simulations of Cellular and Mobile Networks," EURASIP Journal on Wireless Communications and Networking, pp. 1-15.
- R. Jain, D. M Chiu and W. Hawe, 1984. "A Quantitative Measure of Fairness and Discrimination for Resource Allocation in Shared Systems," Technical Report, Digital Equipment Corporation, DEC-TR-301.
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