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New Propagation Model Optimization Approach based on Particles Swarm Optimization Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 118 - Number 10 |
| Year of Publication: 2015 |
| Authors: Deussom Djomadji Eric Michel, Tonye Emmanuel |
10.5120/20785-3430
|
Deussom Djomadji Eric Michel, Tonye Emmanuel . New Propagation Model Optimization Approach based on Particles Swarm Optimization Algorithm. International Journal of Computer Applications. 118, 10 ( May 2015), 39-47. DOI=10.5120/20785-3430
Abstract
Propagation models are keys components of coverage planning. With the deployment of 4G network worldwide, operators need to plan the coverage of their network efficiently, in order to minimize cost and improve the quality of service. In this paper, the standard model K factors is taken into account to develop a method for tuning propagation models based on particle swarm optimization algorithm. The data are collected on the existing CDMA2000 1X-EVDO rev B network in the town of Yaoundé, capital of Cameroon. The root mean squared error (RMSE) between actual measurements and radio data obtained from the prediction model developed is used to test and validate the technique. The values of the RMSE obtained by the new model and those obtained by the standard model of OKUMURA HATA in urban area are also compared. Through the comparison of RMSE from optimized model and OKUMURA HATA, it can be concluded that the new model developed using particle swarm optimization performs better than the OKUMURA HATA model and is more accurate. The new model is also more representative of the local environment and also similar to the optimized model obtained when using linear regression method. This method can be applied anywhere to optimize existing propagation model.
References
- Deussom E. and Tonye E. «New Approach for Determination of Propagation Model Adapted To an Environment Based On Genetic Algorithms: Application to the City Of Yaoundé, Cameroon», IOSR Journal of Electrical and Electronics Engineering, Volume 10, pages 48-49, 2015.
- R. Mardeni and K. F. Kwan «Optimization of Hata prediction model in suburban area in Malaysia» Progress In Electromagnetics Research C, Vol. 13, pages 91-106, 2010.
- Chhaya Dalela, and all « tuning of Cost231 Hata modele for radio wave propagation prediction », Academy & Industry Research Collaboration Center, May 2012.
- Medeisis and Kajackas « The tuned Okumura Hata model in urban and rural zones at Lituania at 160, 450, 900 and 1800 MHz bands », Vehicular Technology Conference Proceedings, VTC 2000-Spring Tokyo. IEEE 51st Volume 3 Pages 1815 – 1818, 2000.
- Deussom E. and Tonye E.
- worked on «Optimization of Okumura Hata Model in 800MHz based on Newton Second Order algorithm. Case of Yaoundé, Cameroon", IOSR Journal of Electrical and Electronics Engineering, Volume 10, issue2 Ver I, pages 16-24, 2015.
- MingjingYang; and al « A Linear Least Square Method of Propagation Model Tuning for 3G Radio Network Planning », Natural Computation, 2008. ICNC '08. Fourth International Conference on Vol. 5, pages 150 – 154, 2008.
- Chen, Y. H. and Hsieh, K. L « A Dual Least-Square Approach of Tuning Optimal Propagation Model for existing 3G Radio Network », Vehicular Technology Conference, 2006. VTC 2006-Spring. IEEE 63rd Vol. 6, pages 2942 – 2946, 2006.
- Allam Mousa, Yousef Dama and Al «Optimizing Outdoor Propagation Model based on Measurements for Multiple RF Cell ». International Journal of Computer Applications (0975 – 8887) Volume 60– No. 5, December 2012
- HUAWEI Technologies, CW Test and Propagation Model Tuning Report , page 7, 20 Mars 2014.
- HUAWEI Technologies, BTS3606CE&BTS3606AC and 3900 Series CDMA Product Documentation, pages 138-139.
- Standard Propagation Model Calibration guide, Avril 2004, page 23.
- Riccardo Poli, James Kennedy, and Tim Blackwell. Particle swarm optimization. Swarm Intelligence, pages: 33–57, 2007.
- Russell C. Eberhart, Yuhui Shi, and James Kennedy. Swarm Intelligence. The Morgan Kaufmann Series in Artificial Intelligence. Morgan Kaufmann, San Francisco, CA, USA, 2001.
- Maurice Clerc and James Kennedy The particle swarm - explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evolutionary Computation, 6(1):58–73, 2002.
- HUAWEI Technologies, Radio Transmission Theory, page 24, 11 Nov 2005.
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