Deep Learning for Tuning Optical Beamforming Networks

Herminarto Nugroho, Wahyu Kunto Wibowo, Aulia Rahma Annisa, Hanny Megawati Rosalinda

Abstract


In communication between planes and satellites, Optical Beamforming Networks (OBFNs), which rely on many small and flat Phased Array Antennas (PAAs), need to be tuned in order to receive signals from specific angles. In this paper, we develop a deep neural network representation of tuning OBFNs. The problem of tuning an OBFN is in many aspects similar to training a deep neural network. We present a way to exploit the special structure of OBFNs into deep neural network and an algorithm for tuning OBFNs based on feedback that can be easily measured in real system. Training data, which consists of full signals, can be measured, and therefore is used in this paper. For pilot signals, the desired signal is known explicitly. Given the configuration of OBFNs and all nominal parameters required, it was verified in simulation that the deep neural network can be used to tune large scale OBFNs for any desired delays.

Keywords


artificial neural network; deep learning; optical beamforming network; optical ring resonator; phased array antenna

References


D. Cheng, Field and Wave Electromagnetics, ser. The Addison-Wesley Series in Electrical Engineering. Addison-Wesley Publishing Company, 1989.

L. Zhuang, “Ring resonator-based broadband photonic beamformer for phased array antennas,” Ph.D. dissertation, University of Twente, November 2010.

T. Wilson, K. Rohlfs, and S. Hüttemeister, Tools of Radio Astronomy, ser. Astronomy and Astrophysics Library. Springer Berlin Heidelberg, 2013.

C. Balanis, Modern Antenna Handbook. Wiley, 2008.

R. C. Hansen, Phased Array Antennas. John Wiley & Sons, 2009, vol. 213.

A. Meijerink, C. Roeloffzen, L. Zhuang, D. Marpaung, R. Heideman, A. Borreman, and W. van Etten, “Phased array antenna steering using a ring resonator-based optical beam forming network,” in Proceedings of the IEEE Symposium on Communications and Vehicular Technology, Liege, Belgium, November 2006, pp. 7–12.

A. Meijerink, C. Roeloffzen, R. Meijerink, L. Zhuang, D. Marpaung, M. Bentum, M. Burla, J. Verpoorte, P. Jorna, A. Hulzinga, and W. van Etten, Novel ring resonatorbased integrated photonic beamformer for broadband phased array receive antennas - Part I: Design and performance analysis, Journal of Lightwave Technology, vol. 28, no. 1, pp. 3–18, January 2010.

G. Lenz, B. Eggleton, C. K. Madsen, and R. Slusher, “Optical delay lines based on optical filters,” IEEE Journal of Quantum Electronics, vol. 37, no. 4, pp. 525–532, 2001.

L. Zhuang, C. G. Roeloffzen, and W. Van Etten, “Continuously tunable optical delay line,” in Proceedings of the IEEE Symposium on Communications and Vehicular Technology, Twente, The Netherlands, November 2005, paper P23.

L. Zhuang, “Time-delay properties of optical ring resonators,” Master’s thesis, University of Twente, 2005.

M. S. Bazaraa, H. D. Sherali, and C. M. Shetty, Nonlinear Programming: Theory and Algorithms. John Wiley & Sons, 2013.

J. C. Boot et al., Quadratic Programming: Algorithms, Anomalies, Applications, ser. Studies in Mathematical and Managerial Economics. Amsterdam: North. Holland Publishing Company, 1964.

A. García García et al., Optical phase synchronization in coherent optical beamformers for phased array receive antennas, Master’s thesis, University of Twente, Enschede, February 2009.

R. Blokpoel, Staggered delay tuning algorithms for ring resonators in optical beamforming networks, Master’s thesis, University of Twente, August 2007. [Online]. Available: http://doc.utwente.nl/62127/

Wiharto, W., Kusnanto, H., & Herianto, H. (2017). Hybrid System of Tiered Multivariate Analysis and Artificial Neural Network for Coronary Heart Disease Diagnosis. International Journal of Electrical and Computer Engineering (IJECE), 7(2), 1023-1031.

Boukadida, S., Gdaim, S., & Mtiba, A. (2017). Sensor Fault Detection and Isolation Based on Artificial Neural Networks and Fuzzy Logic Applicated on Induction Motor for Electrical Vehicle. International Journal of Power Electronics and Drive Systems (IJPEDS), 8(2).

Sun, X., Sun, L., & Zhao, S. (2016). Harmonic Estimation Algorithm based on ESPRIT and Linear Neural Network in Power System. TELKOMNIKA (Telecommunication Computing Electronics and Control), 14(3A), 47-55.

Achmad, B., & Firdausy, K. (2012). Neural Network-based Face Pose Tracking for Interactive Face Recognition System. International Journal on Advanced Science, Engineering and Information Technology, 2(1), 105-108.

Dahiya, M., & Gill, S. (2017). Detection of Rogue Access Point in WLAN using Hopfield Neural Network. International Journal of Electrical and Computer Engineering (IJECE), 7(2), 1060-1070.

D. G. Rabus, Integrated Ring Resonators: The Compendium, ser. Springer Series in Optical Sciences. Berlin, Heidelberg: Springer, 2007.

J. G. Proakis and D. G. Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications, 3rd ed. Upper Saddle River, NJ, USA: Prentice-Hall, Inc., 1996.

T. van den Boom and D. Schutter, Optimization in Systems and Control: Lecture Notes for the Course SC4091. TU Delft, 2012. [Online]. Available: http://books.google.nl/books?id=8f_GnQEACAAJ




DOI: http://dx.doi.org/10.12928/telkomnika.v16i3.8176

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