Microwave LNA Design Based On Adaptive Network Fuzzy Inference and Evolutionary Optimization
This paper presents a novel approach for the design of
microwave circuits using Adaptive Network Fuzzy Inference
Optimizer (ANFIO). The method takes advantage of direct synthesis
of subsections of the amplifier using very fast and accurate ANFIO
models based on exact simulations using ADS. A mapping from
course space to fine space known as space mapping is also used. The
proposed synthesis approach takes into account the noise and
scattering parameters due to parasitic elements to achieve optimal
results. The overall ANFIO system is capable of designing different
LNAs at different noise and scattering criteria. This approach offers
significantly reduced time in the design of microwave amplifiers
within the validity range of the ANFIO system. The method has been
proven to work efficiently for a 2.4GHz LNA example. The S21 of
10.1 dB and noise figure (NF) of 2.7 dB achieved for ANFIO while
S21 of 9.05 dB and NF of 2.6 dB achieved for ANN.
[1] J.W. Bandler, Q.S. Cheng, N.K. Nikolova, and M.A. Ismail, "Implicit
space mapping optimization exploiting preassigned parameters," IEEE
Trans. Microwave Theory Tech., vol. 52, no. 1, pp. 378-385, Jan. 2004.
[2] S. Koziel, J.W. Bandler, and K. Madsen, "A space mapping framework
For engineering optimization: theory and implementation," IEEE Trans.
Microwave Theory Tech., vol. 54, no. 10, pp. 3721-3730, Oct. 2006.
[3] A. Hennings, E. Semouchkina, A. Baker, and G. Semouchkin, "Design
optimization and implementation of bandpass filters with normally fed
Microstrip resonators loaded by high-permittivity dielectric," IEEE
Trans.
Microwave Theory Tech., vol. 54, no. 3, pp. 1253-1261, March 2006.
[4] J. W. Bandler, Q. S. Cheng, S. A. Dakroury, A. S. Mohamed, M. H.
Bakr, K. Madsen, J. Sondergaard , "Space Mapping: The State of the
Art," IEEE Trans. On Microwave Theory Tech., vol. 52, pp. 337-361,
2004.
[5] J.W. Bandler, Q.S. Cheng and S. Koziel, "Simplified space mapping
approach to enhancement of microwave device models," Int. J. RF and
Microwave Computer-Aided Eng., vol. 16, no. 5, pp. 518-535, 2006.
[6] J. Zhu, J. W. Bandler, N. K. Nikolova and Koziel , "Antenna
Optimization Through Space Mapping," IEEE Trans. on Antennas and
Propagation, vol. 55, pp. 651 - 658, 2007.
[7] S. Koziel, J. W. Bandler, "A Space-Mapping Approach to Microwave
Device Modeling Exploiting Fuzzy Systems," IEEE Trans. on
Microwave
Theory and Tech.,vol. 55, pp. 2539 - 2547, 2007.
[8] B. Karlik, H. Torpi, M. Alci, "A fuzzy-neural approach for the
characterization of the active microwave devices," 12th International
Conference on Microwave and Telecomm. Tech., pp. 114 - 117, 2002.
[1] J.W. Bandler, Q.S. Cheng, N.K. Nikolova, and M.A. Ismail, "Implicit
space mapping optimization exploiting preassigned parameters," IEEE
Trans. Microwave Theory Tech., vol. 52, no. 1, pp. 378-385, Jan. 2004.
[2] S. Koziel, J.W. Bandler, and K. Madsen, "A space mapping framework
For engineering optimization: theory and implementation," IEEE Trans.
Microwave Theory Tech., vol. 54, no. 10, pp. 3721-3730, Oct. 2006.
[3] A. Hennings, E. Semouchkina, A. Baker, and G. Semouchkin, "Design
optimization and implementation of bandpass filters with normally fed
Microstrip resonators loaded by high-permittivity dielectric," IEEE
Trans.
Microwave Theory Tech., vol. 54, no. 3, pp. 1253-1261, March 2006.
[4] J. W. Bandler, Q. S. Cheng, S. A. Dakroury, A. S. Mohamed, M. H.
Bakr, K. Madsen, J. Sondergaard , "Space Mapping: The State of the
Art," IEEE Trans. On Microwave Theory Tech., vol. 52, pp. 337-361,
2004.
[5] J.W. Bandler, Q.S. Cheng and S. Koziel, "Simplified space mapping
approach to enhancement of microwave device models," Int. J. RF and
Microwave Computer-Aided Eng., vol. 16, no. 5, pp. 518-535, 2006.
[6] J. Zhu, J. W. Bandler, N. K. Nikolova and Koziel , "Antenna
Optimization Through Space Mapping," IEEE Trans. on Antennas and
Propagation, vol. 55, pp. 651 - 658, 2007.
[7] S. Koziel, J. W. Bandler, "A Space-Mapping Approach to Microwave
Device Modeling Exploiting Fuzzy Systems," IEEE Trans. on
Microwave
Theory and Tech.,vol. 55, pp. 2539 - 2547, 2007.
[8] B. Karlik, H. Torpi, M. Alci, "A fuzzy-neural approach for the
characterization of the active microwave devices," 12th International
Conference on Microwave and Telecomm. Tech., pp. 114 - 117, 2002.
@article{"International Journal of Electrical, Electronic and Communication Sciences:63631", author = "Samad Nejatian and Vahideh Rezaie and Vahid Asadpour", title = "Microwave LNA Design Based On Adaptive Network Fuzzy Inference and Evolutionary Optimization", abstract = "This paper presents a novel approach for the design of
microwave circuits using Adaptive Network Fuzzy Inference
Optimizer (ANFIO). The method takes advantage of direct synthesis
of subsections of the amplifier using very fast and accurate ANFIO
models based on exact simulations using ADS. A mapping from
course space to fine space known as space mapping is also used. The
proposed synthesis approach takes into account the noise and
scattering parameters due to parasitic elements to achieve optimal
results. The overall ANFIO system is capable of designing different
LNAs at different noise and scattering criteria. This approach offers
significantly reduced time in the design of microwave amplifiers
within the validity range of the ANFIO system. The method has been
proven to work efficiently for a 2.4GHz LNA example. The S21 of
10.1 dB and noise figure (NF) of 2.7 dB achieved for ANFIO while
S21 of 9.05 dB and NF of 2.6 dB achieved for ANN.", keywords = "fuzzy system, low noise amplifier, microwaveamplifier, space mapping", volume = "4", number = "7", pages = "1085-4", }