2022 IEEE 41st International Conference on Electronics and Nanotechnology (ELNANO) 2022
DOI: 10.1109/elnano54667.2022.9927081
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Highly Sensitive Broadband SiGe HBT LNA: Genetic Algorithm based Optimization and Design Methodology

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Cited by 3 publications
(7 citation statements)
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“…Reconfigurability of a transceiver can be achieved by adjusting the VCO control voltage to change the frequency band, or channel, of the transceiver. If the signal quality is poor, the VCO can adjust the carrier frequency to avoid interference and improve the SNR [15]. The VCO can also switch between modulation schemes to adapt to varying channel conditions or to increase transmission rates.…”
Section: B Traditional Methods Of Reconfigurabilitymentioning
confidence: 99%
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“…Reconfigurability of a transceiver can be achieved by adjusting the VCO control voltage to change the frequency band, or channel, of the transceiver. If the signal quality is poor, the VCO can adjust the carrier frequency to avoid interference and improve the SNR [15]. The VCO can also switch between modulation schemes to adapt to varying channel conditions or to increase transmission rates.…”
Section: B Traditional Methods Of Reconfigurabilitymentioning
confidence: 99%
“…It is envisaged that the trajectory towards 6G will need to be more inclusive than before [14]. This implies that there may be augmentation between frequency solutions (anticipated: higher frequency as well as satellite or other non-terrestrial solutions) [15]. Through inclusivity and the abovementioned applications, several applicable learning techniques can be identified, presented in the following paragraph.…”
Section: Table 1 Machine Learning Techniques That Can Be Applied To A...mentioning
confidence: 99%
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“…From Table 1, it appears that genetic algorithms (GAs), based on adaptive heuristic or search engine algorithms, can be implemented in antenna array and RF front-end subsystem (mixers, filters, and amplifiers) algorithm development [16]. A GA typically performs better than random search algorithms since it uses historical data to lead the search toward the highest-performing region within the solution space.…”
Section: B High-frequency Learning Techniquesmentioning
confidence: 99%
“…A GA typically performs better than random search algorithms since it uses historical data to lead the search toward the highest-performing region within the solution space. In [16], a GA is implemented to optimize the highly sensitive broadband silicon germanium (SiGe) heterojunction bipolar transistor (HBT) low noise amplifier (LNA) design methodology for radio astronomy. To perform adaptive equalization in analog RF front ends, neural networks are recommended since these tasks are typically applied to large datasets.…”
Section: B High-frequency Learning Techniquesmentioning
confidence: 99%