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Updated: Jan 9, 2026

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
09:36

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements

Published on: June 25, 2021

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一个稀疏波长意识的学习框架,用于强大的FSO通道估计

S Senthilkumar1, R Balakrishnan2, M Irshad Ahamed3

  • 1Department of Electronics and Communication Engineering, E.G.S. Pillay Engineering College, Nagapattinam, Tamil Nadu, 611002, India. senthilkumar.s@egspec.org.

Scientific reports
|December 10, 2025
PubMed
概括

一个新的稀疏波长感知学习网络 (SWALNet) 通过准确估计通道条件来改善自由空间光学 (FSO) 通信. 这种深度学习方法在具有挑战性的大气环境中提高了信号质量和光谱效率.

关键词:
大气流是大气中的流.频道预测 频道预测FSO估计的时间.在OFDM模块化方面,OFDM模块化光学信号的色正在消失.稀少的学习学习.波长的多样性波长的多样性.

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Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
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Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
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