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This project is an investigation into mmWave propagation characteristics, channel modeling, link budgeting and power distribution among multiple hops between Transmitting and Receiving antennas. NYUSIM channel estimator has been used for channel estimation and its base script is modified in MATLAB that helps in generating channel matrix dataset.

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anjleenatufail/Link-Budgeting-and-Channel-Characterization-at-mmWave-frequencies

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Link-Budgeting-and-Channel-Characterization-at-mmWave-frequencies

This project is an investigation into mmWave propagation characteristics, channel modeling, link budgeting and power distribution among multiple hops between Transmitting and Receiving antennas. NYUSIM channel estimator has been used for channel estimation and its base script is modified in MATLAB that helps in generating channel matrix dataset.

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The aim is to observe channel model with Power delay profiles (PDP) for both directional and omnidirectional Antenna configuration, Path loss Exponent (PLE), power spectrum, path loss plots, Outdoor to Indoor (O2I) Penetration Loss etc. at millimeters Wavelength band for both LOS and NLOS environments using a open source novel, measurement based channel simulator NYUSIM. Obtaining this information is vital for the design and operation of future work systems for mm-wave spectrum. The project is mostly revolving around measuring the channel characterization parameters for mmWave frequencies and the path loss model in free space and other scenarios. The effect of foliage loss, the rainfall loss, building penetration loss and the effect of change in antenna polarization settings are also investigated. Taking the advancement of Machine Learning in recent years into account, this project also studies dataset generation for a channel whose Channel Impulse Response is time varying. As measurement of transmitter power and received power using mmWaves can’t be done because of unavailability of certain equipment. We have used NYUSIM for channel estimation at mmWave frequency range. Matlab script that helps in generation of this channel matrix dataset are thoroughly studied in this project. This channel matrix dataset can be further used by applying different machine learning predictive algorithms to predict future variations in the channel.

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This project is an investigation into mmWave propagation characteristics, channel modeling, link budgeting and power distribution among multiple hops between Transmitting and Receiving antennas. NYUSIM channel estimator has been used for channel estimation and its base script is modified in MATLAB that helps in generating channel matrix dataset.

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