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A discrete‐components millimeter‐wave satellite beacon receiver for Q‐band propagation experiment
Author(s) -
Mrak Sebastijan,
Hrovat Andrej,
Vidmar Matjaz,
Vilhar Andrej
Publication year - 2018
Publication title -
international journal of satellite communications and networking
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.388
H-Index - 39
eISSN - 1542-0981
pISSN - 1542-0973
DOI - 10.1002/sat.1240
Subject(s) - computer science , radio receiver design , software defined radio , radio propagation , radio spectrum , bandwidth (computing) , extremely high frequency , frequency band , leverage (statistics) , radio frequency , telecommunications , electronic engineering , transmitter , channel (broadcasting) , machine learning , engineering
Summary Ever increasing bandwidth requirements in satellite communications continuously push the frequency limits. Q‐ band (33 – 50 GHz) is the next frequency band to be populated; however, at these frequencies, the Earth's troposphere (weather) profoundly alters the radio propagation conditions. Therefore, in order to properly plan radio links, accurate statistical models of radio channels are necessary. These statistical models are built upon empirical data, ie, measurements, which are furthermore used to design appropriate Propagation Impairment Mitigation Techniques. The Q‐ band lacks such data, hence the statistical models are inadequate. To address this problem, we propose a cost‐effective, easy to replicate Q‐ band beacon receiver to leverage the Alphasat propagation campaign. We present a step‐by‐step implementation process of the receiver's fundamental part, a Low‐Noise Block, which translates input 39.402 GHz signal into 162 MHz output signal with a conversion gain of 52 dB. The receiver furthermore utilizes software define radio for signal processing and other data manipulation. Here, we describe the receiver implementations in great details, supplementing the crucial parts with laboratory validation results. Finally, we show 2 example datasets, showing usual data obtained during heavy showers and on a quiet day, respectively.