Detection of Impaired OFDM Waveforms Using Deep Learning Receiver
Pihlajasalo, Jaakko; Korpi, Dani; Riihonen, Taneli; Talvitie, Jukka; Uusitalo, Mikko A.; Valkama, Mikko (2022)
Uusitalo, Mikko A.
2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication, SPAWC 2022
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Julkaisun pysyvä osoite on
With wireless networks evolving towards mmWave and sub-THz frequency bands, hardware impairments such as IQ imbalance, phase noise (PN) and power amplifier (PA) nonlinear distortion are increasingly critical implementation challenges. In this paper, we describe deep learning based physical-layer receiver solution, with neural network layers in both time- and frequency-domain, to efficiently demodulate OFDM signals under coexisting IQ, PN and PA impairments. 5G NR standard-compliant numerical results are provided at 28 GHz band to assess the receiver performance, demonstrating excellent robustness against varying impairment levels when properly trained.
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