Webis ineffective when paired with a one-bit ADC. Lastly, [18] demonstrated that one-bit ADCs in linear OFDM receivers for massive MIMO can give the same performance as one-bit ADCs for single-carrier waveforms, provided there is an infinite number of channel taps. There has been a growing interest in harnessing the power of deep learning for ...
One-Bit OFDM Receivers via Deep Learning - Semantic Scholar
WebThis paper develops novel deep learning-based architectures and design methodologies for an orthogonal frequency division multiplexing (OFDM) receiver under the constraint of one-bit complex quantization. Single bit quantization greatly reduces complexity and power consumption, but makes accurate channel estimation and data detection difficult. This is … Web12. maj 2024. · Here, ML blocks replace the individual processing blocks of an OFDM receiver, and we specifically describe this swapping for the legacy channel estimation, symbol demapping, and decoding blocks with Neural Networks (NNs). A unique aspect of this modular design is providing flexible allocation of processing functions to the legacy … prp fencing
Improved Deep Learning in OFDM Systems With Imperfect …
Web20. apr 2024. · Abstract. Deep learning (DL) based autoencoder (AE) has been proposed recently as a promising, and potentially disruptive Physical Layer (PHY) design for beyond-5G communication systems. Compared to a traditional communication system with a multiple-block structure, the DL based AE provides a new PHY paradigm with a pure … WebFig. 3. Constellation diagram of the QPSK modulated OFDM symbols received at 20 dB SNR for the (a) ideal unquantized case (b) one-bit quantization applied separately for … Web01. maj 2024. · This paper develops novel deep learning-based architectures and design methodologies for an orthogonal frequency division multiplexing (OFDM) receiver under the constraint of one-bit complex ... prp finishing inc