Spatial Signal Design for Positioning via End-to-End Learning
Saved in:
| Title: | Spatial Signal Design for Positioning via End-to-End Learning |
|---|---|
| Authors: | Rivetti, Steven, 1998, Mateos Ramos, José Miguel, 1998, Wu, Yibo, 1996, Song, Jinxiang, 1995, Keskin, Musa Furkan, 1988, Yajnanarayana, Vijaya, Häger, Christian, 1986, Wymeersch, Henk, 1976 |
| Source: | Fysikbaserad djupinlärning för optisk dataöverföring och distribuerad avkänning A flagship for B5G/6G vision and intelligent fabric of technology enablers connecting human, physical, and digital worlds (Hexa-X ) A New Waveform for Joint Radar and Communications Beyond 5G IEEE Wireless Communications Letters. 12(3):525-529 |
| Subject Terms: | end-to-end learning, mmWave positioning, precoder optimization |
| Description: | This letter considers the problem of end-to-end (E2E) learning for joint optimization of transmitter precoding and receiver processing for mmWave downlink positioning. Considering a multiple-input single-output (MISO) scenario, we propose a novel autoencoder (AE) architecture to estimate user equipment (UE) position with multiple base stations (BSs) and demonstrate that E2E learning can match model-based design, both for angle-of-departure (AoD) and position estimation, under ideal conditions without model deficits and outperform it in the presence of hardware impairments. |
| File Description: | electronic |
| Access URL: | https://research.chalmers.se/publication/535817 https://research.chalmers.se/publication/535817/file/535817_Fulltext.pdf |
| Database: | SwePub |
Full Text Finder 
Nájsť tento článok vo Web of Science | Abstract: | This letter considers the problem of end-to-end (E2E) learning for joint optimization of transmitter precoding and receiver processing for mmWave downlink positioning. Considering a multiple-input single-output (MISO) scenario, we propose a novel autoencoder (AE) architecture to estimate user equipment (UE) position with multiple base stations (BSs) and demonstrate that E2E learning can match model-based design, both for angle-of-departure (AoD) and position estimation, under ideal conditions without model deficits and outperform it in the presence of hardware impairments. |
|---|---|
| ISSN: | 21622345 21622337 |
| DOI: | 10.1109/LWC.2022.3233475 |