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Titel:

Learning the Channel State Information Across the Frequency Division Gap in Wireless Communications

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Rizzello, V.; Brayek, I.; Joham, M.; Utschick, W.
Abstract:
Massive multiple-input multiple-output (MIMO) is a key technology for the fifth-generation (5G) and beyond to enable high-rate and low latency communications. However, due to the large pilot sequences required for the downlink (DL) channel estimation, this solution turns out to be potentially intractable for frequency division duplex (FDD) systems. In this paper, we propose a machine learning-based approach in order to predict the DL channel-state-information (CSI) from the uplink CSI. The novel...     »
Kongress- / Buchtitel:
WSA 2020; 24th International ITG Workshop on Smart Antennas
Jahr:
2020
Monat:
Feb
Seiten:
1-6
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