In this work, we consider a radar-enabled ambient backscatter communication, where the reverberation generated by a radar system is used as an ambient carrier to deliver information to a destination. Different from a previous study, that focuses on noncoherent encoding/decoding strategies, which require an exhaustive search on a set whose cardinality scales exponentially with the data size, we consider here a pilot-based solution and propose a simplified decoding scheme relying on constrained regularized least squares and search relaxation, whose complexity per iteration scales only linearly with the data size. A numerical example is provided to show merits and drawbacks of the proposed scheme with respect to different benchmarks.

Joint Data and Channel Estimation in Radar-enabled Backscatter Communications / Venturino, L.; Grossi, E.; Johnston, J.; Lops, M.; Wang, X.. - (2023), pp. 368-372. (Intervento presentato al convegno 2023 IEEE International Workshop on Technologies for Defense and Security, TechDefense 2023 tenutosi a Roma nel 20-22 Novembre 2023) [10.1109/TechDefense59795.2023.10380821].

Joint Data and Channel Estimation in Radar-enabled Backscatter Communications

Venturino L.;Lops M.;
2023

Abstract

In this work, we consider a radar-enabled ambient backscatter communication, where the reverberation generated by a radar system is used as an ambient carrier to deliver information to a destination. Different from a previous study, that focuses on noncoherent encoding/decoding strategies, which require an exhaustive search on a set whose cardinality scales exponentially with the data size, we consider here a pilot-based solution and propose a simplified decoding scheme relying on constrained regularized least squares and search relaxation, whose complexity per iteration scales only linearly with the data size. A numerical example is provided to show merits and drawbacks of the proposed scheme with respect to different benchmarks.
2023
Joint Data and Channel Estimation in Radar-enabled Backscatter Communications / Venturino, L.; Grossi, E.; Johnston, J.; Lops, M.; Wang, X.. - (2023), pp. 368-372. (Intervento presentato al convegno 2023 IEEE International Workshop on Technologies for Defense and Security, TechDefense 2023 tenutosi a Roma nel 20-22 Novembre 2023) [10.1109/TechDefense59795.2023.10380821].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/953544
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