Ambient backscatters-friendly 5G networks: creating hot spots for tags and good spots for readers

• Main Authors: Fara, Romain, Phan-Huy, Dinh-Thuy, Renzo, Marco Di
• Format: Conference Proceeding
• Language: English
• Subjects: 5G mobile communication; Ambient backscatter; Array signal processing; beamforming; energy detector; internet of things; Precoding; Quality of service; Radio frequency; Simulation; Training; zero forcing
• ISSN: 1558-2612
• DOI: 10.1109/WCNC45663.2020.9120781

In this paper, we present an ambient backscatters-friendly 5G network that creates locations with large power (hot spots) for tags and good reception locations (quiet spots or coherent spots) for readers. Tags are devices that communicate information to readers by backscattering ambient radiofrequency signals. The massive multiple input multiple output (M-MIMO) antenna and beamforming capability of the 5G network is used as follows. In a first step, a training device (separate from tags and readers) is used to send pilots and train the 5G network to perform focusing and/or nulling onto marked locations. In a second step, tags and readers are positioned onto the marked locations. The robustness of M-MIMO beamforming to slight changes in the environment is exploited. Our initial simulation results, in a multipath propagation channel environment, show that creating a hot spot on a tag improves the tag-reader range however with a low probability of detection. Creating a hot spot on a tag and a good reception spot on a reader at the same time, improves the tag-reader range with 99% probability of detection. The study also shows that beamforming does not degrade the performance of a legacy 5G communication.