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Instantaneous Interference Evaluation Model for Smart Antennas in 5G Ultra-Dense Networks

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Internet of Things, Smart Spaces, and Next Generation Networks and Systems (NEW2AN 2021, ruSMART 2021)

Abstract

The rapidly increasing number of simultaneously transmitting devices in the upcoming 5G Ultra-Dense Networks (UDN) leads to the relevant problem of unacceptable interference level in densified multi-user radio access network. Transition to millimeter-wave frequencies and evolving massive MIMO systems on the physical layer is essential for minimizing the interference level of devices, using the same frequency resource, by means of angular and spatial multi-user separation with smart antennas. Its adaptive 3D-beamforming capability is expected to alleviate the 5G UDN interference problem by means of steering the transmitted signal of interest (SOI) toward the desired direction and simultaneously, avoiding signal of no interest (SNOI) transmission or reception from the unwanted direction. This well-known problem was already well treated in the past decade for stationary devices. However, the case of user mobility had not yet been thoroughly investigated. The challenge here consists in the instantaneous dependency of signal to interference ratio (SIR) on devices angular and spatial separation, which changes during their motion. Current work presents an instantaneous SIR evaluation model for the special case of two mobile devices and two stationary base stations, equipped with smart antennas, which perform location-aware beamforming (LAB) during mobile devices motion, accounting for their SOI and SNOI roles. Simulation results demonstrate considerable SIR fluctuation that needs to be accounted for when assessing device angular and spatial separation.

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Correspondence to Grigoriy Fokin .

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Davydov, V., Fokin, G., Moroz, A., Lazarev, V. (2022). Instantaneous Interference Evaluation Model for Smart Antennas in 5G Ultra-Dense Networks. In: Koucheryavy, Y., Balandin, S., Andreev, S. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2021 2021. Lecture Notes in Computer Science(), vol 13158. Springer, Cham. https://doi.org/10.1007/978-3-030-97777-1_31

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  • DOI: https://doi.org/10.1007/978-3-030-97777-1_31

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