Abstract
Currently, researchers are investigating methods of identifying user’s mobility characteristics within mmWave networks. Some examples of these characteristics include user’s speed and movement direction. Having knowledge of user’s mobility would aid in predicting future base stations that the user could handover to, therefore, enabling the network to prepare for incoming users. In this paper we propose a low-complexity speed estimation algorithm that utilizes the SINR reports sent by the user to the mmWave base station. We avoided using functions such as Global Positioning System (GPS) to avoid consuming the user’s finite power resources. Results show that our proposed algorithm is capable of estimating user’s speeds with an accuracy of 96%, 90%, 81%, and 53% for users moving at 27 m/s, 20 m/s, 13.5 m/s, and 7 m/s, respectively.
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Alattas, A., Rahulamathavan, Y., Kondoz, A. (2020). A Novel Speed Estimation Algorithm for Mobile UE’s in 5G mmWave Networks. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1228. Springer, Cham. https://doi.org/10.1007/978-3-030-52249-0_45
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DOI: https://doi.org/10.1007/978-3-030-52249-0_45
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