University of Oulu

I. Ismath, K. B. Shashika Manosha, S. Ali, N. Rajatheva and M. Latva-aho, "Deep Contextual Bandits for Fast Initial Access in mmWave Based User-Centric Ultra-Dense Networks," 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), 2021, pp. 1-7, doi: 10.1109/VTC2021-Spring51267.2021.9448999

Deep contextual bandits for fast initial access in mmWave based user-centric ultra-dense networks

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Author: Ismath, Insaf1; Shashika Manosha, K.B1; Ali, Samad1;
Organizations: 1Center for Wireless Communication, University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.2 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2021-10-21


Millimeter wave (mmWave) based multiple-input multiple-output (MIMO) capable user-centric (UC) ultra-dense (UD) networks are suggested to facilitate high throughput requirements of future networks. Due to the high blockage susceptibility of mmWave, the connections may drop frequently. Hence efficient and fast beam management in initial access (IA) is essential. Current cellular systems use beam sweeping based IA mechanisms. UC UD concept requires all of its access points (APs) to perform IA. This leads to a shortage of orthogonal radio resources. Nonorthogonal resource allocation causes interference which leads to a higher misdetection probability. In this paper, we propose a novel deep contextual bandit (DCB) based approach to perform fast and efficient IA in mmWave based UC UD networks. The DCB model uses one reference signal from the user to predict the IA beam. The reduced use of reference signals improves beam discovery delay and relaxes the requirement for radio resources. Ray-tracing and stochastic channel model-based simulations show that the suggested system outperforms its beam sweeping counterpart in terms of probability of beam misdetection and beam discovery delay in mmWave based UC UD networks.

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Series: IEEE Vehicular Technology Conference
ISSN: 1090-3038
ISSN-L: 1090-3038
ISBN: 978-1-7281-8964-2
ISBN Print: 978-1-7281-8965-9
Article number: 9448999
DOI: 10.1109/VTC2021-Spring51267.2021.9448999
Host publication: 93rd IEEE Vehicular Technology Conference, VTC 2021-Spring
Conference: IEEE Vehicular Technology Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work is supported in part by the Academy of Finland 6Genesis Flagship (grant 318927)
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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