Abstract
This paper investigates uplink massive MIMO communication scenarios in dynamic Internet of things (IoT) networks. In this paper, dynamic IoT mainly consists of the Internet of vehicles (IoV) and the original IoT network. Because the speed of vehicle is very fast, the number of users is constantly changing in the IoT network, which leads the structure of the IoT network to change. We mainly consider how to obtain the channel state information (CSI) of active users. Due to active users and inactive users, the system model is considered a sparse structure. This structure inspired us to give an algorithm suitable for the sparse structure and obtain more accurate channel state information of dynamic IoT networks, though these numerical results, under the premise of guaranteeing performance, can greatly reduce the complexity of the algorithm.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Boccardi, F., Heath, R.W., Lozano, A., et al.: Five disruptive technology directions for 5G. IEEE Commun. Mag. 52(2), 74–80 (2014)
Wang, P., Li, Y., Song, L., et al.: Multi-gigabit millimeter wave wireless communications for 5G: from fixed access to cellular networks. IEEE Commun. Mag. 53(1), 168–178 (2015)
Niu, Y., Li, Y., Jin, D., et al.: A survey of millimeter wave communications (mmWave) for 5G: opportunities and challenges. Wireless Netw. 21(8), 2657–2676 (2015)
Rusek, F., Hu, S.: Sequential channel estimation in the presence of random phase noise in NB-IoT systems. arXiv:1706.04350 (2017)
Hu, S., Berg, A., Li, X., et al.: Improving the performance of OTDOA based positioning in NB-IoT system. arXiv:1704.05350 (2017)
Zhang, Z., Wang, X., Zhang, Y., et al.: Grant-free rateless multiple access: a novel massive access scheme for internet of things. IEEE Commun. Lett. 20(10), 2019–2022 (2016)
Alkhateeb, A., El Ayach, O., Leus, G., et al.: Channel estimation and hybrid precoding for millimeter wave cellular systems. IEEE J. Sel. Top. Signal Process. 8(5), 831–846 (2014)
Liu, C., Li, M., Collings, I.B., et al.: Design and analysis of transmit beamforming for millimeter wave base station discovery. IEEE Trans. Wireless Commun. 16(2), 797–811 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Xiu, Y., Wang, W., Shen, Y., Zhang, Z. (2020). Based on Deep Learning CSI Recovery for Uplink Massive Device Dynamic Internet of Thing. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-13-6508-9_1
Download citation
DOI: https://doi.org/10.1007/978-981-13-6508-9_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6507-2
Online ISBN: 978-981-13-6508-9
eBook Packages: EngineeringEngineering (R0)