Deep Learning Based CS Channel Estimation in MIMO System

Ye, Linxia; Hou, Xiaoyun; Wang, Qingyao

doi:10.1109/iccc56324.2022.10065944

Cited by 1 publication

(2 citation statements)

References 18 publications

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“…To this end, we have investigated much of the literature since 2017. [39] -Increasing energy efficiency [40] -Effective electricity supply and management [41] -Weather prediction from historical data [41] Advanced mobile edge computing -Achieving low latency via decentralized structure [42] -High QoS achievement [43] -Overload mitigation [43] -Real-time immersive service [42] -Enhanced privacy security [44] Non-terrestrial networks -Reducing coverage holes [45] -Frequency co-existence [46] -RIS-aided zero-coverage hole networks [47] -UAM transportation service [46] Vision-aided wireless communication -Environmental awareness [48] -Energy conservation [49] -UAV communication systems [50] -Traffic congestion mitigation [51] Integrated sensing and communication -High-resolution sensing [52] -Simultaneous imaging and localization [53] -Enabling autonomous vehicles [53] -Traffic accident detection [54]…”

Section: Prime Technologies For Sscmentioning

confidence: 99%

“…A possible solution to predict CSI from channel estimates is to exploit the DL-based time series prediction model [69]. Furthermore, a DL-based CS algorithm for sparsity detection in the Doppler region was introduced to improve the channel estimation efficiency in high-speed mobile communication scenarios [39]. AI-based channel estimation and prediction algorithms can contribute to future-proofing transportation in SSC by tackling outdated CSIs and optimizing pilot use in high-speed communication scenarios.…”

mentioning

confidence: 99%

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Key Technologies for 6G-Enabled Smart Sustainable City

Kim,

Shim

et al. 2024

Electronics

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With the advancement of information and communication technologies (ICTs), the way we live and communicate with each other is changing rapidly. As urban environments continue to evolve, the smart sustainable city (SSC) has sparked considerable attention. We are hoping for a new era in which numerous devices and machines including vehicles, sensors, and robots are all connected to communicate, respond, and operate in real time. The next-generation communication system, the sixth generation (6G), is expected to play a crucial role in improving the efficiency of urban operations and services. In this paper, we first provide the recent trends and key features of standardization in the SSC. To make the future SSC, we highlight key candidate technologies of 6G such as non-terrestrial networks, advanced mobile edge computing, vision-aided wireless communication, artificial intelligence (AI)-based wireless communication, and integrated sensing and communication. We put forth the main technical challenges given to each prime technology along with the potential benefits to pave the way for 6G-enabled SSC. We further address how the potential benefits of prime technologies enable various urban practice cases for 6G-enabled SSC.

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