Pourkabirian, Azadeh and Anisi, Mohammad Hossein (2022) Robust Channel Estimation in Multiuser Downlink 5G Systems Under Channel Uncertainties. IEEE Transactions on Mobile Computing, 21 (12). pp. 4569-4582. DOI https://doi.org/10.1109/tmc.2021.3084398
Pourkabirian, Azadeh and Anisi, Mohammad Hossein (2022) Robust Channel Estimation in Multiuser Downlink 5G Systems Under Channel Uncertainties. IEEE Transactions on Mobile Computing, 21 (12). pp. 4569-4582. DOI https://doi.org/10.1109/tmc.2021.3084398
Pourkabirian, Azadeh and Anisi, Mohammad Hossein (2022) Robust Channel Estimation in Multiuser Downlink 5G Systems Under Channel Uncertainties. IEEE Transactions on Mobile Computing, 21 (12). pp. 4569-4582. DOI https://doi.org/10.1109/tmc.2021.3084398
Abstract
In wireless communication, the performance of the network highly relies on the accuracy of channel state information (CSI). On the other hand, the channel statistics are usually unknown, and the measurement information is lost due to the fading phenomenon. Therefore, we propose a channel estimation approach for downlink communication under channel uncertainty. We apply the Tobit Kalman filter (TKF) method to estimate the hidden state vectors of wireless channels. To minimize the maximum estimation error, a robust minimax minimum estimation error (MSE) estimation approach is developed while the QoS requirements of wireless users is taken into account. We then formulate the minimax problem as a non-cooperative game to find an optimal filter and adjust the best behavior for the worst-case channel uncertainty. We also investigate a scenario in which the actual operating point is not exactly known under model uncertainty. Finally, we investigate the existence and characterization of a saddle point as the solution of the game. Theoretical analysis verifies that our work is robust against the uncertainty of the channel statistics and able to track the true values of the channel states. Additionally, simulation results demonstrate the superiority of the model in terms of MSE value over related techniques.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | 5G networks; Channel estimation; game theory; minimax optimization; Quality of Service guarantees |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 01 Jul 2021 12:06 |
Last Modified: | 30 Oct 2024 20:52 |
URI: | http://repository.essex.ac.uk/id/eprint/30523 |
Available files
Filename: TMC-Manuscript.pdf