Xu, B;
Chen, Y;
Cui, Q;
Tao, X;
Wong, KK;
(2024)
Sparse Bayesian Learning-Based Channel Estimation for Fluid Antenna Systems.
IEEE Wireless Communications Letters
10.1109/LWC.2024.3500218.
(In press).
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Abstract
Fluid antenna system (FAS) has emerged to give comparable performance to conventional multiple-input multiple-output (MIMO) systems with fewer radio-frequency (RF) chains. The performance of FAS depends on the accuracy of the channel state information (CSI) estimation. In this letter, we develop a sparse Bayesian learning (SBL) algorithm and an improved SBL algorithm to estimate FAS's CSI. Simulation results demonstrate that both our proposed algorithms achieve higher accuracy in channel estimation compared to existing algorithms.
| Type: | Article |
|---|---|
| Title: | Sparse Bayesian Learning-Based Channel Estimation for Fluid Antenna Systems |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/LWC.2024.3500218 |
| Publisher version: | http://dx.doi.org/10.1109/lwc.2024.3500218 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Channel estimation , Vectors , Radio frequency , Bayes methods , Switches , Estimation , Transmitting antennas , Accuracy , Switching circuits , Receiving antennas |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10201057 |
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