| Paper ID | SAM-4.6 |
| Paper Title |
JOINT CHANNEL, DATA, AND PHASE-NOISE ESTIMATION IN MIMO-OFDM SYSTEMS USING A TENSOR MODELING APPROACH |
| Authors |
Bruno Sokal, Federal University of Ceará, Brazil; Paulo Gomes, Federal Institute of Education, Science and Technology of Ceara, Brazil; André de Almeida, Federal University of Ceará, Brazil; Martin Haardt, Ilmenau University of Technology, Germany |
| Session | SAM-4: MIMO and Massive MIMO Array Processing |
| Location | Gather.Town |
| Session Time: | Wednesday, 09 June, 16:30 - 17:15 |
| Presentation Time: | Wednesday, 09 June, 16:30 - 17:15 |
| Presentation |
Poster
|
| Topic |
Sensor Array and Multichannel Signal Processing: [SAM-TNSR] Tensor-based signal processing for multi-sensor systems |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
In this work, we propose a two-stage tensor-based receiver for joint channel, phase-noise (PN), and data estimation in MIMO-OFDM systems. First, we cast the received signal at the pilot subcarriers as a third-order PARAFAC model. Based on this model, we propose a closed-form algorithm based on the LS-KRF (Least Squares - Khatri-Rao Factorization) that estimates the channel gains and the phase-noise terms through multiple rank-one factorizations. From the estimated channel, the second stage of the receiver consists of data estimation based on a ZF (Zero-Forcing) receiver that capitalizes on the tensor structure of the received signal at the data subcarriers via a Selective Kronecker Product (SKP) approach. Our numerical simulations show that the proposed receiver achieves an improved performance compared to the state-of-art receivers. |
