Maximum likelihood-based adaptive iteration algorithm design for joint CFO and channel estimation in MIMO-OFDM systems
| Autor: | Kai Chieh Huang, Yung-Fang Chen, Shu-Ming Tseng, Nan Hung Cheng |
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| Rok vydání: | 2021 |
| Předmět: |
Mean squared error
Iterative method Computer science lcsh:Electronics 05 social sciences Orthogonal frequency-division multiplexing (OFDM) lcsh:TK7800-8360 Estimator 050801 communication & media studies 020206 networking & telecommunications 02 engineering and technology MIMO-OFDM Multiple input multiple output (MIMO) lcsh:Telecommunication 0508 media and communications Carrier frequency offset (CFO) lcsh:TK5101-6720 Carrier frequency offset 0202 electrical engineering electronic engineering information engineering Bit error rate Joint maximum likelihood estimation Algorithm design Algorithm Computer Science::Information Theory Communication channel |
| Zdroj: | EURASIP Journal on Advances in Signal Processing, Vol 2021, Iss 1, Pp 1-21 (2021) |
| ISSN: | 1687-6180 |
| DOI: | 10.1186/s13634-020-00711-5 |
| Popis: | In this paper, we present a joint time-variant carrier frequency offset (CFO) and frequency-selective channel response estimation scheme for multiple input-multiple output-orthogonal frequency-division multiplexing (MIMO-OFDM) systems for mobile users. The signal model of the MIMO-OFDM system is introduced, and the joint estimator is derived according to the maximum likelihood criterion. The proposed algorithm can be separated into three major parts. In the first part of the proposed algorithm, an initial CFO is estimated using derotation, and the result is used to apply a frequency-domain equalizer. In the second part, an iterative method is employed to locate the fine frequency peak for better CFO estimation. An adaptive process is used in the third part of the proposed algorithm to obtain the updated CFO estimation and track parameter time variations, including the time-varying CFOs and time-varying channels. The computational complexity of the proposed algorithm is considerably lower than that of the maximum likelihood-based grid search method. In a simulation, the mean squared error performance of the proposed algorithm was close to the Cramer-Rao lower bound. The simulation results indicate that the proposed novel joint estimation algorithm provides a bit error rate performance close to that in the perfect channel estimation condition. The results also suggest that the proposed method has reliable tracking performance in Jakes’ channel models. |
| Databáze: | OpenAIRE |
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