TY - JOUR
T1 - Estimating and Tracking Wireless Channels Under Carrier and Sampling Frequency Offsets
AU - Parlin, Karel
AU - Riihonen, Taneli
AU - Nir, Vincent Le
AU - Adrat, Marc
N1 - Publisher Copyright:
© 1991-2012 IEEE.
PY - 2023
Y1 - 2023
N2 - This article addresses the challenge of estimating and tracking wireless channels under carrier and sampling frequency offsets, which also incorporate phase noise and sampling time jitter. We propose a novel adaptive filter that explicitly estimates the channel impulse response, carrier frequency offset, and sampling frequency offset by minimizing the mean-square error (MSE) and, when the estimated parameters are time-varying, inherently performs tracking. The proposed filter does not have any requirements for the structure of the waveform, but the digital transmitted waveform must be known to the receiver in advance. To aid practical implementation, we derive upper bounds for the filter's step sizes. We also derive expressions for the filter's steady-state MSE performance, by extending the well-known energy conservation relation method to account for the self-induced nonstationarity and coupling of update equations that are inherent in the proposed filter. Theoretical findings are verified by comparison to simulated results. Proof-of-concept measurement results are also provided, which demonstrate that the proposed filter is able to estimate and track a practical wireless channel under carrier and sampling frequency offsets.
AB - This article addresses the challenge of estimating and tracking wireless channels under carrier and sampling frequency offsets, which also incorporate phase noise and sampling time jitter. We propose a novel adaptive filter that explicitly estimates the channel impulse response, carrier frequency offset, and sampling frequency offset by minimizing the mean-square error (MSE) and, when the estimated parameters are time-varying, inherently performs tracking. The proposed filter does not have any requirements for the structure of the waveform, but the digital transmitted waveform must be known to the receiver in advance. To aid practical implementation, we derive upper bounds for the filter's step sizes. We also derive expressions for the filter's steady-state MSE performance, by extending the well-known energy conservation relation method to account for the self-induced nonstationarity and coupling of update equations that are inherent in the proposed filter. Theoretical findings are verified by comparison to simulated results. Proof-of-concept measurement results are also provided, which demonstrate that the proposed filter is able to estimate and track a practical wireless channel under carrier and sampling frequency offsets.
KW - Adaptive filtering
KW - frequency offset
KW - mean-square error
KW - steady-state analysis
UR - http://www.scopus.com/inward/record.url?scp=85151506427&partnerID=8YFLogxK
U2 - 10.1109/TSP.2023.3259140
DO - 10.1109/TSP.2023.3259140
M3 - Article
AN - SCOPUS:85151506427
SN - 1053-587X
VL - 71
SP - 1053
EP - 1066
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
ER -