Joint Estimation of Symbol Timing and Sampling Frequency Offset for CDD-OFDM-Based DRM Systems

You, Young-Hwan; Jung, Yongju; Paik, Jong-Ho

doi:10.1109/tbc.2018.2881362

Cited by 7 publications

(7 citation statements)

References 21 publications

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“…Subsequently, a grid search is applied to obtain the estimated SFO. The second previously proposed algorithm is the SFO estimation scheme proposed in [5], which estimates the SFO using cyclic delay diversity (CDD), based on the pilot carriers having maximum channel powers. We note that while CDD is designed for MISO channels, we assume that the estimator can achieve periodicity of the channel in the current setup -which is an assumption which favors CDD.…”

Section: B Performance Comparison With Previous Workmentioning

confidence: 99%

“…In the class of DA schemes we note the work in [4], which presents a DA SFO estimation algorithm for OFDM communications based on exploiting the phase differences between the pilot symbols. In [5], the authors propose an algorithm for SFO estimation using the channel frequency response, where pilot patterns with a maximum channel power (i.e., the magnitude-squared of the channel frequency response) are chosen to facilitate robustness of the estimate with respect to the frequency-selectivity of the channel. In [6], a DA algorithm for the joint acquisition of the SFO and the CFO for OFDM signals is proposed.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Sampling Frequency Offset Estimation Algorithm for OFDM Systems Based on Cyclostationary Properties

Kumar

Dabora

2019

IEEE Access

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Sampling frequency synchronization in orthogonal frequency division multiplexing (OFDM) communications is critical for achieving the full advantages offered by this modulation scheme. In this paper, we propose a novel and efficient, blind, cyclostationarity-based sampling frequency synchronization (CB-SFS) algorithm for estimating the sampling frequency offset (SFO) in OFDM communications by exploiting the relationship between the sampling frequency and the cyclostationary properties of the sampled received signal. The proposed scheme is ignorant of the channel coefficients and does not require pilots. These two properties are rather unique in this context and are not possessed by previous schemes which achieve comparable estimation performance. These properties also make the proposed CB-SFS scheme suitable for a wide range of communications scenarios. The main novelty of the new scheme is the understanding that SFO alters the cycle frequencies at the receiver, yet these frequencies are a priori known for the discretetime (DT) transmitted signal, as they result from the periodic operation of the DT signal generation scheme at the transmitter. We show that the mismatch between the measured and the expected cycle frequencies is directly related to the SFO. Complexity analysis and numerical simulations are carried out and demonstrate the superiority of the proposed CB-SFS algorithm compared to the existing approaches. It is illustrated that the proposed algorithm can achieve a smaller estimation error at the same complexity order of current algorithms while providing a higher spectral efficiency and robustness to additive stationary noise and to multipath.INDEX TERMS Orthogonal frequency division multiplexing, sampling frequency offset, synchronization, cyclostationary processes, almost cyclostationary processes.

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Section: B Performance Comparison With Previous Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Sampling Frequency Offset Estimation Algorithm for OFDM Systems Based on Cyclostationary Properties

Kumar

Dabora

2019

IEEE Access

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“…A number of CFO and SFO estimation algorithms have been studied throughout the years. These studied algorithms can be classified into two types: blind algorithms that do not use pilot symbols [7][8][9] and data-aided (DA) [10][11][12][13][14][15][16][17][18][19][20] algorithms using pilot symbols. Because of their simple form and computational convenience, DA methods have received more attention and are considered in this paper.…”

Section: Introductionmentioning

confidence: 99%

“…ML estimation requires at least a onedimensional exhaustive search and is not suitable for hardware implementation. Therefore, many DA suboptimal linear algorithms have been suggested [14][15][16][17][18]. A simple joint CFO and SFO estimation was presented in [14], where the value of the CFO was estimated for every symbol, but the SFO was derived from the early estimation of the CFO, resulting in a residual SFO and performance decrease.…”

Section: Introductionmentioning

confidence: 99%

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Successive Interference Cancellation-Based Weighted Least-Squares Estimation of Carrier and Sampling Frequency Offsets for WLANs

Zhou

Zheng

et al. 2020

IEEE Access

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A successive interference cancellation (SIC)-based weighted least-squares (WLS) estimation for the carrier frequency offset (CFO) and the sampling frequency offset (SFO) is presented for wireless local area networks (WLANs) based on orthogonal frequency division multiplexing (OFDM). The proposed SIC-based WLS performs the estimation by exploiting the phase rotation in the frequency domain caused by the CFO and the SFO. SIC-based WLS estimates the CFO and the SFO successively instead of by traditional simultaneous estimation. The estimation of CFO based on the Taylor series is performed first, and then the WLS estimation of SFO based on successive cancellation of the CFO is carried out. The simulation results show that the SIC-based WLS can estimate the CFO and the SFO effectively. Compared to the WLS scheme, a performance improvement of more than 0.6 dB is achieved by SIC-based WLS, and nearly 10 percent of the complexity is reduced.

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Hybrid Cramer-Rao Bound on Carrier and Sampling Frequency Offset Estimation for OFDM Systems in Rayleigh Fading Channels

Cheng

Russell

2022

Wireless Pers Commun

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For the carrier frequency offset (CFO) and sampling (clock) frequency offset (SFO) estimation, the hybrid Cramer-Rao bound (HCRB) is developed when the CFO, SFO, information-bearing symbols are deterministic and channel coefficients are random. Both noise and channel coefficients are complex Gaussian. The HCRB is a lower bound on the mean squared estimation error for any unbiased estimator of a parameter. For the HCRB to be applicable, it is necessary for deterministic parameters to be identifiable (uniquely determined). Some necessary identifiability conditions of some deterministic parameters are found and presented. The HCRB is dependent on the initial time instant. The HCRB is used to assess the performances of some existing methods via simulation. Our results demonstrate that even the best performance is still around 10 dB higher than the HCRB. Further effort is needed to develop more accurate methods.

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Joint Estimation of Symbol Timing and Sampling Frequency Offset for CDD-OFDM-Based DRM Systems

Cited by 7 publications

References 21 publications

A Novel Sampling Frequency Offset Estimation Algorithm for OFDM Systems Based on Cyclostationary Properties

A Novel Sampling Frequency Offset Estimation Algorithm for OFDM Systems Based on Cyclostationary Properties

Successive Interference Cancellation-Based Weighted Least-Squares Estimation of Carrier and Sampling Frequency Offsets for WLANs

Hybrid Cramer-Rao Bound on Carrier and Sampling Frequency Offset Estimation for OFDM Systems in Rayleigh Fading Channels

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