Deep-Learning-Based Carrier Frequency Offset Estimation and Its Cross-Evaluation in Multiple-Channel Models

The paper proposes a novel estimation scheme of carrier frequency offset (CFO) based on Added Preamble Sequence Semi-Blind (APSSB) scheme. The proposed CFO estimator is based on APSSB OFDMA model in which Gold sequence is added to the output of IDFT modulator and exploited for CFO estimation at the receiver. CFO estimators based on APSSB scheme and preamble are compared by both SINR analysis and simulation. We propose that the APSSB scheme should be employed for fine frequency synchronization in OFDMA especially in delay- insensitive service. In this paper, we propose the APSSB OFDMA model in which APSSB sequence is added to the output of IFFT modulator. The APSSB sequence is exploited for CFO estimation by correlation detection with the local APSSB sequence at the receiver. Comparison of SINR is made between CFO estimation schemes based on APSSB and preamble. More accurate CFO estimation by APSSB scheme doesn't cause date rate decrease because data and APSSB sequence are transmitted simultaneously. Furthermore, CFO estimation of APSSB scheme is more accurate than preamble scheme when APSSB symbol number for CFO estimation is large enough to exceed the threshold. Furthermore, the estimation time of APSSB scheme is more flexible than preamble scheme. The APSSB scheme has the property of better accuracy as well as larger delay. We propose the APSSB scheme should be employed for fine frequency synchronization in delay- insensitive service.

In recent years, the constant-envelope orthogonal frequency-division multiplexing (CE-OFDM) has been considered as a candidate waveform in broadband satellite systems as it has a 0-dB peak-to-average power ratio (PAPR). However, the carrier frequency offset (CFO) estimation scheme for CE-OFDM broadband satellite systems directly affects system performance. In this paper, we analyze the network architecture and the propagation environment of CE-OFDM broadband satellite systems, and we propose a data-aided CFO estimation strategy based on the frequency domain pilot symbols. The Cramer–Rao bound (CRB) of our CFO estimator is given by mathematical analysis, and the effect of the number of pilot symbols on the estimation performance is analyzed. The pilot symbol-based CFO estimator is composed of a phase demodulator and a discrete Fourier transform (DFT) module, and it can obtain a large estimation range under a small pilot overhead. The simulation results show that the CE-OFDM broadband satellite systems can achieve a good bit error rate (BER) performance by using the proposed strategy to estimate and compensate the CFO.

In this paper we propose a non-data aided estimator for joint time delay, carrier frequency offset (CFO) and channel estimation for uplink asynchronous CDMA system. The cost function for CFO estimation is a determinant of a matrix, which is a function of the CFO. The CFO estimator does the estimation by performing a linear search and the search point which minimizes the determinant is the estimated CFO. The matrix corresponding to the estimated CFO is used for channel estimation, where the channel impulse response (CIR) is obtained as the eigenvector corresponding to the minimum eigenvalue of that matrix. Time synchronization is inherently done along with the channel estimation, assuming the maximum channel order for all user channels is known. We also modify the existing estimator based on generalized eigenvalue problem (GEVP) and show the performance improvement through computer simulations. The performance of the proposed method is compared with the modified generalized eigenvalue problem method (MGEVPM). Computer simulations show that the proposed estimator performs better than MGEVPM and has wider CFO acquisition range than MGEVPM. Using Taylor's series approximation, we reformulate the proposed estimator in order to reduce the computational complexity. Through computer simulations we show that the performance of the reformulated estimator improves with increase in the order of Taylor's series and performs better than MGEVPM.

The carrier frequency offset (CFO) estimation is an important task for orthogonal frequency-division multiple-access (OFDMA) systems. Making use of the intrinsic periodic structure of the received signal samples, an effective Unitary-ESPRIT algorithm based on unitary transformation technique is proposed for the CFO estimation problem. Compared with other recently proposed CFO estimation approaches, the proposed algorithm offers a number of advantages. Firstly, the presented approach can reduce the computation complexity considerably, since it is efficiently formulated in terms of real-valued computation except for the data preprocessing. Secondly, it can provide better CFO estimation performance by incorporating the data stacking technology and the unitary transformation, etc. Simulation results demonstrate the efficacy of the proposed algorithm.

The paper deals with the problem of the carrier frequency-offset (CFO) estimation for wireless communications. Since the well-known maximum-likelihood (ML) CFO estimator is rather complex, many complexity-reduced CFO estimators have so far been proposed. However, most of them are based on periodic training sequences and have limited estimation range. We propose a general framework called composite frequency- offset estimator (CFE), which can extend the estimation range of any range-limited correlation-based CFO estimator up to the full transmission spectrum. We first formulate the CFO estimation as a problem of composite hypothesis testing, and then solve the problem by the composite hypothesis testing approaches. We show that the composite frequency-offset estimate is the ML estimate as long as the original range-limited estimator is unbiased and attains the Cramer-Rao Lower Bound. The CFE also allows a flexible tradeoff between the estimation range and computational complexity. Finally, numerical results show the efficiency of the proposed method.

In this paper, we propose a low-complexity carrier frequency offset (CFO) estimation algorithm for OFDM based wireless LAN, IEEE 802.11a. The complexity of the arctangent operation to calculate the argument of auto-correlation for CFO estimation is reduced by a novel range pointer method. The proposed algorithm estimates fine CFO value first and then based on the fine CFO value, simple criteria is used for the boundary decision of integer CFO estimation. The simulation results show that the performance of the proposed algorithm is slightly better than the conventional method while the computational complexity is reduced by 50%. Furthermore, the proposed method can be easily implemented for the low complex next generation MIMO-OFDM based WLAN systems.

Orthogonal frequency division multiplexing (OFDM) has been adopted in various wireless communication standards to exploit its high spectral efficiency and robustness against multipath fading channels. Along with the potential benefits of OFDM transmissions, a stringent requirement on orthogonality among subcarriers makes OFDM highly susceptible to synchronization errors, i.e., time and frequency offsets. Addressing the carrier frequency offset (CFO) estimation problem, the paper proposes a pilot-aided CFO estimation scheme for both coarse and fine carrier frequency synchronization in single-input single-output (SISO) OFDM receivers. By exploiting the maximum likelihood (ML) principle, the proposed ML-based CFO estimation algorithm functions properly over a wide range of CFO values and outperforms existing correlation-based schemes.

An uplink OFDMA systems is considered. Different users use different transmit antennas, thus, each user contributes a different carrier frequency offset (CFO) at the receiver. The multiple CFOs introduce intercarrier interference, thus impeding user separation and transmit signal recovery. A low complexity CFO estimation approach is proposed for estimating multiple CFOs. The proposed approach relies on one or more pilot symbols per user which are placed far from each other and each one carries the same symbol over a number of successive blocks. A user's CFO is obtained based on averaging over consecutive OFDM blocks of the symbols corresponding to the pilot tones of that user. Simulation results suggest that accurate CFOs estimation is possible with a very small amount of averaging, which makes the method applicable to the case of slowly varying channels. The proposed approach does not require channel state information, which is important as channel state information cannot be easily obtained before CFO correction.

Carrier frequency offset (CFO) is one of the most important problems in an orthogonal frequency division mul- tiplexing (OFDM) system, which seriously degrades the perfor- mance of the systems due to its time-variant behavior. This paper suggests a pilot-less residual CFO estimator for ultra-wideband OFDM (UWB-OFDM) systems. The proposed scheme uses a time-domain spreaded data samples which is provided in UWB Wimedia OFDM system. To demonstrate the efficiency of the proposed pilot-less CFO estimator, analytical expression of the mean square error (MSE) is reported and comparisons are made with the conventional pilot-aided CFO estimator in terms of MSE, bit error rate (BER), and throughput.

In the uplink system, different carrier frequency offsets (CFO) of different users at the receiver resulting multiuser interference (MUI) and thus degrade the performance of Multicarrier Code Division Multiple Access (MC-CDMA) system. In the previous study, Modified Minimum Mean Square Error Frequency Domain Equalization (Modified MMSE-FDE) has been proposed by Agnihotri which results in a better performance than the conventional MMSE. However, the achieved Bit Error Rate (BER) is not smaller than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> for Signal to Noise Ratio (SNR) below 20. This paper proposed a new algorithm to improve Modified MMSE-FDE performance in mitigating multiuser interference (MUI) in single cell MC-CDMA system, that is called as Carrier Frequency Offset Estimation-Minimum Mean Square Error Frequency Domain Equalization (CFO Estimation-MMSE FEQ). CFO Estimation-MMSE FEQ takes into account the rest of MUI as well as Modified MMSE-FDE to design equalization coefficient, but CFO Estimation-MMSE FEQ uses CFO estimation that is not on Modified MMSE-FDE. The value of CFO is estimated and regenerated in the receiver and then used to estimate MUI. In order to get signal processing more efficient, CFO Estimation-MMSE FEQ only takes the real trace of equalization coefficient matrix. MC-CDMA with CFO Estimation-MMSE FEQ has better performance than MC-CDMA with Modified MMSE-FDE. However, the complexity of CFO Estimation-MMSE FEQ is higher than Modified MMSE-FDE. By taking only the real trace of equalization coefficient matrix, the complexity of CFO Estimation-MMSE FEQ is getting simpler than taking the whole of equalization coefficient matrix. Furthermore, CFO Estimation-MMSE FEQ that takes only the real trace of equalization coefficient matrix is 2.9 % more efficient than CFO Estimation-MMSE FEQ that takes the whole of equalization coefficient matrix.

In this paper, a fine carrier frequency offset (CFO) estimator is proposed for ultra-wideband multi-band orthogonal frequency division multiplexing (UWB MB-OFDM) systems. The proposed scheme uses a frequency domain spreaded data symbol which is provided in the MB-OFDM system. To demonstrate the efficiency of the proposed CFO estimator, comparisons are made with other existing estimator in terms of mean square error (MSE) and bit error rate (BER). Indexing Terms : UWB, MB-OFDM, carrier frequency offset, frequency-domain spreading

This study deals with the joint channel and carrier frequency offset (CFO) estimation in a Multiple Input Single Output (MISO) communications system. This problem arises in OFDM (Orthogonal Frequency Division Multiplexing) based multi-relay transmission protocols such that the geo-routing one proposed by A. Bader et al in 2012. Indeed, the outstanding performance of this multi-hop relaying scheme relies heavily on the channel and CFO estimation quality at the PHY layer. In this work, two approaches are considered: The first is based on estimating the overall channel (including the CFO) as a time-varying one using an adaptive scheme under the assumption of small or moderate CFOs while the second one performs separately, the channel and CFO parameters estimation based on the considered data model. The two solutions are analyzed and compared in terms of performance, cost and convergence rate.

OFDM (orthogonal frequency division multiplexing) is a promising technology for future broadband wireless communications due to its capability in combating multipath fading. Carrier frequency offset (CFO), which can induce the loss of orthogonality among OFDM sub-carriers and significant performance degradation, needs to be estimated and compensated for. In this paper, we propose a general CFO estimator based on the maximum likelihood (ML) estimation criterion. It will be shown that with the same estimator architecture, CFO can be obtained using either training OFDM symbols, pilot tones, null sub-carriers, or a combination of them. Furthermore, by taking advantage of the channel side information, the performance of CFO estimation can be significantly improved. To demonstrate the capability of the proposed CFO estimator, we will consider an OFDM system using the signal structure of the IEEE WLAN standard 802.11a. Compared with previous work using null sub-carriers alone, it will be shown that by taking advantage of the pilot tones, null sub-carriers, and the channel statistics, the performance of CFO estimation can be improved by about 2 dB

The estimation of carrier frequency offset (CFO) is an important issue in the study of the orthogonal frequency division multiplexing (OFDM) systems. In the past, many CFO estimation methods have been proposed. In this paper, we propose a new blind CFO estimation for OFDM systems based on the so-called remodulated received vectors [8]. The CFO estimate is given by a closed form formula. The proposed method has very low complexity and its performance is robust to different modulation symbols and the presence of virtual carriers.

The problem of pilot assisted carrier frequency offset (CFO) estimation in LTE system is investigated in this paper. Since both the pilot design and the number of pilot symbols are already fixed in LTE technical standards, it is proposed to employ multiple successive pilot symbols to improve the CFO estimation performance under the LTE standard constraints. We firstly present the generalized CRLB (GCRLB) analysis based on multiple successive pilot symbols. It is revealed that, better CFO estimate can be achieved by jointly using multiple successive pilot symbols than by using only one pilot symbol. The enhanced maximum likelihood (ML) carrier frequency offset estimate problem is formulated and simulation results are presented to validate that the proposed CFO estimate scheme offers an effective mechanism to improve the CFO estimate in practical LTE system.