Approximated Maximum Likelihood Estimation of Carrier Frequency Offset in Practical OFDM Systems

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 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.

In this paper, we propose a hybrid scheme for the carrier frequency offset (CFO) estimation in OFDM communication systems. The main novelty of the approach is the judicious combination of two methods so as to reduce the bandwidth overhead and computational complexity without compromising the estimation range. The cyclic prefix (CP) associated with the OFDM symbols are used for the fractional frequency offset estimation. The integer frequency offset is estimated by means of a cost function minimization employing a few null subcarriers, which are allocated using a modified Fibonacci series. Performance of the frequency offset estimator is mathematically analyzed by deriving the Cramer-Rao bound (CRB) and is compared with the mean square error performance of the estimator. For moderate SNRs, our algorithm is shown to outperform some existing methods in terms of MSE (and thereby BER) performance, training overhead and receiver complexity.

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

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 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.

In the uplink of an orthogonal frequency division multiple access (OFDMA) system, because of multiple access interference (MAI), carrier frequency offset (CFO) estimation is much more difficult than that in single-user systems. This paper proposes a null subcarrier-based iterative CFO estimation method for the uplink of OFDMA system adopting sub-band based carrier assignment scheme. Rather than applying independent estimations for users separated by bandpass filters, we first obtain an inaccurate initial CFO estimate for each user. Then, we run an iterative scheme which could update the estimates and reduce errors iteration by iteration. The performance of the proposed method is evaluated by simulations.

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.

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.

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.

Although fruitful studies have been conducted on carrier frequency offset (CFO) estimations in linear coherent optical fiber communication systems, there are few studies on CFO estimations and recoveries in the systems based on the nonlinear Fourier transform (NFT). Although the CFO is originated from the linear frequency domain, it definitely has effects on nonlinear spectra, including the shift of the nonlinear frequency and the phase rotations of the scattering data, which are similar to its effects on linear spectra. This work indicates that it is feasible to estimate frequency offset (FO) by capturing symbol variations in the nonlinear frequency domain (NFD) rather than in the linear frequency domain; the latter was usually exploited in the literature. Based on a thorough investigation of the FO induced behavior that appears in a nonlinear frequency division multiplexing (NFDM) system, we proposed a nonlinear frequency domain estimation method aided by training symbols (TS) using an angle search algorithm after NFT operations at the receiver. The discussions in this paper prove that the proposed method is generally applicable to the NFDM systems regardless of whether using single or multiple eigenvalues. A performance comparison between the NFD method and the conventional method in the linear frequency domain is performed with different modulation formats for both single and multiple eigenvalue NFDM transmission systems. The analysis results show that the proposed method holds the better stability and estimation accuracy in contrast with the linear domain estimation method. The TS overhead can also be deduced dramatically, which implies better transmission efficiency. Therefore, the NFD method is more powerful for eigenvalue NFDM transmission systems, especially for the scenarios where high order modulation formats and multiple eigenvalues are utilized.

The frequency synchronization issue of multiuser in the uplink of an orthogonal frequency-division multiple-access (OFDMA) system is investigated in this letter. We develop a subspace based blind carrier frequency offsets (CFOs) estimation algorithm for the base station (BS) equipped with uniform linear array (ULA). Due to the adoption of ULA at the BS and the narrowband signal assumption, CFOs of different users can be separated by their spatial information. Thus, unlike existing blind alternatives, which are subject to some specific carrier assignment schemes (CAS) or rely on null subcarriers, our proposed method can support generalized carrier assignment scheme (GCAS) and fully loaded systems, i.e., all subcarriers are available to users. Consequently, the dynamic channel assignment is available and the bandwidth efficiency is higher. Moreover, the closed-form directions of arrival (DOAs) of all active users are also obtained, which can be used in downlink beamforming in frequency division duplex (FDD) systems. Performance of the proposed scheme is evaluated by computer Monte Carlo simulations.

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

In this paper, we study carrier frequency offset (CFO) and symbol timing offset (STO) estimation in the uplink of multiuser offset QAM filter bank multicarrier (FBMC) communication systems. A low-complexity frequency-domain CFO estimator using periodical training sequence is proposed. Also a good estimate of STO is obtained by maximizing the energy of subcarriers subject to training sequence at the output of analysis filter bank. Furthermore we derive the theoretical MSE for the proposed CFO estimator. Computer simulations show that the derived MSE matches the simulated MSE closely. Compared with state-of-the-art time domain estimator, the proposed estimator achieves better performance with a lower computational complexity.

In this paper, we propose a method for joint estimation of carrier frequency offsets (CFO) of multiple active users in an orthogonal frequency division multiple access (OFDMA) uplink using the recently-developed bat algorithm. An initialization technique that can drastically reduce the total computational complexity of joint maximum likelihood (ML) estimation problems is employed to make the metaheuristic bat algorithm more efficient. This initialization improves the convergence rate of the estimator and thus reduces its total computational load in a significant manner. The CFO estimates obtained from the proposed method are also characterized by low mean square error values compared to a conventional implementation of the bat algorithm for the problem. The efficacy of the proposed method is substantiated through computer simulation studies.