Initial Synchronization for Multi-Cell OFDMA Systems

Carrier frequency offset (CFO) is a major factor that degrades performance of the orthogonal frequency division multiplexing (OFDM) system. For orthogonal frequency division multiple access (OFDMA) uplink systems, there are multiple CFOs need to be estimated simultaneously, which is a very challenging task. Particle swarm optimization (PSO) algorithm has been recognized a potential approach for CFOs estimation. However, its performance deteriorates as the number of users increases due to insufficient particles diversity. To overcome this difficulty, an enhanced PSO called MRPSO is proposed to increase particles diversity by employing mutation and repulsive operations. Furthermore, a least square (LS) scheme is adopted to improve the estimated CFOs. Simulation results indicate that the proposed MRPSO attains best BER and MSE performances in CFOs estimation as compared to other PSO-based schemes.

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.

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.

In this paper, we deal with the multiple carrier frequency offsets (CFOs) estimation issues for orthogonal frequency-division multiple access (OFDMA) based uplink system. In such system, the interleaved carrier assignment scheme (CAS) has gained much attention for it brings maximum frequency diversity though it undergoes severe CFO problem than other schemes. The multiple-CFO estimation problem in this scheme uses a similar signal structure as that of Direction of Arrival (DOA) estimation problem in array signal processing, so subspace based multiple signal classification (MUSIC) algorithm can be exploited to estimate multiple CFOs. Compared with the conventional MUSIC algorithm utilizing eigenvalue decomposition of complex-value covariance matrix, the proposed unitary MUSIC and unitary root-MUSIC CFO estimation algorithms have comparable performance but lower computational complexity because of real-value covariance matrix used, which is verified by computer simulation.

Efficient carrier frequency offset estimation algorithm for generalized frequency division multiplexing systems

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 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 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 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.

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.

SUMMARYIn this paper, we propose a novel hybrid joint maximum‐likelihood estimator for carrier frequency offset (CFO), timing offset, and channel response of all users in the uplink of an orthogonal frequency division multiple access (OFDMA) system. The proposed estimation method significantly reduces complexity of this multiparameter, multidimensional optimization problem, using the concept of separation of the different user signals by means of newly defined projection operators. This projection technique is combined with the alternating projection method available in the literature to arrive at a new hybrid algorithm that offers significant performance advantages in terms of computational complexity and estimator performance. The joint estimation of the CFOs, timing offsets, and channel coefficients for all active users together at the base station of the OFDMA uplink is a rarely addressed task. The proposed method also offers the flexibility of application to any subcarrier assignment scheme used in OFDMA systems. Extensive simulation studies corroborate the advantages of the new hybrid method for all three estimation requirements in the multiuser OFDMA uplink. Copyright © 2012 John Wiley & Sons, Ltd.

In orthogonal frequency-division multiple access (OFDMA) systems, closely spaced and overlapped sub-carriers are divided into groups and assigned to multiple users for simultaneous transmission. However, carrier frequency offsets (CFOs) between the transmitter and the receiver destroy the orthogonality and introduce inter-carrier interference (ICI), resulting in multiple-access interference (MAI). By the inner structure of the received signals, this paper presents a novel CFO estimation algorithm for interleaved OFDMA uplink systems. The proposed algorithm exploits the idea of whitening the spatial covariance matrix of received signals to obtain the CFO estimates of all users. The proposed approach relies only on stationary second-order statistics that are based on a joint diagonalization of a set of covariance matrices. Simulation results illustrate the efficacy of the proposed algorithm.

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 study, the authors propose a blind carrier frequency offset (CFO) estimation method for the tile structure orthogonal frequency division multiple access (OFDMA) uplink with multi‐antenna receiver. They employ an iterative approach to extract the signal component for each user gradually and propose a carefully designed CFO estimator to update the CFO estimate during the iterative procedure. The key ingredient of the proposed method is using few subcarriers on both sides within each tile as the ‘guard subcarriers’, which can greatly mitigate the effect of multi‐user interference. The proposed method supports not only fully loaded transmissions, but also the generalised assignment scheme that provides the flexibility for dynamical resource allocation. The numerical results are provided, which indicate that the proposed method can almost converge to the analytical lower bound within a few iterative cycles. It is seen that the proposed method also outperforms the existing competitor with multi‐antenna receiver in terms of estimation performance, especially with few adopted blocks.