Carrier Frequency Offset Estimation Method Research Articles

Virtual Array-Based Signal Detection and Carrier Frequency Offset Estimation in a Multistatic Collaborative Passive Detection System

To tackle the problem of difficult signal detection and carrier frequency synchronization faced by wireless communication among stations of the multistatic passive detection system in interference environments, an adaptive signal detection and carrier frequency offset (CFO) estimation method based on a virtual array is proposed in this paper. This is a data-aided method that utilizes a training sequence composed of three segments of sub-training sequences with different symbols. This method first uses spatial spectrum estimation to obtain the coarse frequency estimations of interference signals and CFO from virtual array signals constructed from the first two sub-training sequences. Then, beamforming is conducted accordingly on the virtual array signals constructed from the third sub-training sequence to suppress the in-band interferences and protrude the expected signal. Finally, improved performance of signal detection and CFO estimation is obtained with the beamformed signals. Simulation experiments show that a missed detection probability as low as 1 × 10−4, with a false detection probability of 1 × 10−3, can be obtained under a signal-to-interference ratio (SIR) of −10 dB and Eb/N0 of 1 dB. Moreover, the proposed method can also simultaneously achieve a CFO estimation error that is lower than 3%, with the condition of Eb/N0 being as low as −5 dB under different SIRs. Simulation results validate the proposed method and demonstrate the promising application prospects of the proposed method in networked passive detection scenarios.

Non-pilot based carrier frequency offset estimation and reflection coefficient optimization for RIS-assisted OFDM systems

Carrier frequency synchronization between the transmitter and receiver is challenging due to oscillator inaccuracies and Doppler shifts, which lead to inter-carrier interference. To address this synchronization error, i.e., carrier frequency offset (CFO), we introduce a novel method for estimating the CFO in reconfigurable intelligent surfaces (RIS)-assisted orthogonal frequency division multiplexing (OFDM) systems. Additionally, we present a method to optimize reflection coefficients, as adjusting the reflection coefficient of RIS can effectively manipulate signal propagation and amplitude, thereby enhancing system performance. In the proposed method, a randomized set of reflection coefficients is applied for the first OFDM symbol, and CFO is estimated using the oversampling method within that symbol over the Rayleigh fading environment. A deterministic approach is adopted to reduce grid search complexity. Simulation results demonstrate the superior performance of the proposed CFO estimation method, particularly in high signal-to-noise ratio scenarios, compared to the existing Zadoff Chu sequence-based estimator in terms of mean square error (MSE). Subsequently, the CFO is compensated in the second OFDM symbol using the estimated CFO, and the reflection coefficient is optimized by identifying the channel tap associated with the maximum channel impulse gain technique. The optimized reflection coefficient enhances system performance in terms of bit error rate (BER) for RIS-assisted OFDM systems.

Blind Carrier Frequency Offset Estimation in Weighted Fractional Fourier Transform Communication Systems

In this study, a blind carrier frequency offset (CFO) estimation method is proposed using the time-frequency symmetry of the transmitted signals of a weighted Fourier transform (WFrFT) communication system. Blind CFO estimation is achieved by focusing on the property that results in matching the signal waveforms before and after the Fourier transform when the WFrFT parameter is set to a certain value. Numerical simulations confirm that the proposed method is more resistant to Rayleigh fading than the conventional estimation methods.

Efficient Carrier Frequency Offset Estimation in Wireless Sensor Networks

The carrier frequency offset (CFO) estimation is a crucial problem in orthogonal frequency division multiplexing (OFDM) systems, especially for the enabling technologies in the Internet of Things, which demand stringent limitations of low cost, low power consumption, and wide ranges, like wireless sensor networks. In this letter, we propose an efficient CFO estimation method for OFDM systems with in- and quadrature-phase (IQ) imbalance, which combines the emerging multitask learning (MTL) with the channel residual energy (CRE) to reduce the average inferring time greatly. The MTL estimator can extract the correlated features between the CFO and the IQ imbalance so as to mitigate the intractable coupling effect. On the other hand, the CRE technique can guide the neural network and loss function design to improve the estimation accuracy and the training efficiency. Numerical results demonstrate that our proposal achieves high estimation accuracy while the inferring time is significantly reduced compared with other methods.

Novel Data-Aided Carrier Frequency Offset Compensation Methods Using Asymmetric-Shape Constellations for Burst-Mode Coherent Reception

This paper introduces a novel data-aided carrier frequency offset (CFO) estimation and compensation method for m-array phase shift keying (m-PSK) signals in burst-mode digital coherent reception. Its key advances are as follows; the use of newly designed training symbols (TS) that exhibit asymmetric distributed constellations after differential decoding and a vector summation based feed-forward CFO estimation algorithm. These offer short response time and strong robustness to training symbols (TS) timing detection error with wide CFO estimation range of ±B/2, where B is signal baudrate. We evaluate the feasibility of the proposal by simulations of and experiments on 12.5-Gbaud SP-QPSK signals that target optical budget enhancement of 25-Gbps/λ-class PONs to realize long-reach and high splitting ratio optical access. The 100-km burst-mode transmission experiments confirm the proposal offers high sensitivity detection of better than −43 dBm with much wider CFO range of above ±10 GHz.

Differential Evolution Algorithm-Aided Time-Varying Carrier Frequency Offset Estimation for OFDM Underwater Acoustic Communication

Orthogonal frequency division multiplexing (OFDM) is the preferred scheme for high-speed communication in the field of underwater acoustic communication. However, it is very sensitive to the carrier frequency offset (CFO). This study used a time-varying CFO estimation method aided by the differential evolution (DE) algorithm to accurately estimate the CFO of an OFDM system. This method was based on the principle that the received OFDM signal with inter-carrier interference could be considered by a Multi Carrier-code division multiple access (MC-CDMA) system on the receiver side because MC-CDMA is a technology that combines OFDM and code division multiple access (CMDA). Because it is suitable for solving problems where there are dependencies between adjacent variables, the DE algorithm was used to capture the varying CFO values on the adjacent blocks. The spreading code of the MC-CDMA was obtained based on the estimated CFO values, which were elements in the DE solutions. Then the received signal was reconstructed. The Root-Mean-Square Error between the reconstructed and actual received signals was used as the cost function, and the CFO was estimated using the DE algorithm because of its powerful parallel search capability. The simulation results showed that the proposed method had a high estimation accuracy. Compared with other intelligent optimization algorithms such as the genetic algorithm and simulated annealing mutated-genetic algorithm, the time-varying CFO estimation performance of the DE algorithm was better because of its unique ability to solve problems with dependencies between adjacent variables. Specifically, under the condition of a high signal-to-noise ratio, the improvement of estimation accuracy reaches 36.13%, and the Bit Error Rate of demodulation is thus reduced by 75%, compared with the reference algorithms. In addition, the proposed method also has good applicability to modulation methods. For phase-shift keying and quadrature amplitude modulation, in particular, the proposed method not only achieved high-precision time-varying CFO estimation values, but also reduced the demodulation deterioration caused by noise.

Low-Complexity Joint CFO and Channel Estimation for RIS-Aided OFDM Systems

Accurate channel estimation is essential for achieving the performance gains offered by reconfigurable intelligent surface (RIS)-aided wireless communications. A variety of channel estimation methods have been proposed for such systems; however, none of the existing methods takes into account the effect of synchronization errors such as carrier frequency offset (CFO). In general, CFO can significantly degrade the channel estimation performance of orthogonal frequency division multiplexing (OFDM) systems. Motivated by this, we investigate the effect of CFO on channel estimation for RIS-aided OFDM systems. Furthermore, we propose a joint CFO and channel impulse response (CIR) estimation method for these systems. Simulation results demonstrate the effectiveness of our proposed method, and also demonstrate that the use of time-domain rather than frequency-domain estimation in this context results in an improvement in the mean-squared error (MSE) performance of channel estimation as well as in a significantly lower overall computational complexity.

Estimasi Carrier Ferquency Offset menggunakan Timing Metric pada Sinyal OFDM

OFDM is one of technology that can be utilized in a variety of telecommunication systems that being widely developed today, for application in LAN, WLAN, 3G, 4G, or 5G. One of the problem faced by the OFDM technology that its sensitivity to Carrier Frequency Offset (CFO) and the lack of synchronization in the OFDM signal. This research aims to design the synchronization that estimates Carrier Frequency Offset (CFO) to obtain synchronization of OFDM signal, where the error of the estimated Carrier Frequency Offset can be obtained, minimized and better than previous studies. The CFO estimation method in this research is using the training symbol on the OFDM symbol and utilize the statistical characteristics of the timing metric. This researchs result shows the Mean Square Error (MSE) of estimated Carrier Frequency Offset to Carrier Frequency Offset input, with range MSE 9.43 x 10-3 at 0 dB SNR input and MSE 1.687 x 10-5 at 30 dB SNR input. If Signal to Noise Ratio is greater, then the value of the mean square error (MSE) will be smaller. The position of the timing metric for timing estimation also affects to CFO estimation. CFO estimation accuracy will be maximized when using maximum timing metric.

ICA based estimation and compensation of carrier frequency offset for MBOFDM based UWB systems

A carrier frequency offset (CFO) is addressed as a main type of wireless communication system imperfections in this paper. Carrier frequency offset (CFO) severely deteriorates the performance of OFDM receiver. Here an effective time domain CFO estimation and compensation method using symmetric subcarrier allocation (SCA) for multiband orthogonal frequency division multiplexing (MBOFDM) based ultra-wideband system is proposed. A data supported CFO estimation technique, which is robust to a larger offset, is presented as a novel method in compensation of CFO. An effective separation matrix scheme of OFDM signal with CFO is obtained. Subsequently, independent component analysis (ICA) based CFO estimation is stated. On fully exploiting the ECMA-368 preamble symbols, the proposed technique is capable for carrier frequency offset of 100 ppm, and the result is confirmed through simulations.

Novel Blind CFO Estimation Method for OFDM/OQAM System

To solve the performance degradation due to Carrier Frequency Offset (CFO) for OFDM/OQAM system, a new blind CFO estimation method is proposed in this letter. This method uses the header structure of the transmitted signal by considering that there is an OFDM/OQAM symbol of null-valued OQAM symbols before the first one and exploits the orthogonality among subcarriers as well as the orthogonality between synthesis and analysis filter banks to estimate the CFO. Therefore, without compromising the spectral efficiency of OFDM/OQAM system this method can estimate accurately the CFO. Simulation results illustrate the effectiveness of the proposed method.

Blind digital modulation classification for STBC‐OFDM system in presence of CFO and channels estimation errors

Here, the authors propose a robust blind digital modulation classification (BDMC) algorithm for space time block coding (STBC)-based MIMO-OFDM system in the presence of carrier frequency offset (CFO) and channel estimation errors. Previous papers published on the topic of modulation identification were limited to single-carrier systems operating over frequency-flat channels. The problem of joint channel and CFO estimation in conjunction with blind digital modulation classification for STBC-OFDM in frequency selective channel and in the presence of the impulsive noise has not been addressed before to the best of their knowledge. To cope with performance degradation of BDMC due to CFO and channels errors, they propose joint semi-blind CFO and channels estimation methods. Higher order statistics (HOS), used for feature extraction, are combined with pattern recognition methods to solve the modulation identification problem. The main contribution of their work is the development of estimators, the study of their impacts on the blind classification capability, and the use of simulations to demonstrate the superior performance of the proposed algorithms.

Analysis of CFO Estimation for QAM-FBMC Systems Considering Non-Orthogonal Prototype Filters

The carrier frequency offset (CFO) on the orthogonal waveforms such as orthogonal frequency division multiplexing and offset quadrature amplitude modulation filter-bank multi-carrier (QAM-FBMC) has been well studied. However, the impact of the CFO on the QAM-FBMC systems is more complicated because of non-orthogonal prototype filters. The unavoidable interference from the non-orthogonality makes pilot signal design difficult and makes it hard to estimate the CFO accurately. In this paper, we discover the impact of the CFO on QAM-FBMC systems, evaluate the procedures of the basic CFO estimation methods, and analyze the performances of the CFO estimations. For the integer part estimation of CFO, we propose the design of pilot symbol that has a prominent peak at pilot subcarrier location in the up-sampled frequency domain. For the fractional part estimation, we formulate the basic CFO estimation by using two adjacent pilot symbols, and we analyze the mean-squared error performances with linear approximation and Cramer-Rao lower bound. We compare the performance of the CFO estimator and analytic approach in the additive white Gaussian noise and the pedestrian channel and show that the proposed estimator works well in the non-orthogonal QAM-FBMC systems.

Low‐complexity search method for CFO estimation in GFDM

In this Letter, the authors propose a low-complexity search method for carrier frequency offset (CFO) estimation in generalised frequency division multiplexing (GFDM). The proposed technique does not have any limitations on CFO acquisition range while providing an accurate estimate. Compared with the existing solutions in the literature with the lowest complexity, the proposed technique brings at least an order of magnitude complexity reduction without any performance penalty. Finally, the numerical results and comparisons with the existing literature in terms of performance and complexity attest the efficacy of the proposed method.

Distributed signal processing for dense 5G IoT platforms: Networking, synchronization, interference detection and radio sensing

Driven by the fourth industrial revolution (Industry 4.0), future and emerging Internet of Things (IoT) technologies will be required to support unprecedented services and demanding applications for massive machine-type connectivity, with low latency, high reliability and distributed information processing capability. In this article, distributed signal processing methodologies are highlighted as enablers for next generation cloud-assisted IoT systems. The proposed distributed algorithms run inside a wireless cloud network (WCN) platform and are exploited for WCN self-organization, distributed synchronization, networking and sensing. The WCN can lease augmented communication and sensing services to off-the-shelf industrial wireless devices via a dense, self-organizing “cloud” of wireless nodes. The paper introduces, at first, the WCN architecture and illustrates an experimental case study inside a pilot industrial plant. Next, it proposes a re-design of consensus-based algorithms for enabling a selected set of distributed information processing functionalities within the WCN platform, with application in practical IoT scenarios. In particular, cooperative communication algorithms are adopted to support reliable communication services. Distributed timing and carrier frequency offset estimation methods are investigated to enable low-latency services through accurate synchronization. Autonomous identification of recurring interference patterns is proposed for multiple access coordination in the shared 5G spectrum. Finally, localization and vision applications based on distributed processing of wireless signals are investigated to support contact-free human–machine interfaces.

Mobile Lattice-Coded Physical-Layer Network Coding with Practical Channel Alignment

Physical-layer network coding (PNC) is a communications paradigm that exploits overlapped transmissions to boost the throughput of wireless relay networks. A high point of PNC research was a theoretical proof that PNC that makes use of nested lattice codes could approach the information-theoretic capacity of a two-way relay network (TWRN), where two end nodes communicate via a relay node. The capacity cannot be achieved by conventional methods of time-division or straightforward network coding. Many practical challenges, however, remain to be addressed before the full potential of lattice-coded PNC can be realized. Two major challenges are: (1) for good performance in lattice-coded PNC, channels of simultaneously transmitting nodes must be aligned; (2) for lattice-coded PNC to be practical, the complexity of lattice encoding at the transmitters and lattice decoding at the receiver must be reduced. We address these challenges and implement a first lattice-coded PNC system on a software-defined radio (SDR) platform. Specifically, we design and implement a low-overhead channel precoding system that accurately aligns the channels of distributed nodes. In our implementation, the nodes use low-cost temperature-compensated oscillators (TCXO) only—a consequent challenge is that the channel alignment must be done more frequently and more accurately compared with the use of expensive oscillators. The low overhead and accurate channel alignment are achieved by (1) a channel precoding system implemented over FPGA to realize fast feedback of channel state information; (2) a highly-accurate carrier frequency offset (CFO) estimation method; and (3) a partial-feedback channel estimation method that significantly reduces the amount of feedback information from the receiver to the transmitters for channel precoding at the transmitters. To reduce lattice encoding and decoding complexities, we adapt the low-density lattice code (LDLC) for use in PNC systems. Experiments show that our implemented lattice-coded PNC achieves better bit error rate performance compared with time-division and straightforward network coding systems. It also has good throughput performance in mobile non-LoS scenarios.

Performance of an Integer Carrier Frequency Offset Estimation Method in OFDM Systems

ABSTRACTIn this paper, an integer carrier frequency offset estimation method, based on the spectrum of a demodulated measurement, was studied and compared with another method, based on the null subspace spectrum of a measurement, by theoretical analysis and simulation. The impact of the fractional carrier frequency offset estimation is also studied. Contrary to the conclusion drawn by the authors of the former method, it is discovered, in this paper, that the former performs much worse than the latter for SUI-3 channels and Rayleigh channels, because its selection rule on null subcarriers, given by the demodulated measurement spectrum, is much more sensitive to channel deep fades. It is also proved in this paper that the former does not offer significant computational advantage over the latter.

Frequency Offset Estimation of Satellite-Based AIS Signals Based on Interpolated FFT

Aimed at addressing the problem of carrier synchronization for satellite-based Automatic Identification System (AIS) signals, a novel data-aided carrier frequency offset estimation method in the intermediate frequency is proposed in this paper. AIS signals use Gaussian Minimum Shift Keying (GMSK) for transmission, and a nonlinearity of the GMSK signal is shown to be a sine wave with frequency related to the carrier frequency offset. Based on that, this method constructs an auxiliary function with the available symbols to avoid the influence of the modulated phase information, and it estimates the frequency offset due to Doppler shift with a new interpolated FFT method. Moreover, this method performs better when the signals are filtered by band pass filter even through the bandwidth is as low as the 1/3 nominal bandwidth. Computer simulations are used to assess the synchronizer performance on AWGN channels.

Efficient Constant Modulus Based Carrier Frequency Offset Estimation for CO-OFDM Systems

This paper proposes a blind carrier frequency offset (CFO) estimation method for coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems, using constant modulus signaling. The proposed scheme is based on a robust cost-function, which deviates from the common assumption that the channel frequency response slowly varies either in time or frequency domain. The proposed method adopts a cost-function similar to the Godard's method for blind channel equalization. Using Monte Carlo simulations, the proposed method is shown to offer a superior performance compared to prominent existing methods, in a practical optical link scenario. Also, we show that the proposed cost-function can be approximated and expressed in a closed-form in such a way that the CFO estimate is obtained using only three trial values.

Joint estimation of carrier frequency and phase offset based on pilot symbols in quasi-constant envelope OFDM satellite systems

Spectral efficiency and energy efficiency are two important performance indicators of satellite systems. The Quasi-Constant Envelope Orthogonal Frequency Division Multiplexing (QCE-OFDM) technique can achieve both high spectral efficiency and low peak-to-average power ratio (PAPR). Therefore, the QCE-OFDM technique is considered as a promising candidate multi-carrier technique for satellite systems. However, the Doppler effect will cause the carrier frequency offset (CFO), and the non-ideal oscillator will cause the carrier phase offset (CPO) in satellite systems. The CFO and CPO will further result in the bit-error-rate (BER) performance degradation. Hence, it is important to estimate and compensate the CFO and CPO. This paper analyzes the effects of both CFO and CPO in QCE-OFDM satellite systems. Furthermore, we propose a joint CFO and CPO estimation method based on the pilot symbols in the frequency domain. In addition, the optimal pilot symbol structure with different pilot overheads is designed according to the minimum Cramer- Rao bound (CRB) criterion. Simulation results show that the estimation accuracy of the proposed method is close to the CRB.

Covariance-Fitting-Based Blind Carrier Frequency Offset Estimation Method for OFDM Systems

In this paper, a new unsupervised carrier frequency offset (CFO) estimation method is proposed for orthogonal frequency division multiplexing (OFDM) systems using constant modulus constellations. Under the assumption that the channel variation is slow within two adjacent OFDM symbols, the influence of the channel on corresponding subcarriers of the two OFDM symbols will be the same. Utilizing this feature, a robust cost function is formulated based on covariance fitting criterion between two nearby OFDM symbols, and the CFO is estimated by minimizing this objective function. The mean square error (MSE) and bit error rate (BER) performance of the proposed covariance-fitting-based CFO estimation method is compared with that of the prominent conventional estimation schemes under noisy multipath channels with high delay spreads and Doppler spreads. The effect of channel length on the performance of the proposed estimator is also investigated. Based on Monte Carlo simulations, it is shown that the proposed method is robust under different channel conditions and provides more accurate CFO estimates.