This letter deals with joint carrier frequency offset (CFO) and direction of arrival (DOA) estimation based on the minimum variance distortionless response (MVDR) criterion for interleaved orthogonal frequency division multiple access (OFDMA)/space division multiple access (SDMA) uplink systems. In order to reduce the computational load of two-dimensional searching based methods, the proposed method includes only once polynomial CFO rooting and does not require DOA paring, hence it raises the searching efficiency. Several simulation results are provided to illustrate the effectiveness of the proposed method.

Orthogonal frequency division multiplexing (OFDM) is very sensitive to the carrier frequency offset (CFO). The CFO estimation precision heavily makes impacts on the OFDM performance. In this paper, a new Bayesian learning-assisted joint CFO tracking and channel impulse response estimation is proposed. The proposed algorithm is modified from a Bayesian learning-assisted estimation (BLAE) algorithm in the literature. The BLAE is expectation-maximization (EM)-based and displays the estimator mean square error (MSE) lower than the Cramer-Rao bound (CRB) when the CFO value is near zero. However, its MSE value may increase quickly as the CFO value goes away from zero. Hence, the CFO estimator of the BLAE is replaced to solve the problem. Originally, the design criterion of the single-time-sample (STS) CFO estimator in the literature is maximum likelihood (ML)-based. Its MSE performance can reach the CRB. Also, its CFO estimation range can reach the widest range required for a CFO tracking estimator. For a CFO normalized by the sub-carrier spacing, the widest tracking range required is from -0.5 to +0.5. Here, we apply the STS CFO estimator design method to the EM-based Bayesian learning framework. The resultant Bayesian learning-assisted STS algorithm displays the MSE performance lower than the CRB, and its CFO estimation range is between ±0.5. With such a Bayesian learning design criterion, the additional channel noise power and power delay profile must be estimated, as compared with the ML-based design criterion. With the additional channel statistical information, the derived algorithm presents the MSE performance better than the CRB. Two frequency-selective channels are adopted for computer simulations. One has fixed tap weights, and the other is Rayleigh fading. Comparisons with the most related algorithms are also been provided.

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.

This paper describes a method to evaluate the modulated waveforms output by a high-speed external phase modulator over a wide wavelength range by using linear optical sampling (LOS) and a wavelength-swept light source. The phase-modulated waveform is sampled by LOS together with the reference signal before modulation, and the modulation waveform is observed by removing the phase noise of the light source extracted from the reference signal. In this process, the frequency offset caused by the optical-path length difference between the measurement and reference interferometers is removed by digital signal processing. A pseudo-random binary-sequence modulated signal is observed with a temporal resolution of 10ps. We obtained a dynamic range of ∼40dB for the measurement bandwidth of 10 nm. When the measurement bandwidth is expanded to entire C-Band (∼35nm), the dynamic ranges of 37∼46dB were observed, depending on the wavelengths. The measurement time was sub-seconds throughout the experiment.

This paper proposes a physical-layer cell identity (PCID) detection method that uses joint estimation of the frequency offset and secondary synchronization signal (SSS) sequence for the 5G new radio (NR) initial access with beamforming transmission at a base station. Computer simulation results show that using the PCID detection method with the proposed joint estimation yields an almost identical PCID detection probability as the primary synchronization signal (PSS) detection probability at an average received signal-to-noise ratio (SNR) of higher than approximately -5dB suggesting that the residual frequency offset is compensated to a sufficiently low level for the SSS sequence estimation. It is also shown that the PCID detection method achieves a high PCID detection probability of greater than 90% and 50% at the carrier frequency of 30 and 50GHz, respectively, at the average received SNR of 0dB for the frequency stability of a user equipment oscillator of 3ppm.

This paper presents the physical-layer cell identity (PCID) detection probability using the narrowband primary synchronization signal (NPSS) and narrowband secondary synchronization signal (NSSS) based on the narrowband Internet-of-Things (NB-IoT) radio interface considering frequency offset and the maximum Doppler frequency in the 28-GHz band. Simulation results show that the autocorrelation based NPSS detection method is more effective than the cross-correlation based NPSS detection using frequency offset estimation and compensation before the NPSS received timing detection from the viewpoints of PCID detection probability and computational complexity. We also show that when using autocorrelation based NPSS detection, the loss in the PCID detection probability at the carrier frequency of fc =28GHz compared to that for fc =3.5GHz is only approximately 5% at the average received signal-to-noise ratio (SNR) of 0dB when the frequency stability of a local oscillator of a user equipment (UE) set is 20ppm. Therefore, we conclude that the multiplexing schemes and sequences of NPSS and NSSS based on the NB-IoT radio interface associated with autocorrelation based NPSS detection will support the 28-GHz frequency spectra.

This paper presents the physical-layer cell identity (PCID) detection probability using the primary synchronization signal (PSS) and secondary synchronization signal (SSS) for the New Radio (NR) radio interface considering a large frequency offset and high Doppler frequency in multipath Rayleigh fading channels in the 28-GHz band. Simulation results show that cross-correlation based PSS detection after compensating for the frequency offset achieves higher PCID detection probability than autocorrelation based PSS detection at the average received signal-to-noise power ratio (SNR) values below approximately 0dB for the frequency stability of a user equipment (UE) oscillator of ϵ =5ppm. Meanwhile, both methods achieve almost the same PCID detection probability for average received SNR values higher than approximately 0dB. We also show that even with the large frequency offset caused by ϵ =20 ppm, the high PCID detection probability of approximately 90 (97)% and 90 (96)% is achieved for the cross-correlation or autocorrelation based PSS detection method, respectively, at the average received SNR of 0dB for the subcarrier spacing of 120 (240)kHz. We conclude that utilizing the multiplexing scheme for the PSS and SSS and their sequences is effective in achieving a high PCID detection probability considering a large frequency offset even with the frequency deviation of ϵ =20ppm in the 28-GHz band.

Universal filtered multicarrier (UFMC) systems offer a flexibility of filtering sub-bands with arbitrary bandwidth to suppress out-of-band (OoB) emission, while keeping the orthogonality between subcarriers in one sub-band. Oscillator discrepancies between the transmitter and receiver induce carrier frequency offset (CFO) in practical systems. In this paper, we propose a novel CFO estimation method for UFMC systems that has very low computational complexity and can then be used in practical systems. In order to fully exploit the coherence bandwidth of the channel, the training symbols are designed to have several identical segments in the frequency domain. As a result, the integral part of CFO can be estimated by simply determining the correlation between received signal and the training symbol. Simulation results show that the proposed method can achieve almost the same performance as an existing method and even a better performance in channels that have small decay parameter values. The proposed method can also be used in other multicarrier systems, such as orthogonal frequency division multiplexing (OFDM).

In this letter, the performance of a state-of-the-art deep learning (DL) algorithm in [5] is analyzed and evaluated for orthogonal frequency-division multiplexing (OFDM) receivers, in the presence of harmonic spur interference. Moreover, a novel spur cancellation receiver structure and algorithm are proposed to enhance the traditional OFDM receivers, and serve as a performance benchmark for the DL algorithm. It is found that the DL algorithm outperforms the traditional algorithm and is much more robust to spur carrier frequency offset.

A simple and novel multiple-symbol differential detection (MSDD) scheme is proposed for IEEE 802.15.4 binary phase shift keying (BPSK) receivers. The detection is initiated by estimating and compensating the carrier frequency offset (CFO) effect in the chip sample of interest. With these new statistics, the decisions are jointly made by allowing the observation window length to be longer than two bit intervals. Simulation results demonstrate that detection reliability of the IEEE 802.15.4 BPSK receivers is significantly improved. Namely, at packet error rate (PER) of 1×10-3, the signal-to-noise ratio (SNR) gap between ideal coherent detection (perfect carrier reference phase and no CFO) with differential decoding and conventional optimal single differential coherent detection (SDCD) is filled by 2.1dB when the observation window length is set to 6bit intervals. Then, the benefit that less energy consumed by retransmissions is successfully achieved.

In this letter, we analyze performances of a frequency offset estimation based on the maximum likelihood criterion and provide a theoretical proof that the mean squared error of the estimation grows with increase in the offset. Moreover, we propose a new iterative offset estimation method based on the analysis. By computer simulations, we show that the proposed estimator can achieve the lowest estimation error after a few iterations.

Timing and frequency offsets are caused by imperfect synchronization at the receiver. These errors degrade the performance of OFDM systems by introducing inter-carrier-interference (ICI) and inter-symbol-interference (ISI). In this paper, we derive signal-to-interference ratio (SIR) analytically with timing and frequency offsets for the case that the sampling rate of analog-to-digital converter (ADC) in OFDM receiver is an integer fraction of the signal bandwidth. We find the exact form of interference power as a function of the fractional sampling rate. Our derived analysis is confirmed by simulations and can be applied to see the exact performance of OFDM systems with fractional sampling rate.

In this letter, standard particle swarm optimization (PSO) with the center-symmetric trimmed correlation matrix and the orthogonal projection technique is firstly presented for blind carrier frequency offset estimation under interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. It doesn't require eigenvalue decomposition and only needs a single OFDMA data block. Second, this letter also presents adaptive multiple inertia weights with Newton method to speed up the convergence of standard PSO iteration process. Meanwhile, the advantage of inherent interleaved OFDMA signal structure also is exploited to conquer the problems of local optimization and the effect of ambiguous peaks for the proposed approaches. Finally, several simulation results are provided for illustration and comparison.

This paper describes a blind frequency offset estimator (FOE) with wide frequency range for coherent quadrature amplitude modulation (QAM) receivers. The FOE combines a spectrum-based frequency offset estimation algorithm as a coarse estimator with a frequency offset estimation algorithm using the periodogram as a fine estimator. To establish our design methodology, each block of the FOE is rigorously analyzed by using formulas and the minimum fast Fourier transform (FFT) size that generates a frequency spectrum for both the coarse and fine estimators is determined. The coarse estimator's main feature is that all estimation processes are carried out in the frequency domain, which yields convergence more than five times faster than that of conventional estimators. The estimation frequency range of the entire FOE is more than 1.8 times wider than that of conventional FOEs. Experiments on coherent optical 64-ary QAM (64-QAM) reveal that frequency offset estimation can be achieved under a frequency offset value greater than the highest value of the conventional estimation range.

In this paper, an interference rejection combining (IRC) technique is proposed for SFBC-OFDM cellular systems that exhibit multiple carrier frequency offsets (CFOs). The IRC weight and the corresponding value for CFO compensation in the proposed technique are obtained by maximizing the post-SINR, i.e., minimizing both the interference signal and inter-channel interference (ICI) terms caused by multiple CFOs. The performance of the conventional IRC and proposed IRC techniques is evaluated by computer simulation for an SFBC-OFDM cellular system with multiple CFOs.

A low-complexity time-frequency multiplex estimator and low-complexity equalizer transceiver design are proposed to combat the problems of RF impairment associated with zero-IF transceiver of multi-carrier systems. Moreover, the proposed preambles can estimate the transmitter (TX) in-phase and quadrature-phase (IQ) imbalance, carrier frequency offset (CFO), and channel impulse response parameters. The proposed system has two parts. First, all parameters of the impairments are estimated by the designed time-frequency multiplex estimator. Second, the estimated parameters are used to compensate the above problems and detect the transmitted signal with low complexity. Simulation results confirm that the proposed estimator performs reliably with respect to IQ imbalance, CFO, and multipath fading channel effects.

This letter deals with the carrier frequency offsets (CFO) estimation problem for orthogonal frequency division multiple access (OFDMA) uplink systems. Combined with centro-symmetric (CS) trimmed autocorrelation matrix and weighting subspace projection, the proposed estimator has better estimate performance than MVDR, MUSIC, CS-MUSIC, and ESPRIT estimators, especially in relatively less of OFDMA blocks and low SNR situations. Simulation results are presented to verify the efficiency of the proposed estimator.

In this letter, we propose a simple algorithm to jointly estimate the symbol timing offset (STO) and carrier frequency offset (CFO) of wireless body area network (WBAN) signals. The preamble specified in IEEE 802.15.6 WBAN is used to achieve an accurate timing and frequency estimation based on the differential correlation. Simulations demonstrate that the proposed joint estimation scheme can be effectively employed to get accurate STO and CFO estimate with less complexity.

We have proposed an intruder detection method by using multiple-input multiple-output (MIMO) channels. Although the channel capacity for MIMO transmission is severely degraded in time-variant channels, we can take advantage of this feature in MIMO sensor applications. For MIMO sensors, the accurate estimation of channel state information (CSI) is essential. Moreover, the transceiver should be simplified from the viewpoint of saving power. Narrowband signals such as minimum shift keying (MSK) and offset quaternary phase shift keying signals are effective and are used in sensor network systems. However, because the timing and carrier offsets between the transmitter and receiver are relatively large compared to the symbol rate, accurate CSI estimation is impossible given the severe constraints imposed by the timing and carrier offsets. To solve this issue, a signal synchronization method for the CSI estimation using a narrowband MSK signal has been proposed. In this paper, we propose a new CSI estimation method for arbitrary amplitude and phase modulation schemes for the MIMO sensor. The key point of the proposed method is that control signals (unique words) are mapped so as not to pass through the origin of the complex I/Q plane. The estimation accuracy of the proposed method is evaluated via a computer simulation. Moreover, the basic performance by the proposed CSI estimation method is verified when considering intruder detection by MIMO sensor.

D2D (Device-to-Device) communication has received considerable attention in recent years as one of the key technologies for future communication systems. Among the typical D2D communication systems, FlashLinQ (FLQ) adopted single-tone OFDM (Orthogonal Frequency Division Multiplexing) transmission which enables wide-sense discovery and distributed channel-aware link scheduling. Although synchronization based on a CES (Common External Source) is basically assumed in FLQ, a means to support devices when they are unable to use a CES is still necessary. In most OFDM systems, CFO (Carrier Frequency Offset) induces ICI (Inter Channel Interference) which degrades overall system performance drastically. Especially in D2D systems, ICI can be amplified due to different path losses between link and a precise estimation and correction of CFO is very important. Many CFO estimation algorithms based on DA (Data Aided) and NDA (None Data Aided) were proposed for OFDM systems, but there are several constraint conditions on frequency synchronization in D2D systems. Therefore, in this paper, we propose a new NDA-CFO estimation method for OFDM based D2D systems. The proposed method is based on the characteristics of single-tone OFDM signal, and is composed of two estimation stages: initial estimation and feed-back estimation. In initial estimation, the estimation of CFO is obtained by using two correlation results in a symbol. Also, estimation range can be adaptively defined as the distance between the two windows. In feed-back estimation, the distance between the two correlation results is gradually increased by re-using the estimated CFO and the correlation results. Therefore, more precise CFO estimation can be obtained. A numerical analysis and performance evaluation verify that the proposed method has a large estimation range and achieves precise estimation performance compared to the conventional methods.