Timing Offset Estimation Research Articles

New Preamble Sequence for WiMAX System with Improved Synchronization Accuracy

Worldwide Interoperability for Microwave Access (WiMAX) trusts Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) combination for the deployment of physical layer functions and for connecting the medium access control to the wireless media. Even though Orthogonal Frequency Division Multiplexing (OFDM) facilitates reliable digital broadband transmission in the fading wireless channels, the presence of synchronization errors in the form of Carrier Frequency Offset (CFO) and Time Offset (TO) adversely affect the performance of OFDM based physical layers. The objective of this work is to improve the accuracy of the frequency and the time offset estimation in the WiMAX physical layer. A method to enhance the synchronization accuracy by fine-tuning the merit factor of the preamble sequence is suggested in this paper. Also, a new preamble with improved synchronization accuracy is proposed for the WiMAX system. The performance of the proposed preamble is evaluated in a Rayleigh fading channel and the results of simulations show that the Mean Square Error (MSE) in offset estimation is significantly reduced and it outperforms the standard WiMAX preamble.

Estimation of Array Locations, Orientations, Timing Offsets and Target Locations in Bistatic Radars

Estimation of Array Locations, Orientations, Timing Offsets and Target Locations in Bistatic Radars

Time and Frequency Synchronization for OTFS

In this letter, we propose timing offset (TO) and carrier frequency offset (CFO) estimators for orthogonal time frequency space modulation (OTFS). The proposed estimators do not require any additional training overheads as they deploy the same pilot signal that is used for channel estimation. Hence, no additional training overhead is required for synchronization, thanks to the periodic properties of the pilot signal in the delay-time domain. Our proposed TO estimator finds the start of each OTFS block by searching for a periodic sequence in delay and time dimensions. The CFO is then estimated by finding the mean of the angles of a two-dimensional correlation function at the best timing instant. As a novel aspect of these estimators, the multipath diversity of the channel is exploited to achieve a high estimation accuracy. Finally, we show the efficacy of our proposed synchronization techniques through extensive simulations.

STO Estimation for OFDM System Using CDM

In this letter, we propose a novel scheme for symbol timing offset (STO) estimation by using a convolutional neural network (CNN)-deep neural network (DNN) model (CDM) architecture for the orthogonal frequency division multiplexing (OFDM) system over different fading channel models. The proposed scheme estimates STO in the presence of carrier frequency offset (CFO) and without prior knowledge of the channel, modulation format, and transmitted OFDM signal parameters. The CDM architecture achieves better estimation accuracy gain compared to that of statistical-based and pilot-assisted CNN-based methods. Finally, the proposed CDM is validated over a radio frequency testbed, and the desired constellation diagram is obtained.

Cooperative Reflection and Synchronization Design for Distributed Multiple-RIS Communications

To reap the promised gain achieved by distributed reconfigurable intelligent surfaces (RISs)-enhanced communications in a wireless network, timing synchronization among these metasurfaces is an essential prerequisite in practice. This paper proposes a unified framework for the joint estimation of the unknown timing offsets and the RIS channel parameters, as well as the design of cooperative reflection and synchronization algorithm for the distributed multiple-RIS communication. Considering that RIS is usually a passive device with limited capability of signal processing, the individual timing offset and channel gains of each hop of the RIS links cannot be directly estimated. To make the estimation tractable, we propose to estimate the cascaded channels and timing offsets jointly by deriving a maximum likelihood estimator. Furthermore, we theoretically characterize the Cramér-Rao lower bound (CRLB) to evaluate the accuracy of this estimator. By using the proposed estimator and the derived CRLBs, an efficient resynchronization algorithm is devised jointly at the RISs and the destination to compensate the multiple timing offsets. Based on the majorization-minimization framework, the proposed algorithm admits semi-closed and closed form solutions for the RIS reflection matrices and the timing offset equalizer, respectively. Simulation results verify that our theoretical analysis well matches the numerical tests and validate the effectiveness of the proposed resynchronization algorithm.

Joint STO and DFO Estimation for SEFDM in Low-Earth-Orbit Satellite Communications

In this article, a joint symbol timing offset (STO) and Doppler frequency offset (DFO) estimation algorithm is proposed for spectrally efficient frequency division multiplexing (SEFDM) system in the downlink of low-earth-orbit (LEO) satellite communications. Considering the nonorthogonality of SEFDM, the proposed algorithm is derived by maximizing likelihood function. To reduce computation complexity of STO estimator, all unnecessary terms in likelihood function are ignored. Further, the proposed CFO estimator is simplified by replacing the inverse trigonometric function with polynomial approximation. According to relevant standards issued by the International Telecommunications Union and the 3rd Generation Partnership Project, simulation parameters are set to evaluate the estimation performance. Simulation results show that the proposed algorithm is robust to different packing factors of SEFDM, and outperforms traditional estimation methods.

Robust Frequency-Domain Timing Offset Estimation for DCO-OFDM Systems

Optical wireless communication (OWC) systems suffer inter-symbol interference (ISI) in time domain due to light emitting diode (LED)’s limited bandwidth at transmitter. As intensity modulation and direct detection (IM/DD) is used, the transmitted signals are unipolar and real-valued rather than bipolar and complex-valued as in radio frequency (RF). Thus, it is challenging to employ the RF-based timing offset estimation for OWC. Also, there is no carrier frequency offset (CFO) like in RF. It is possible to estimate timing offset in frequency domain for two reasons. First, the effect of ISI in time domain is mitigated in frequency domain with correct timing offset estimation, robust against LED’s limited bandwidth. Second, the correlation between frequency-domain signals are high, as signals are bipolar and complex-valued in frequency domain rather than unipolar and real-valued in time domain. Therefore, we propose an effective frequency-domain timing offset estimation approach for direct current biased optical-orthogonal frequency division multiplexing (DCO-OFDM) OWC systems, where a small number of pilots are applied on few DCO-OFDM subcarriers, leading to very low spectral overhead. The property of no CFO is utilized to formulate an error function, by exploring the correlation between received signals and pilots. We propose a squared error function (SEF)-based timing offset estimation approach, conducted by maximizing the ratio of two successive variances of squared errors. Simulation results show that, with a very low training overhead of 0.48%, the proposed SEF-based approach provides a bit error ratio (BER) performance close to ideal case with perfect timing offset estimation, perfect channel state information and zero-forcing (ZF) equalization.

Efficient Timing Offset Estimation Method Tailored for ACO-OFDM VLC Systems

The asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM)-based visible light communication (VLC) system has received widespread attention due to its capability to support high spectrum efficiency as well as high power efficiency. The accuracy of symbol timing offset estimation is a critical factor limiting the performance of ACO-OFDM. In order to cope with this challenge, a training symbol-aided symbol timing synchronization method tailored for ACO-OFDM is put forward. The influence of the design of training symbol structure and timing metric on the synchronization accuracy is investigated, and three timing metrics are presented to supply simple and efficient timing offset estimation by utilizing the structure of odd-even mirror-symmetric and complementary symmetric of the newly designed training symbol. In addition, the system bit error rate (BER) penalty induced by timing synchronization error is analyzed, and the approximate relationship between BER performance loss and timing estimation error probability and ideal BER performance is presented. Simulation is used to assess the performance of the three proposed timing metric methods in different channel environments, and they are compared with the two existing timing synchronization algorithms in ACO-OFDM, namely the modified Park method and the Tian method. The results show that the new synchronization method is superior to the comparison methods concerning achievable synchronization accuracy and system BER penalty.

The Process of Data Validation and Formatting for an Event-Based Vision Dataset in Agricultural Environments

Abstract In this paper, we describe our team’s data processing practice for an event-based camera dataset. In addition to the event-based camera data, the Agri-EBV dataset contains data from LIDAR, RGB, depth cameras, temperature, moisture, and atmospheric pressure sensors. We describe data transfer from a platform, automatic and manual validation of data quality, conversions to multiple formats, and structuring of the final data. Accurate time offset estimation between sensors achieved in the dataset uses IMU data generated by purposeful movements of the sensor platform. Therefore, we also outline partitioning of the data and time alignment calculation during post-processing.

An Iterative-Optimization-Based Calibration Framework for VIO With Limited Prior Conditions

Most of the visual inertial positioning accuracy is constrained by the calibration accuracy of the sensor, however, there are few navigation systems that take the time offset and extrinsic parameters into account at the same time. In this paper, an iterative-optimization-based calibration framework for VIO (visual-inertial odometry) with limited prior conditions is proposed. In particular, a three-stage calibration method is presented, which includes the time offset estimation stage, the extrinsic and intrinsic parameters calibration stage, and global temporal and IMU parameter optimization stage. In the first stage, the time offset calibration model is proposed, which estimates the time delay by iteratively optimizing the orientation residual equation. In the second stage, based on the assumption of constant angle velocity and linear velocity between two continuous keyframes, an iterative-based coarse-to-fine calibration strategy is presented to calibrate the initial extrinsic and IMU intrinsic parameters. In the third stage, a global optimization-based algorithm is introduced to obtain a more accurate time offset value and IMU intrinsic parameters. What’s more worth mentioning is that the proposed method does not require any prior parameters, which greatly improves the universality of the navigation system. To evaluate the effectiveness and accuracy of the proposed algorithm, the method is tested on both simulation and public dataset, and also compared with classical systems. Abundant experimental results illustrate that the proposed method can effectively estimate the time offset, the IMU intrinsic and extrinsic parameters.

A Novel Timing Synchronization Method for DCO-OFDM-Based VLC Systems

Being sensitive to synchronization errors, symbol timing synchronization is a key factor affecting the performance of orthogonal frequency division multiplexing (OFDM) -based visible light communication (VLC) systems. A novel timing synchronization method based on odd-even symmetry for direct current biased optical OFDM (DCO-OFDM) is investigated in this paper. The proposed method produces an excellent pulse-like timing metric, resulting in a sharper peak at the correct place, while the values of other parts are negligible. The performance of the proposed timing synchronization approach is assessed by measuring the root mean squared error (RMSE) and mean absolute error (MAE) of timing offset estimation and bit error rate (BER) performance by computer simulation. The simulation results show that this novel symbol timing synchronization approach is superior to the typical methods for DCO-OFDM, such as the Park method and Guerra method, in various channel environments.

Joint Timing and Frequency Synchronization Using Convolutional Neural Network in WLAN Systems

In wireless communication systems, the performance of the receiver is very sensitive to time and frequency offsets. In particular, orthogonal frequency division multiplexing (OFDM) systems are highly vulnerable to those offsets due to inter-carrier interference (ICI) and inter-symbol interference (ISI). To solve this problem, wireless local area network (WLAN) systems transmit a preamble for synchronization. In this paper, we propose a joint time and frequency offsets estimation technique based on convolutional neural network (CNN) for WLAN systems. In the proposed technique, the correlation between the received signal and the transmitted preamble is performed first. Then the frequency offset is coarsely compensated by several hypothesized offsets. The compensated signals are inputted to the proposed CNN and the CNN predicts the time and frequency offsets. The estimation performance is examined through computer simulation. According to the results, the proposed time offset estimator shows 3 dB to 6 dB performance gain, and the frequency offset estimator shows much lower root mean square error (RMSE) performance than the conventional technique at low SNRs

GNSS-to-GNSS time offsets: study on the broadcast of a common reference time

We present two different approaches to broadcasting information to retrieve the GNSS-to-GNSS time offsets needed by users of multi-GNSS signals. Both approaches rely on the broadcast of a single time offset of each GNSS time versus one common time scale instead of broadcasting the time offsets between each of the constellation pairs. The first common time scale is the average of the GNSS time scales, and the second time scale is the prediction of UTC already broadcast by the different systems. We show that the average GNSS time scale allows the estimation of the GNSS-to-GNSS time offset at the user level with the very low uncertainty of a few nanoseconds when the receivers at both the provider and user levels are fully calibrated. The use of broadcast UTC prediction as a common time scale has a slightly larger uncertainty, which depends on the broadcast UTC prediction quality, which could be improved in the future. This study focuses on the evaluation of two different common time scales, not considering the impact of receiver calibration, at the user and provider levels, which can nevertheless have an important impact on GNSS-to-GNSS time offset estimation.

Multi‐phase initial ranging process for OFDMA systems: improved dynamic threshold‐based multi‐user detection approach

Initial ranging (IR) is a process of performing power adjustment, timing offset estimation, and synchronisation between the base station (BS) and all users. It plays a vital role in mobile WiMAX standard, which establishes a communication link between BS and ranging subscriber stations (RSSs). Since RSS is located far away from the BS and uplink signal is corrupted by noise, the IR process becomes inferior. Thus, the authors propose an improved dynamic threshold-based IR method comprising three phases: (i) code detection phase, (ii) filtering phase, and (iii) parameter estimation phase. In the first two phases, the received signal is pre-processed to eliminate noise and unselected codes from the codeset by employing adaptive filter and weight-based code detection method. Then, the noise-free signal is considered for the final phase, which improves accuracy. The iterative expectation maximisation algorithm is involved in the estimation of channel coefficient and timing offset. All possible active paths are detected by setting a dynamic threshold value for each channel by the enhanced dynamic threshold method. For all active channels, round trip delay, and power level are estimated by considering particular channel coefficient and timing offset. Extensive simulation of proposed work shows considerable improvements in performance.

Distributed Multisensor Multitarget Tracking Algorithm with Time-Offset Registration

In multisensor systems, the signal processing delay, measurement acquisition delay, and other factors will lead to imprecisely time-stamped measurements, namely, the problem of time-offset. To deal with the measurement time offsets in distributed multisensor systems, a distributed multisensor multitarget tracking algorithm with time-offset registration is proposed. The local processors track multiple targets in the presence of false alarms and missed detections based on the joint probabilistic data association (JPDA) algorithm and the extended Kalman filter (EKF), providing the time-biased local tracks. In the global processor, in allusion to the global track accuracy degradation introduced by the time offsets of local tracks, the equivalent measurements are firstly constructed based on local tracks by using the inverse Kalman filter. The pseudo-measurement equation of time offset for constant velocity targets is derived and the pseudo-measurement calculation method is presented. Then, the pseudo-measurement based relative time-offset estimation algorithm is presented, by using the recursive least squares estimation (RLSE) and the Kalman filter (KF) to jointly estimate the state in space and time domains, respectively. Finally, a framework of distributed multisensor multitarget tracking with time-offset registration is presented, where the time-varying relative time-offset estimation and compensation, 'equivalent measurement to global track' association, and global track update are included. Simulations for multisensor multitarget tracking in the presence of false alarms and missed detections are conducted, demonstrating that the present algorithm effectively improves the accuracy of fused global tracks.

GNSS time offset monitoring based on the single difference among systems

Time offset monitoring of multiple Global Navigation Satellite Systems is important for compatibility and interoperability. Unlike conventional signal space approaches, such as single-point positioning (SPP) and precise point positioning, an approach based on the principle of single difference among systems, single-difference point positioning (SDPP), is proposed to omit the receiver clock parameter and reduce the influence of the common model errors during estimation. The proposed approach was validated on different datasets, and results shown that the estimated time offset among systems using SDPP has no significant difference with that using SPP. Moreover, SDPP retrieves the best time offset estimation when considering it as a random walk process, as it provides smooth estimation with low noise. Furthermore, considering constraints from station coordinates and tropospheric delay further improves time offset estimation. The time offset estimation over time remains within a reasonable range, exhibits some periodicity, and estimation from different stations is consistent if disregarding system biases. In addition, the estimated time offset can be used to improve the SPP accuracy.

ML-Based Forward Symbol Timing Offset Estimation for Burst Signals

In order to ensure the performance of burst signal demodulation, forward symbol timing offset estimation algorithm is usually used for symbol timing recovery. Aiming at the shortcomings of common forward symbol timing estimation algorithms, a new algorithm based on maximum likelihood estimation joint trigonometric polynomial interpolation is proposed in this article, which is suitable for the data of four samples per symbol and can resist large frequency offset. Hereafter, in order to make it more suitable for engineering practice, optimize it into an improved data-aided (DA) forward symbol timing offset estimation algorithm with multiple characteristics, e.g., moderate frequency offset capture range, insensitive to shaping coefficient, relatively low complexity, excellent estimation performance, flexible algorithm structure and less sample data required for calculation. The simulation results show that the performance of the improved algorithm in this article can approach the modified cramer-rao bound (MCRB) within the frequency offset capture range, under the conditions of low signal to noise ratio (SNR) and small shaping coefficient.

Waveform Design and Accurate Channel Estimation for Frequency-Hopping MIMO Radar-Based Communications

Frequency-hopping (FH) MIMO radar-based dual-function radar communication (FH-MIMO DFRC) enables communication symbol rate to exceed radar pulse repetition frequency, which requires accurate estimations of timing offset and channel parameters. The estimations, however, are challenging due to unknown, fast-changing hopping frequencies and the multiplicative coupling between timing offset and channel parameters. In this article, we develop accurate methods for a single-antenna communication receiver to estimate timing offset and channel for FH-MIMO DFRC. First, we design a novel FH-MIMO radar waveform, which enables a communication receiver to estimate the hopping frequency sequence (HFS) used by radar, instead of acquiring it from radar. Importantly, the novel waveform incurs no degradation to radar ranging performance. Then, via capturing distinct HFS features, we develop two estimators for timing offset and derive mean squared error lower bound of each estimator. Using the bounds, we design an HFS that renders both estimators applicable. Furthermore, we develop an accurate channel estimation method, reusing the single hop for timing offset estimation. Validated by simulations, the accurate channel estimates attained by the proposed methods enable the communication performance of DFRC to approach that achieved based on perfect timing and ideal knowledge of channel.

A New Perspective on the Initial Uplink Synchronization Problem

We explore the frequency domain properties of the signal model associated with the initial uplink synchronization (IUS) problem, and provide some new insights. We show that the adverse effects of carrier frequency offset (CFO) are confined in a small region in the frequency domain. We present a new code design approach that avoids the above mentioned region to cancel the adverse effects of CFO. In this design the codes of different users occupy mutually disjoint intervals on the frequency axis. In this way we minimize the interference between different codes, and thereby, allow considerably large number of simultaneous IUS users in the system. For the proposed codes, we design a simple energy detector. This detector relies on classical results from statistical detection theory. We also propose a simple timing offset estimation technique, which requires us to locate the maximum in a periodogram. The resulting detection-estimation algorithms are simple, non-iterative, fast and accurate. The utility of the proposed design is illustrated using numerical simulation results.

Comprehensive Time-Offset Estimation for Multisensor Target Tracking

Temporal registration of sensors is an essential preprocessing step in multisensor target tracking systems. A new approach for multisensor time-offset estimation is proposed in this article. First, the time offset pseudomeasurement equation is derived and calculated in both centralized and decentralized scenarios, where measurements and local tracks are available at the fusion center, respectively. The observability of time offset is analyzed theoretically, which shows that only relative time offsets between sensors are observable. Second, a two-sensor two-stage filtering method is developed with four different formulations corresponding to different time-offset statistical models and target dynamic models to obtain a relative time-offset estimate. A multisensor two-stage filter is also proposed to obtain a minimum-bias time-offset estimate. Furthermore, the interacting multiple model estimator is used to deal with temporal registration in the presence of target maneuvers. Finally, the posterior Cramer–Rao lower bound (PCRLB) is derived for relative time-offset estimation. Simulation results show that the proposed algorithm with two sensors yields an empirically unbiased estimate of the relative time offset, and that the root-mean-square errors (RMSEs) match the corresponding PCRLB. Simulation results for multisensor target tracking are also presented to demonstrate the validity of the proposed algorithms.