Permanent Magnet Temperature Estimation for PMSMs Using Virtual Position-offset Injection

This paper proposes a virtual position-offset injection based permanent magnet temperature estimation approach for permanent magnet synchronous machines(PMSMs). The concept of virtual position-offset injection is mathematically transforming the machine model to a virtual frame with a position-offset. The virtual frame temperature estimation model is derived to calculate the permanent magnet temperature(PMT) directly from the measurements with computation efficiency. The estimation model involves a combined inductance term, which can simplify the establishment of saturation compensation model with less measurements. Moreover, resistance and inverter distorted terms are cancelled in the estimation model, which can improve the robustness to the winding temperature rise and inverter distortion. The proposed approach can achieve simplified computation in temperature estimation and reduced memory usage in saturation compensation. While existing model-based approaches could be affected by either the need of resistance and inverter information or complex saturation compensation. Experiments are conducted on the test machine to verify the proposed approach under various operating conditions.

Polynomial rooting based frequency offset estimation for MIMO OFDM systems

Based on the frequency domain training sequences, the polynomial-based carrier frequency offset （CFO） estimation in multiple-input multiple-output （ MIMO ） orthogonal frequency division multiplexing （ OFDM ） systems is extensively investigated. By designing the training sequences to meet certain conditions and exploiting the Hermitian and real symmetric properties of the corresponding matrices, it is found that the roots of the polynomials corresponding to the cost functions are pairwise and that both meger CFO and fractional CFO can be estimated by the direct polynomial rooting approach. By analyzing the polynomials corresponding to the cost functions and their derivatives, it is shown that they have a common polynomial factor and the former can be expressed in a quadratic form of the common polynomial factor. Analytical results further reveal that the derivative polynomial rooting approach is equivalent to the direct one in estimation at the same signal-to-noise ratio（SNR） value and that the latter is superior to the former in complexity. Simulation results agree well with analytical results.

Doppler frequency offset estimation and diversity reception scheme of high-speed railway with multiple antennas on separated carriage

The challenges of severe Doppler effects in high-speed railway are considered. By building a cooperative antenna system; an algorithm of joint channel estimation and Doppler frequency offset （DFO） estimation is proposed based on Ricean channel model. First, a maximum likelihood estimation （MLE） algorithm for DFO is designed, show- ing that the Doppler estimation can be obtained by estimating moving velocity of the train and the path loss with the exploitation of pilots that are placed inside the frame. Then a joint detection algorithm for the receiver is proposed to exploit multi-antenna diversity gains. Last, the theoretical Crammer Rao bound （CRB） for joint channel estimation and DFO estimation is derived. The steady performance of the system is confirmed by numerical simulations. In particular, when the Ricean fading channel parameter equals 5 and the velocities of train are 100 m/s and 150 m/s, the estimation variances of DFO are very close to the theoretical results obtained by using CRB. Meanwhile, the corresponding sig- nal to noise ratio loss is less than 1.5 dB when the bit error rate is 10-5 for 16QAM signals.

Efficient integer frequency offset estimation for OFDM systems

An efficient scheme of integer frequency offset estimate for orthogonal frequency division multiplexing （OFDM） systems is proposed based on a training symbol with several identicalparts. In this scheme, the received training symbol is first reshaped into several sub-symbols.It shows that the reshaping process in-troduees time diversity multiplexing.After a special fast Fourier transform （FFT） algorithm is applied to the sub-symbol,the integer frequency is estimated by finding the maximum magnitude of the resulting fre-quency domain signal.To improve the estimate performance,diversity combining methods are presented to makefull use of the multiple frequency domain sub-symbols.Compared to the traditional scheme, theproposed one has an improved estimate performance demonstrated by the computation simulation, while maintaining a very low complexity.

ESTIMATION OF CARRIER FREQUENCY OFFSETS FOR MIMO SYSTEMS WITH DISTRIBUTED TRANSMIT ANTENNAS

The problem of estimating the carrier frequency offsets in Multiple-Input Multiple-Output (MIMO) systems with distributed transmit antennas is addressed. It is supposed that the transmit antennas are distributed while the receive antennas are still centralized, and the general case where both the time delays and the frequency offsets are possibly different for each transmit antenna is considered. The channel is supposed to be frequency flat, and the macroscopic fading is also taken into consideration. A carrier frequency offset estimator based on Maximum Likelihood (ML) is proposed, which can separately estimate the frequency offset for each transmit antenna and exploit the spatial diversity. The Cramer-Rao Bound (CRB) for synchronous MIMO (i.e., the time delays for each transmit antenna are all equal) is also derived. Simulation results are given to illustrate the per- formance of the estimator and compare it with the CRB. It is shown that the estimator can provide satisfactory frequency offset estimates and its performance is close to the CRB for the Signal-to-Noise Ratio (SNR) below 20dB.

Fractional Frequency Offset Estimation for OFDM Systems in Non-Cooperative Communication

The traditional fractional frequency offset(FFO) estimation schemes for orthogonal frequency division multiplexing(OFDM) in non-cooperative communication have the problems of susceptible performance with the frequency offset values and the number of OFDM symbols,a novel fractional frequency offset blind estimation scheme based on EKF for OFDM systems is conceived.The nonlinear function of the frequency offset is calculated by employing the correlation.And then the frequency offset is estimated by means of the iterative algorithm of EKF.The finally fractional frequency offset is estimated by adopting repeated the above process.Simulation results demonstrate that the proposed scheme is robust to the frequency offset values without any requirements of a prior knowledge.

Deep learning based Doppler frequency offset estimation for 5G-NR downlink in HSR scenario

In the fifth-generation new radio(5G-NR) high-speed railway(HSR) downlink,a deep learning(DL) based Doppler frequency offset(DFO) estimation scheme is proposed by using the back propagation neural network(BPNN).The proposed method mainly includes pre-training,training,and estimation phases,where the pre-training and training belong to the off-line stage,and the estimation is the online stage.To reduce the performance loss caused by the random initialization,the pre-training method is employed to acquire a desirable initialization,which is used as the initial parameters of the training phase.Moreover,the initial DFO estimation is used as input along with the received pilots to further improve the estimation accuracy.Different from the training phase,the initial DFO estimation in pre-training phase is obtained by the data and pilot symbols.Simulation results show that the mean squared error(MSE) performance of the proposed method is better than those of the available algorithms,and it has acceptable computational complexity.

Data-Aided Frequency Offset Estimation with Narrowband Interference

An algorithm for carrier frequency offset estimation with narrowband interference in burstmode transmissions is proposed.The algorithm is data-aided and has a feedforward structure that can be easily implemented digitally.The principle of the algorithm is based on a properly designed training sequence and an interpolation technique.Simulation results indicate that the estimation range is about ±20% of the symbol rate.The performance is satisfactory for a signal-to-noise ratio（SNR）as low as -13 dB and the mean square error（MSE）is approximately irrelevant to signal-to-interference ratio（SIR）values over -20 dB.

Carrier Frequency Offset Estimation for FM and Symbiotic FM Radio Data System Hybrid Signal

The symbiotic FM radio data system(SRDS)is a radio data system that a specially designed OFDM signal co-lives with FM signal,which enables a significantly higher data rate than existing radio data systems.The cyclic prefix of the OFDM symbol has the same length as the OFDM body,which enables the analytic separation of the co-channel OFDM and FM signal at receiver side,utilizing the fact that the OFDM body and prefix is equal.In this work,we show that the OFDM body and prefix cannot be viewed as equal when there is sufficient carrier frequency offset(CFO).Thus,we propose a two-step CFO estimation algorithm for FM and SRDS hybrid signal.The first step estimates the coarse CFO by exploring the characteristics of the FM signal.Once the coarse CFO is removed,the residual CFO is small enough for FM and OFDM separation.The second step fine estimates CFO from the OFDM-only signal using its repeated PN structure after the separation.Detailed mathematical equations are formulated and simulation results are given.The results show that the proposed algorithm works fine with the simulation setup and has a final residual CFO less than 3.9Hz.

Blind estimation of phase offset in OFDM subcarrier for coherent demodulation

An adaptive algorithm named low complexity phase off- set estimation （LC-POE） is proposed for orthogonal frequency division multiplexing （OFDM） signals. Depending on the requirement, the estimation procedure is divided into several scales to accelerate the adaptive convergence speed and ensure the estimation accuracy. The true phase offset is estimated through shrinking the detection range and raising the resolution scale step by step. Both the convergence performance and complexity are discussed in the paper. Simulation results show the effectiveness of the proposed algorithm. The LC-POE algorithm is promising in the application of OFDM systems.

Particle filter for joint frequency offset and channel estimation in MIMO-OFDM systems

A particle filter is proposed to perform joint estimation of the carrier frequency offset （CFO） and the channel in multiple-input multiple-output orthogonal frequency division multiplexing （MIMO-OFDM） wireless communication systems. It marginalizes out the channel parameters from the sampling space in sequential importance sampling （SIS）, and propagates them with the Kalman filter. Then the importance weights of the CFO particles are evaluated according to the imaginary part of the error between measurement and estimation. The varieties of particles are maintained by sequential importance resampling （SIR）. Simulation results demonstrate this algorithm can estimate the CFO and the channel parameters with high accuracy. At the same time, some robustness is kept when the channel model has small variations.

An iterative interference cancellation based frequency offset estimation method for OFDMA uplink systems

In this paper, Moose scheme is used for frequency offset estimation in OFDMA uplink svstems due to that the signals from different users can be easily distinguished in frequency domain. However, differential multiple access interference （MAI） will deteriorate the frequency offset estimation performances, especially in interleaved OFDMA system. Analysis and simulation results manifest that frequency offset estimation by Moose scheme in block OFDMA system is more robust than that in interleaved OFDMA systern. And an iterative interference cancellation method has been proposed to suppress the differential MAI interference for interleaved OFDMA system, in which Moose scheme is the special case of the number of iteration is equal to one. Simulation results demonstrate that the proposed method can improve the performance with the increase of the number of iterations. In consideration of the performance and complexity, the proposed method with two iterations is selected. And the full comparison results of the proposed iterative method with two iterations and that with one iteration （conventional Moose scheme） are given in the paper, which sufficiently demonstrate that the performance gain can be obtained by the interference cancellation operation in interleaved OFDMA system.

A FREQUENCY OFFSET ESTIMATION ALGORITHM FOR OFDM SYSTEMS

A new fine carrier frequency offset estimation algorithm in Orthogonal Frequency Division Multiplexing (OFDM) system is proposed. The correlation item is the training sequence instead of the received signal in the new algorithm. Simulation results show that the performance of the new algo- rithm is 4dB-9dB better than that of Schmidl's algorithm. Coarse frequency offset estimation is also discussed in this paper, which is the improvement of Zhang's method. The estimation range using the improvement method is twice as that using the Zhang's method. Based on the hardware of the receiver and the improved algorithm, a method using Fast Fourier Transform (FFT) is proposed to implement the coarse frequency estimation. The chip area of OFDM system can be reduced by using the proposed method.

JOINT ESTIMATION OF CARRIER FREQUENCY OFFSET AND POWER DELAY PROFILE FOR MIMO-OFDM SYSTEMS

This paper develops a Cyclic Prefix(CP)based joint Maximum-Likelihood(ML)estima-tion algorithm of Carrier Frequency Offset(CFO)and Power Delay Profile(PDP)for Multi-InputMulti-Output Orthogonal Frequency Division Multiplexing(MIMO-OFDM)systems.However,theexact solution of the joint ML estimation is very complex since it needs a search over amulti-dimensional domain.Thus a simplified method is proposed to estimate the CFO and the PDPiteratively via the alternating-projection method which could induce the multidimensional searchproblem to a sequence of simple one-dimensional searches.Simulations show that the proposed algo-rithm is more accurate and robust than the existing algorithms.

Q-factor estimation in CMP gather and the continuous spectral ratio slope method

The attenuation factor or quality factor(Q-factor or Q) has been used to measure the energy attenuation of seismic waves propagating in underground media. Many methods are used to estimate the Q-factor. We propose a method to calculate the Q-factor based on the prestack Q-factor inversion and the generalized S-transform. The proposed method specifies a standard primary wavelet and calculates the cumulative Q-factors; then, it finds the interlaminar Q-factors using the relation between Q and offset(QVO) and the Dix formula. The proposed method is alternative to methods that calculate interlaminar Q-factors after horizon picking. Because the frequency spectrum of each horizon can be extracted continuously on a 2D time–frequency spectrum, the method is called the continuous spectral ratio slope(CSRS) method. Compared with the other Q-inversion methods, the method offers nearly effortless computations and stability, and has mathematical and physical significance. We use numerical modeling to verify the feasibility of the method and apply it to real data from an oilfield in Ahdeb, Iraq. The results suggest that the resolution and spatial stability of the Q-profile are optimal and contain abundant interlaminar information that is extremely helpful in making lithology and fluid predictions.

Evaluation of Preamble Based Channel Estimation for MIMO-FBMC Systems

Filter-bank multicarrier （FBMC） with offset quadrature amplitude modulation （OQAM） is a candidate waveform for future wireless communications due to its advantages over orthogonal frequency division multiplexing （OFDM） systems. However, because of or-thogonality in real field and the presence of imaginary intrinsic interference, channel estimation in FBMC is not as straightforward as OFDM systems especially in multiple antenna scenarios. In this paper, we propose a channel estimation method which employs intrinsic interference cancellation at the transmitter side. The simulation results show that this method has less pilot overhead, less peak to average power ratio （PAPR）, better bit error rate （BER）, and better mean square error （MSE） performance compared to the well-known intrinsic approximation methods （IAM）.

Joint synchronization estimation based on genetic algorithm for OFDM/OQAM systems

This paper investigates the problem of synchronization for offset quadrature amplitude modulation based orthogonal frequency division multiplexing(OFDM/OQAM) systems based on the genetic algorithm. In order to increase the spectrum efficiency,an improved preamble structure without guard symbols is derived at first. On this basis, instead of deriving the log likelihood function of power spectral density, joint estimation of the symbol timing offset and carrier frequency offset based on the preamble proposed is formulated into a bivariate optimization problem. After that, an improved genetic algorithm is used to find its global optimum solution. Conclusions can be drawn from simulation results that the proposed method has advantages in the joint estimation of synchronization.

A high performance frequency offset estimator for OFDM

This paper proposes a simple method to enlarge the estimation range of conventional carrier frequency offset (CFO) estimation methods based on correlations among the identical parts of the preamble. A novel preamble is designed, which is composed of one regular OFDM training block with even numbers of identical parts and one irregular OFDM training block with odd numbers of identical parts. The initial estimates obtained over the two training blocks are next exploited to jointly estimate the CFO. By elaborately selecting the numbers of identical parts for the two training blocks, the proposed CFO estimator can estimate frequency offset over tens of the subcarrier spacing. Simulation results showed that the proposed CFO estimator satisfies the estimate range requirement for the practical OFDM systems, while achieving a very good estimate performance.

TDOA Localization Algorithm with Compensation of Clock Offset for Wireless Sensor Networks

This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadcast signals periodically,the clock offsets and skews of anchor pairs can be estimated using broadcasting signal's time-of-arrivals(TOA) at anchors.A kalman filter is adopted to improve the accuracy of clock offsets and track the clock drifts due to random fluctuations.Once the source transmits signal,the TOAs at anchors are stamped respectively and source's TDOA error due to clock offset and skew of anchor pair can be mitigated by a compensation operation.Based on a Gaussian noise model,maximum likelihood estimation(MLE) for the source position is obtained.Performance issues are addressed by evaluating the Cramer-Rao lower bound and the selection of broadcasting period.The proposed algorithm is simple and effective,which has close performance with synchronous TDOA algorithm.

Quality monitoring and biases estimation of BOC navigation signals

Many safety-critical applications that utilize the global navigation satellite system (GNSS) demand highly accurate positioning information, as well as highly integrity and reliability. Due to GNSS signals are easily distorted by the interferences or disturbances, the signal quality monitoring (SQM) is necessary to detect the presence of dangerous signal distortions. In this paper, we developed an SQM software for binary offset carrier (BOC) modulated navigation signals. Firstly, the models of BOC signal with ideal and distortion are presented respectively. Then the architecture of SQM software is proposed. Moreover, the effect of the white gaussian noise (WGN) and the front-end filter on the correlation peak of the receiver is analyzed. Finally, the biases induced by the signal distortion are evaluated. The experiments simulate the relationships between the code phase shift and the normalized correlation value in the case of the signal digital distortion and the analog distortion. The simulation results demonstrate that the proposed SQM method can effectively monitor the signal distortion and accurately estimate the correlation peak deviation caused by the distortion.