Device-free Human Activity Recognition using CSI

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

In this paper, we propose a new carrier frequency offset (CFO) estimation algorithm and a new CFO correction structure in the multi-stage synchronization strategy in time and frequency domain for OFDM. The new CFO estimation algorithm uses all pilots including continual pilots (CP) and scattered pilots (SP) to estimate the CFO in frequency domain, and it can acquire more accurate estimation results than the conventional algorithm only using CP. The new CFO correction structure is a double-loop structure, and in the double-loop synchronization structure, fractional frequency offset (FFO) is corrected using a long loop as conventional method, however, integral frequency offset (IFO) does not go back to the time domain, and it is recovered using a short loop in frequency domain, which can shorten the convergence time of frequency synchronization. The analysis and simulations show the improved performance of the proposed CFO estimation algorithm and the double-loop correction structure.

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.

A new pilot assisted (PA) carrier frequency offset (CFO) estimation algorithm for OFDM communication system is presented in this paper. This algorithm extends the principle of the discrete Fourier transform (DFT) based single carrier frequency estimation algorithm in S. Reisenfeld and E. Aboutanios (2003). The proposed algorithm comprises of two steps, first a coarse CFO estimator such as the one presented in M. Li and W. Zhang (2003) is employed to estimate the integer component of the CFO. Assuming frequency corresponding to the DFT bin number which is the integer component of the CFO has been estimated correctly, the residue CFO will be bounded between -0.5T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">U</sub> to 0.5T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">U</sub> , where T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">U</sub> is the OFDM symbol period. In this paper, a new fractional frequency estimation algorithm is presented. Unlike the fractional frequency estimation algorithm presented in M. Li and W. Zhang (2003) and P.H. Moose (1994), this estimator can estimate the frequency offset on a symbol by symbol bases which is ideal for environments where the channel characteristics change rapidly. It will be shown that under additive white Gaussian noise (AWGN), the proposed frequency estimation algorithm has a variance performance that approaches the Cramer Rao lower bound (CRLB) at high signal to noise ratio (SNR) and has an acquisition range of -0.5T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">U</sub> to 0.5T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">U</sub> Hz

We investigate a carrier frequency offset (CFO) estimation algorithm for coherent optical quaternary phase-shift keying (QPSK) receivers. The algorithm utilizes the phase difference between the samples with different time-domain separations, so that the estimation accuracy can be significantly enhanced, compared with the algorithm that only compares the phase difference between adjacent samples. In a 28-GBaud coherent QPSK system, simulation results show that when 16 time spans and 512 samples are utilized, a uniform standard deviation of less than 3 MHz can be achieved for the CFO estimation error, when the optical signal-to-noise ratio is 11.5 dB.

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 the context of 4G wireless mobile systems with direct conversion receivers, an new algorithm for carrier frequency offset (CFO) and IQ-imbalance estimation and compensation at the receiver is proposed. All processing for estimation and compensation of both CFO and IQ-imbalance is done in the time domain. Because the CFO is estimated while taking into account the presence of IQ-imbalance, a very precise estimate of the CFO can be obtained, even in the presence of large IQ-imbalance. The algorithm uses a repetitive low peak-to-average preamble sequence. At the transmitter, in order to improve the estimation result, an artificial CFO is digitally super-imposed on a part of the preamble sequence. The new algorithm yields better results than existing CFO estimation algorithms for SNRs where the IQ imbalance is dominant over the Gaussian noise. The structure of the preamble also allows an effective IQ-imbalance estimation.

This paper presents a new carrier frequency offset (CFO) estimation algorithm with low-complexity for uplink OFDMA systems. Extended Kalman Filter (EKF) is employed in time domain, while the multiple access interference (MAI) cancellation strategy is combined in every recursion. In addition, an adaptive noise variance estimator is contrived for EKF, and a robust EKF method is derived for CFO estimation with data symbols. The proposed algorithm is suitable for online estimation, and can be applied to both preamble and data symbols. Simulation results show that it has a large estimation range, while approaching the Cramer-Rao Bound (CRB) closely with quite reduced complexity.

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.

Since human bodies are good reflectors of wireless signals, human activities can be recognized by monitoring changes in WiFi signals. However, existing WiFi-based human activity recognition systems do not build models that can quantify the correlation between WiFi signal dynamics and human activities. In this paper, we propose a Channel State Information (CSI)-based human Activity Recognition and Monitoring system (CARM). CARM is based on two theoretical models. First, we propose a CSI-speed model that quantifies the relation between CSI dynamics and human movement speeds. Second, we propose a CSI-activity model that quantifies the relation between human movement speeds and human activities. Based on these two models, we implemented the CARM on commercial WiFi devices. Our experimental results show that the CARM achieves recognition accuracy of 96% and is robust to environmental changes.

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.

A novel blind carrier frequency offset (CFO) estimation algorithm was proposed which is based on estimating signal parameter via rotational invariance techniques (ESPRIT) for multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems with virtual carriers. The algorithm estimates CFO in closed-form by jointly exploiting the shift-invariant structure of received signals on multiple receive antennas. It can work effectively in different type of channel. Performance analysis of the proposed algorithm using Monte Carlo simulations and comparisons with some existing approaches are also reported.

Abstract. In this paper, an overview of carrier frequency offset (CFO) estimation algorithms for Orthogonal Frequency Division Multiplexing (OFDM) systems is presented. It is well-known that multicarrier systems suffer from their high sensitivity to mismatches of transmitter and receiver oscillator frequencies. The performance degrades since the CFO destroys the orthogonality of the subcarriers. Hence, extensive research has been done on the estimation and correction of the CFO in Single-Input Single-Output (SISO) systems. Mainly, the proposed algorithms can be categorized into data-aided and blind techniques. Several estimation techniques have been extended to the Single-Input Multiple- Output (SIMO) case where multiple receive antennas can be utilized to gain diversity. However, less attention has been paid on synchronization in the attractive Multiple-Input Multiple-Output (MIMO) case which is topic of tremendous interest in current research. The present paper concentrates on aspects of this new scenario. Starting with algorithms for SISO and SIMO, this contribution reviews briefly proposed carrier frequency synchronization techniques which could be implemented in forthcoming MIMO systems.

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 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.