Shouyin Liu

Bio: Shouyin Liu is an academic researcher from Central China Normal University. The author has contributed to research in topics: Orthogonal frequency-division multiplexing & Fading. The author has an hindex of 9, co-authored 43 publications receiving 288 citations. Previous affiliations of Shouyin Liu include Hanyang University.

A study of joint tracking algorithms of carrier frequency offset and sampling clock offset for OFDM-based WLANs

Abstract: We present three joint tracking algorithms of carrier frequency and sampling clock offsets for OFDM-based WLAN systems, such as IEEE 802.11a standard. In such systems, one symbol usually contains a few pilots so that the estimation accuracy and robustness of conventional methods do not satisfy the system requirement. In this paper, three joint tracking algorithms for accurate frequency and sampling estimation are presented. The first method is performed by a one-dimensional least square estimation and averaging over L symbols. The second algorithm compares the phase difference of the current symbol with the subsequent D-th symbol and gives better performance, especially when the SNR or synchronization offset is smaller. The third method uses two-dimensional linear least square estimation within the frequency and time domains. Simulations using these algorithms have been performed with 16-QAM modulation schemes. Simulation results show that the three algorithms can improve the estimation accuracy and robustness.

The MMSE Channel Estimation Based on DFT for OFDM System

Abstract: The minimum mean-square error (MMSE) channel estimation has well performance but higher complexity than least-square (LS) channel estimation, specially it requires the channel statistical properties including the channel autocorrelation matrix and the noise variance. However, it is difficult to obtain the channel statistical properties in practice. In this paper, through the DFT based estimator, in time domain, the noise variance can be estimated, and the channel autocorrelation matrix is also obtained by using the noise suppressed channel impulse response. Then the MMSE channel estimation for OFDM system is realized. Simulation results demonstrate that the performance is better than the DFT based estimator and closed to the ideal MMSE estimator.

Improved Localization Algorithms Based on Reference Selection of Linear Least Squares in LOS and NLOS Environments

Abstract: Linear Least Squares (LLS) estimation is a low complexity but sub-optimum method for estimating the location of a mobile terminal (MT) from some measured distances. It requires selecting one of the known fixed terminals (FTs) as a reference FT for obtaining a linear set of expressions. In this paper, the choosing of the reference FT is investigated. By analyzing the objective function of LLS algorithm, a new method for selecting the reference FT is proposed, which selects the reference FT based on the minimum residual (denoted as MR-RS) rather than the smallest measured distance and improves the localization accuracy significantly in Line of sight (LOS) environment. In Non-line of sight (NLOS) environment, we combine MR-RS algorithm with two other existing algorithms (residual weighting algorithm and three-stage algorithm) to form new algorithms, which also improve the localization accuracy comparing with the two algorithms. Moreover, the time complexity of the proposed algorithms is analyzed. Simulation results show that the proposed methods are always better than the existing methods for arbitrary geometry position of the MT and the LOS/NLOS conditions.

Weighted Linear Least Square Localization Algorithms for Received Signal Strength

Abstract: Localization based on the received signal strength (RSS) is by far the cheapest and simplest option. By constructing the appropriate path-loss model, the RSS information can be converted to the distance estimates which can determine the position of the target node with Linear Least Square (LLS) algorithm. In this paper, the LLS algorithm can be directly applied by subtracting a reference node equation from the remaining ones rather than defining a new variable, which selects the reference node with the maximal RSS among all the RSS measurements. Furthermore, based on the latest research results about the estimates of the squared distance, we investigate the unbiased and linear minimum mean square error (MMSE) estimates of the squared distance, and the covariance matrixes about the two estimates with the proposed LLS algorithm are derived, respectively. Then the weighted LLS localization algorithms are presented by utilizing the covariance matrixes. Simulation results demonstrate that the localization accuracy of the linear MMSE estimate with the proposed LLS algorithm is superior to the unbiased estimate. Moreover, the proposed weighted LLS algorithms outperform the traditional LLS localization algorithms in terms of localization accuracy.

Exact BER Expression for Alamouti Scheme with Joint Transmit and Receive Antenna Selection

Abstract: In this paper, we propose a simple joint transmit and receive antenna selection algorithm based on maximizing the instantaneous signal to noise ratio (SNR) over uncorrelated Rayleigh fading channels in multi-input multi-output (MIMO) systems. For a special case that two transmit antennas and one receive antenna are selected, while Alamouti scheme is employed, the exact bit error rate (BER) expression for binary phase shift keying (BPSK) is derived. The analytical results are exactly verified by the simulations.

Channel estimation for wireless ofdm systems

Abstract: Techniques are described for efficiently estimating and compensating for the effects of a communication channel in a multi-carrier wireless communication system. The techniques exploit the fact that the transmitted symbols are drawn from a finite-alphabet to efficiently estimate the propagation channel for multi-carrier communication systems, such systems using OFDM modulation. A transmitter transmits data through a communication channel according to the modulation format. A receiver includes a demodulator to demodulate the data and an estimator to estimate the channel based on the demodulated data. The channel estimator applies a power-law operation to the demodulated data to identify the channel. The techniques can be used in both blind and semi-blind modes of channel estimation.

Survey of NLOS identification and error mitigation problems in UWB-based positioning algorithms for dense environments

Abstract: In this survey, the currently available ultra-wideband-based non-line-of-sight (NLOS) identification and error mitigation methods are presented. They are classified into several categories and their comparison is presented in two tables: one each for NLOS identification and error mitigation. NLOS identification methods are classified based on range estimates, channel statistics, and the actual maps of the building and environment. NLOS error mitigation methods are categorized based on direct path and statistics-based detection.

Security Aspects in Software Defined Radio and Cognitive Radio Networks: A Survey and A Way Ahead

Abstract: Software Defined Radio (SDR) and Cognitive Radio (CR) are promising technologies, which can be used to alleviate the spectrum shortage problem or the barriers to communication interoperability in various application domains. The successful deployment of SDR and CR technologies will depend on the design and implementation of essential security mechanisms to ensure the robustness of networks and terminals against security attacks. SDR and CR may introduce entirely new classes of security threats and challenges including download of malicious software, licensed user emulation and selfish misbehaviors. An attacker could disrupt the basic functions of a CR network, cause harmful interference to licensed users or deny communication to other CR nodes. The research activity in this area has started only recently and many challenges are still to be resolved. This paper presents a survey of security aspects in SDR and CR. We identify the requirements for the deployment of SDR and CR, the main security threats and challenges and the related protection techniques. This paper provides an overview of the SDR and CR certification process and how it is related to the security aspects. Finally, this paper summarizes the most critical challenges in the context of the future evolution of SDR/CR technologies.

GPS Localization Accuracy Classification: A Context-Based Approach

Abstract: Global Positioning System (GPS) localization has been attracting attention recently in various areas, including intelligent transportation systems (ITSs), navigation systems, road tolling, smart parking, and collision avoidance. Although, various approaches for improving localization accuracy have been reported in the literature, there is still a need for more efficient and more effective measures that can ascribe some level of accuracy to the localization process. These measures will enable localization systems to manage the localization process and resources to achieve the highest accuracy possible and to mitigate the impact of inadequate accuracy on the target application. The localization accuracy of any GPS system depends heavily on both the technique it uses to compute locations and the measurement conditions in its surroundings. However, while localization techniques have recently started to demonstrate significant improvement in localization performance, they continue to be severely impacted by the measurement conditions in their environment. Indeed, the impact of the measurement conditions on the localization accuracy in itself is an ill-conditioned problem due to the incongruent nature of the measurement process. This paper proposes a scheme to address localization accuracy estimation. This scheme involves two steps, namely, measurement condition disambiguation and enhanced location accuracy classification. Real-life comparative experiments are presented to demonstrate the efficacy of the proposed scheme in classifying GPS localization accuracy under various measurement conditions.

Joint weighted least-squares estimation of carrier-frequency offset and timing offset for OFDM systems over multipath fading channels

Abstract: This work presents an algorithm for joint estimation of carrier-frequency offset and timing offset for orthogonal frequency-division multiplexing (OFDM) systems in the tracking mode. The proposed weighted least-squares algorithm derives its estimates based on phase differences in the received pilot subcarrier signals between two symbols. Moreover, the optimal weights in two different channel conditions are derived. Both analysis and simulation show that the weighted least-squares algorithm can effectively and accurately estimate the carrier-frequency offset as well as the timing offset of OFDM signals in multipath fading channels.