Zhijiang Xu

An adaptive signal-to-noise ratio estimator in mobile communication channels

Representing the reception condition directly, signal-to-noise ratio (SNR) is an important parameter in mobile propagation channels, and therefore is widely used in system performance evaluations and adaptive applications. Hence, this paper puts forward a frequency domain SNR estimator in mobile communications, where we exploit the signal model with the band-limited fading channel and the additive white Gaussian noise. With the above model, the noise power spectrum density can be estimated from the periodogram of channel-plus-noise signals, subsequently leading to our SNR estimation. Moreover, in order to degrade the intrinsic spectrum leakage of fast Fourier transform in periodogram calculation, the leakage expression is derived analytically and then an adaptive process is proposed to make a tradeoff between leakage reduction and noise smoothing. We verify our algorithm by simulations and observe high accuracy in a wide range of velocities and SNRs. Additionally, unlike the conventional work, the proposed estimator is not strictly based on the assumption of specific Doppler spectral shapes except for the requirement of the band-limited channel, hence it is robust to general mobile channels.

A novel ad hoc routing protocol research based on mobility prediction algorithm

Mobile ad hoc network (MANET) is a network that every node processes packet routing without infrastructure. The fast equipping and mobile self-organization characters push MANET the hot point in wireless communication research. Based on ad hoc on-demand vector (AODV) routing protocol, this paper provides a novel MAODV routing protocol research based on mobility prediction algorithm. The MAODV controls route discovery, keeping and switch by estimating neighbor nodes distance and predicting neighbor nodes mobility to suit fast changed network topology. Simulator result demonstrates that, compared with original AODV, MAODV could reduce end-to-end delay effectively and enhance the real-time character.

A novel digital filter structure with minimum roundoff noise

In this paper, a novel structure is derived for efficient implementation of digital filters as well as minimizing the finite word length (FWL) errors. Such a structure is actually an improved version of that reported previously. The performance of this new structure and the famous normalized lattice structure are analyzed by deriving the corresponding expression for the roundoff noise gain. Design examples are presented to illustrate the behavior of the proposed structure and to compare it with some existing ones. It is shown that the proposed structure outperforms the others in terms of minimizing roundoff noise as well as implementation efficiency.

Image denoising using 2-D FIR filters designed with DEPSO

Digital images are often corrupted by additive noises during transmission. Thus, how to alleviate noise as much as possible has received concerns for decades. In this paper, we present a simple denoising method based on two dimensional (2-D) finite impulse response (FIR) filtering, where by differential evolution particle swarm optimization (DEPSO) algorithm, five two dimensional finite impulse response filters are designed to filter different kinds of pixels. Comprised by differential evolution algorithm and particle swarm optimization algorithm, differential evolution particle swarm optimization algorithm is effective and robust, which helps to yield better denoise performance. And computer simulation demonstrates that the proposed method is superior to the conventional lowpass filtering method, as well as the modern bilateral filtering and stochastic denoising method.

Doppler shift estimator with MMSE parameter optimization for very low SNR environment in wireless communications

A novel iterative Doppler shift estimator is proposed in very low signal-noise-ratio (SNR) environments in single carrier mobile systems. The proposed method exploits the logarithm envelope (LE) of channel estimates, and iteratively finds the minimum mean square error (MMSE) estimation of Doppler shift. Extensive simulations conducted under a wide range of noise corruption clearly show that the proposed estimator substantially outperforms several existing estimators in terms of accuracy.

A New Method for SNR and Doppler Shift Estimation in Wireless Propagations

Recently, thanks to the development of wireless communications, radio propagation plays an important role in the research of electromagnetic wave. Furthermore, signal-to-noise ratio (SNR) and Doppler shift of radio propagations receive many attentions due to their comprehensive use in adaptive reception. Hence with the help of double sampling rate (DSR) technique, this paper presents a new estimator to estimate the above two parameters together. We verify our algorithm by computer simulation, and the results have shown a good performance in a wide range of velocities and SNRs.

A Dynamic Clustering-Based Algorithm for Wireless Sensor Networks

Wireless sensor networks (WSN) have recently emerged as a hot research topic. One of the most important concerns for WSN is energy. To obtain long lifetime, one potential method is to use clustering algorithm. Moreover, WSN should meet various requirements for quality of service (QoS). Accordingly, this paper presents an energy-aware QoS routing algorithm for WSN, which can also run efficiently with best-effort traffic. Furthermore, our work differs from existing algorithms in two ways: (1) improve the first order energy consumption model with dynamic clustering; (2) use clustering to build the multi-objectives programming model to support QoS. Simulations and comparisons with some typical route algorithms show that our algorithm is robust and effective.

Frequency sampling design of 2-D FIR filters based on DEPSO

Frequency sampling is a classical method for 2-D FIR filters design, which can be subdivided into the uniform and non-uniform approaches. However, previous work mainly focused on reducing the algorithm complexity or seeking the alternative implementation approaches rather than optimizing the samples. In this paper, a method to refine the conventional frequency sampling method is proposed, where samples equally distributed on the Cartesian grid are adjusted by utilizing DEPSO algorithm so as to achieve the nearly optimum minimax design. Simulation results demonstrated that this new method outperforms the conventional methods on minimax sense. And the generated filters can give better image denoising performance than the median filter.

Covert digital communication systems based on joint normal distribution

The correlation coefficient of two consecutive Gaussian sequences is modulated by a binary message bit to achieve a secure communication system. The receiver of the proposed random communication system demodulates the received signal by estimating the correlation coefficient of the transmitted two consecutive sequences. Theoretical bit error rate (BER) expressions in frequency-flat/-selective fading channels with/without Doppler shift are derived. Simulation results show that the proposed system can achieve reasonably low BERs in an additive white Gaussian noise channel as well as a Rayleigh fading channel. More importantly, the proposed system shows good performance in resisting eavesdropping, since the transmitted sequence appears to be a Gaussian noise which is almost always inevitable in the process of wireless communications.

Structure and performance analysis of an S α S-based digital modulation system.

In this study, the parameter of a symmetric α-stable (SαS) noise sequence is modulated by the binary message sequence to achieve a secure communication system. The characteristic exponent ‘α’ of an SαS noise sequence carries the binary information. In order to recover the binary message sequence at the receiver, the authors propose a logarithmic moments estimator to estimate the characteristic exponent ‘α’ of the transmitted noise sequence. The optimal decision threshold and the minimum theoretical bit error ratio are derived. It is shown that the simulation results of the presented logarithmic moments estimator are consistent with the analytical results. Moreover, this estimator shows better performance and lower computational complexity than the conventional SINC estimator based on the fractional low-order moment method.