Zhao Xiao-hui

Optimal power allocation for multiuser underlay cognitive radio networks under QoS and interference temperature constraints

Power allocation is an important issue for Cognitive Radio Networks (CRNs), since it needs to consider the Quality of Service (QoS) for Secondary Users (SUs) while maintaining the interference power to Primary User (PU) below the Interference Temperature (IT) threshold. In this paper, based on Euclidean projection, we propose a distributed power control algorithm with QoS requirements to minimise the total power consumption of SUs under the time-varying channel scenario. Considering the maximum transmit power constraints and the minimum signal to interference plus noise constraints for each SU, together with the IT constraints for each PU, the power allocation problem is transformed into a convex optimization problem without auxiliary variables, and is solved by the Lagrangian dual method with less information exchange. Simulation results demonstrate that the proposed scheme is superior to the Iterative Water-Filling Algorithm (IWFA).

Fabrication, Characterization and Properties of Superparamagnetic Reduced Graphene Oxide/Fe3O4 Hollow Sphere Nanocomposites

Abstract The reduced graphene oxide wrapped Fe3O4 hollow nanospheres have been synthesized by a simple self-assembly process driven by electrostatic interaction. The structure, the chemical component and the morphology were characterized by XRD, SEM, TEM, FTIR, and Raman spectroscopy. Result show that the fabricated nanocomposites exhibit superparamagnetic property with the saturation magnetization of 70.2 A·2·kg−1 at room temperature and allow rapid separation in water solution under an external magnetic field. The high magnetism and excellent water dispersibility make the nanocomposites ideal candidates for various important applications such as magnetic resonance imaging, biosensors, communication, and microwave absorption.

Double exponential model of ultrasonic signals

The notion of representing discrete-time ultrasonic signals using double exponential model and the method of computing modelpsilas parameters using Prony method are introduced. The rise time tr and full width half maximum tfwhm of double exponential model is discussed and contrasted with the damped exponential model. It is shown that flexibility of double exponent model is superior to damped exponential model. Fitting the measured data and simulation of TOA (Time-Of-Arrived) proved that the double exponent model has better performance than the damped exponential model.

Achievement of Bluetooth adaptive packet selection strategies based on SNR estimation

Abstract It is necessary to estimate channel quality in order to put Bluetooth adaptive packet selection strategies into practice. However, the current Bluetooth channel quality estimation algorithms are either poor at timeliness or not applicable to systems which only support basic rate (BR) data packets (Gaussian frequency shift keying (GFSK) modulation scheme). It is investigated to apply the channel quality estimation algorithm based on power spectrum to Bluetooth adaptive packet selection strategies in this paper. Simulation results and analysis show that the proposed channel quality estimation algorithm based on power spectrum can achieve the accuracy less than 0.2 dB in the estimation range required by Bluetooth adaptive packet selection strategies. It has simple calculation and strong timeliness. The algorithm can also be suitable for different modulation schemes of Bluetooth data packets. It provides a good precondition for the achievement of Bluetooth adaptive packet selection strategies.

MIMO-OFDM channel estimation based on PCA

A semi-blind channel estimation based on PCA was proposed for the multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system. The scheme makes use of the pilots to estimate the channel impulse response based on least square criteria firstly. Then to improve the estimation performance, a PCA approach was applied to track the varying of the channel, which using a variable step-size RLS through a neural network. Since this method was performed in frequency domain, it was not necessary to know the length of the channel. Compared with existing approaches, the proposed method had a high precision and a good performance to track the variations of the fading channels. The simulations show the effectiveness of the new scheme.

Algorithm of Image Enhancement Based on Order Morphology Transformation

A method based Tsallis entropy and order morphology transform for gray image enhancement is proposed in this article. The order morphology transform method improves the evaluation guide of transform, and chose the percentile value and structure B value by the Maximum Tsallis entropy of the area where the coefficient q is 0.8, enhances the gray image. Experiments show that the method enhances the image contrast and suppressing noise and extracting edge. The histogram and gray value show that the image contrast is improved.

A Compressed Format Index Based on the Wavelet Tree and Its Implement

In this paper, we use the function rank and the function select in wavelet tree to implement the faction of the suffix arrays. We also introduce the Canonical Huffman code to encode the Burrows-Wheeler transform (BWT) of a text T. First of all, we use the canonical Huffman code to encode wavelet tree in order to reduce the space of the wavelet tree with Huffman code, we also implement some functions of suffix arrays. Based on this data structure, we implement the suffix automaton in a space economical way.