Hong-xin Zhang

Modulation recognition of communication signals based on high order cumulants and support vector machine

Abstract Using high order cumulants as signal eigenvalues, signals of different modulation formats can be recognized with support vector machine (SVM). Since high order cumulants of different modulation signals are different from each other, fourth and sixth orders of cumulants were chosen and only four eigenvalues were constructed in the recognition in this paper, thus signals of different modulation format and signals of different modulation order with the same format were recognized in low signal-to-noise ratio (SNR). It was shown that the key of recognition of modulation format is how to choose proper high order cumulants as eigenvalues. So that acceptable accuracy of recognition could be obtained in low SNR. During the recognition process, one-to-one classification of LibSVM was used to simplify the usual binary separation process. An efficiency modulation recognition method was put forward with high recognition rate and less complexity.

Implementation of compressive sensing in ECG and EEG signal processing

Abstract The purpose of this paper is to exploit compressive sensing (CS) method in dealing with electrocardiography (ECG) and electroencephalography (EEG) signals at a high compression ratio. In order to get sparse data of ECG and EEG signals before being compressed, a combined scheme was presented by using wavelet transform and iterative threshold method; then, compressive sensing is executed to make the data compressed. After doing compressive sensing, Bayesian compressive sensing (BCS) is used to reconstruct the original signals. The simulation results show that compressive sensing is an effective method to make data compressed for ECG and EEG signals with high compression ratio and good quality of reconstruction. Furthermore, it shows that the proposed scheme has good denoising effects.

Compute extremely low-frequency electromagnetic field exposure by 3-D impendance method

Abstract A 3-D impedance method has been introduced to compute the electric currents induced in a human body exposed to extremely low-frequency electromagnetic field. The 3-D impedance method has been deduced from Maxwell equations and is put into the computation and simulation effectively to the visible human body model, which has 196×114×626 cells and more than 40 types of tissues. As the result, two representative cases are investigated. One is exposure of the human body to 100 μT (1 000 mG), the limit recommended by the International Commission on Non-Ionizing Radiation Protection for the public and the other one is the exposure of human body to 0.4 μT (4 mG), the level at which a statistical link appears with a doubled risk of development of childhood leukaemia. The distribution of induced current density can be obtained and the maximum of induced current are found to be 16 mA/m2 and 0.07 mA/m2.

Research on SVM-based MRI image segmentation

Abstract Based on the gray symbiotic matrix and gray characteristic values, an extraction feature method is proposed for medical image of magnetic resonance imaging (MRI), which can reduce the dimensions of characteristic values, and improve the operation rate as well as classification accuracy. For a single image, by selecting its outline as characteristic values, support vector machine (SVM) is trained by using interval samples to realize the segmentation of other similar images. The problem of low computation efficiency due to large amount of samples is also avoided by reducing the number of samples. The result shows that, by taking the main feature of one picture as training sample, the identification of the same picture can reach 90% and the identification of other similar images can reach 80%. This method can reduce the lesion area and improve processing speed. Meanwhile, the image compress ratio can reach 1/4 when PSNR is 20.49% by utilizing compressed sensing technology on the background of the image based on this image segmentation method.

SAW chirp Fourier transform for MB-OFDM UWB receiver

Abstract In the conventional multiband orthogonal frequency division multiplexing ultra wideband (MB-OFDM UWB) receiver, the fast Fourier transform (FFT) algorithm is realized by the expensive and power-consuming digital signal processor (DSP) chips. In this article, the lower power, lower cost, and lower complexity real-time analog surface acoustic wave (SAW) chirp Fourier transform devices were used to replace the DSP part. A MB-OFDM UWB receiver based on the M-C-M SAW chirp Fourier transform was presented, and the step of signal transformation from input signals was also depicted. The simulation results show that the proposed receiver provides similar bit error performance compared to the fully digital receiver when used in the channel environments proposed by the IEEE 802.15SG3a.

Parameter estimation of chirp signals based on fractional Fourier transform

Abstract The purpose of this project is to implement the fractional Fourier transform (FrFT) on chirp signals and realize the detection and parameter estimation of different chirp signals. In the application of FrFT, pre-estimated method is proposed in this paper to improve the speed of peak searching in the parameter estimation, and suitable dimensional normalization method is selected. So that, a faster and more effective pre-estimation searching method is proposed, and the parameters such as the frequency modulation slope, center frequency, and amplitude can be estimated at the same time. From the simulation results, the estimation of parameters for multi-components chirp signals can be actualized based on FrFt, and the mixed signals can be identified successfully.

Coexistence of broadband power line communication systems

Abstract Recent progress in home networks enhances the application of broadband power line communication (BPL) since it does not require any installation of new communication lines or outlets. However, high-density distribution of BPL devices may bring down the access quality. Besides, the electromagnetic field radiating from the power line may cause interference with other radio systems. Thus, the objective of this study is to investigate the impact of cumulative interference in BPL systems, especially focused on indoor environment. A 2-D model describing the BPL transmission activity is proposed. Based on transmission characteristics of the main networks, it takes into account the coexistence effect of the BPL devices. The maximum acceptable density of BPL devices and the radiation field are finally determined.

Particle filtering based channel estimation in OFDM power line communication

Abstract Particle filtering (PF) algorithm has the powerful potential for coping with difficult non-linear and non-Gaussian problems. Aiming at non-linear, non-Gaussian and time-varying characteristics of power line channel, a time-varying channel estimation scheme combined PF algorithm with decision feedback method is proposed. In the proposed scheme, firstly the indoor power line channel is measured using the pseudo-noise (PN) correlation method, and a first-order dynamic autoregressive (AR) model is set up to describe the measured channel, then, the channel states are estimated dynamically from the received signals by exploiting the proposed scheme. Meanwhile, due to the complex noise distribution of power line channel, the performance of channel estimation based on the proposed scheme under the Middleton class A impulsive noise environment is analyzed. Comparisons are made with the channel estimation scheme respectively based on least square (LS), Kalman filtering (KF) and the proposed algorithm. Simulation indicates that PF algorithm dealing with this power line channel estimation difficult non-linear and non-Gaussian problems performance is superior to those of LS and KF respectively, so the proposed scheme achieves higher estimation accuracy. Therefore, it is confirmed that PF algorithm has its own unique advantage for power line channel estimation.

UWB multi-pulse position modulation for high data-rate wireless application

A new ultra-wide band (UWB) modulation scheme called L-ary ultra-wide band time hopping multi-pulse position modulation (UWB-TH-MPPM) is proposed for high data-rate wireless application, which can provide better communication performance. The constant weight code is introduced to construct the MPPM signal and the comparison between MPPM and single pulse position modulation (SPPM) is done in three aspects, namely, power efficiency, bandwidth efficiency, and probability of symbol error, respectively. The theoretical analysis and the numerical results show that when the constant weight code is appropriately chosen, MPPM can achieve lower probability of symbol error and higher power efficiency than SPPM at the cost of more bandwidth under the same condition. The proposed MPPM can be a good candidate in UWB system design.

Performance analysis of opportunistic spectrum access based on partially observable Markov decision process

Abstract To maximize the throughout of AD hoc system with opportunistic spectrum access (OSA) among multiple secondary users is analyzed. Two distributed learning and allocation schemes are studied by using greedy and random approach, which can maximize the cognitive system throughput or equivalently minimize the total regret in distributed learning and allocation. The simulation results show that the performance of OSA in AD hoc system are affected by package arrival rate and the number of second users. When the second users are less than six, or the package arrival rate is less than 0.06, the throughput of greedy approach is higher than that of random approach, and greedy approach is recommended to be adopted in the design of OSA in AD hoc system.