Yun Lin

A data authentication scheme for UAV ad hoc network communication

In this paper, we propose an efficient and energy-saving distributed network architecture based on clustering stratification to solve the information security problem of unmanned aerial vehicle ad hoc network communication. And a double-authentication watermarking strategy is designed. In order to ensure that the data collected by nodes can be sent securely to the cluster head node, we use the self-characteristic of the collected data to generate the authentication watermark and insert it into the collected data at random. The cluster head node first verifies the integrity of collected data and deletes the suspicious data. Then, the authentication information is generated by combining the chaotic mapping method, and the watermark is hidden by changing the parity of the least significant bits of the data. Experimental results show that the proposed security strategy can resist most attacks, such as selective forwarding, data replay and tampering. Meanwhile, it has low energy consumption and low latency.

Dynamic threshold-setting for RF-powered cognitive radio networks in non-Gaussian noise

Abstract The increasing demand for spectral and energy efficient communication networks has drawn an upsurge of interest in frequency (RF) energy harvesting (EH) cognitive radio networks (CRNs), and the spectrum analyzer is the brain to provide different spectral access and energy harvesting opportunities in wireless-powered cognitive radio networks (WP-CRNs). The performance of detecting the existence of primary signals will be more crucial for the EH node. However, to the best of our knowledge, no dynamic threshold-setting method to achieve target detection performance, particularly in the practical non-Gaussian noise, is reported in the literature. Traditional assumption of additive white Gaussian noise (AWGN) fails to model the behavior of certain types of noise found in practice. In this paper we give a dynamic threshold-setting method to detect the existence of primary signals for the energy harvesting node in non-Gaussian noise background. Combined with the fractional lower order statistics (FLOS), we propose a weighting factor for dynamic threshold-setting to exploit the existence of the PU to harvest RF energy, namely weighting factor based fractional lower order moment (WF-FLOM) detector. Numerical simulation results verify that the proposed method is effective for the EH node, when the signal-to-noise ratio is low or the back ground noise varies.

An intelligent method of cancer prediction based on mobile cloud computing

In recent years, mobile medical services have gradually become the common focus of the communications and healthcare industries. People can get medical information and services efficiently and conveniently anytime, anywhere. However, due to the limitations of the mobile terminal’s own computing and storage capabilities, mobile therapy is greatly challenged. Therefore, we propose a mobile medical health system based on cloud computing. Firstly, principal component analysis was used to obtain representative features. Then, a simplified feature subset was applied to support vector machine (SVM) based on Sigmoid kernel function. The data set was categorized by SVM as cancer patient and normal object experimental results show that the method is improved in accuracy, sensitivity, and specificity.

The comparison of several kinds of time-frequency analysis methods

In this paper, the author introduces three useful linear time-frequency analysis methods: short-time Fourier transform(STFT), wavelet transform(WT), S transform(ST) and generalized S transform(GST). Then, algorithm simulations are conducted using these four methods to show their advantage and disadvantage.

Automatic recognition of communication signal modulation based on neural network

In order to solve the problem of low modulation recognition rate of digital communication signals and the difficulty of selecting the appropriate decision threshold, the paper features a recognition method for communication signal modulation. The paper constructs characteristic parameters for recognizing signals in the cyclic frequency domain, and uses a 3-layer neural network as a classifier to identify the modulation mode. The experiment indicates that it can recognize 2FSK, 4FSK, 8FSK, BPSK, QPSK, MSK and 2ASK When signal to noise ratio (SNR) is higher than 0 dB, the recognition rate achieves 95%. The results suggest that recognition of communication signal modulation based on neural network is accurate and feasible.

A multi-focus image fusion algorithm in 5G communications

In this paper, we first build a mobile cloud platform that users can upload multi-focus images or download full-focus images through the 5G network. Then we design a method named Region Mosaicking on Contrast Pyramid (RMCP) for image fusion on the cloud platform. In the RMCP method, we apply the Sum-Modified-Laplacian to measure the focus of the multi-focus image, and use the density-based region growth algorithm to segment the focus region mask for each image. Finally, the mask is decomposed into a mask pyramid to monitor the mosaic region of the contrast pyramid. The experimental results show that RMCP based on 5G network outperforms other methods. In addition, RMCP is suitable for mobile devices.

Regarding Engineering Education Professional Certification as a Starting Point, Do a Good Job of Audit Assessment

With the gradual implementation and deepening of engineering education in colleges and universities. Student-centered, guided by training objectives and graduation requirements. The teaching evaluation system aiming at improving students’ learning ability and ability tends to be more accurate, comprehensive and scientific. The development of intelligent talents with student development as the core. Clear new professional development trend of “Computational Complexity of System, Technology-Driven Innovation Driven and Entrepreneurial Driven, and Promotion of Interdisciplinary Formation”. Improving the students’ ability to solve complex problems and the normal monitoring of basic state data have become the important means of teaching quality assurance.

Taking Students as the Center, Discussing Some Thoughts on the Certification of Engineering Education Major

This article from the audit evaluation and professional certification two aspects of engineering education professional certification conducted a series of studies. In accordance with the “five in one” evaluation system proposed by the state to improve professional quality, “students” “learning effectiveness” as the center to achieve the goal of personnel training, develop students’ ability to learn for life, training students’ positivist and logical thinking. It is an inevitable trend to innovate the model of school-enterprise cooperation and education, promote the combination of teaching and research, and make clear that the evaluation orientation of “taking output as the mainstay” is the construction of engineering education. Finally, deepen the development of higher education informatization through innovation.

Simulation research and implementation of optimal jamming effect on MSK signal

With the rapid development of communication technology, digital communication has become the main way of information transmission. MSK signal has the advantages of continuous phase, constant envelope and so on. It has been widely used, so it is very important to select the best jamming pattern for MSK signal. In this paper, we analyze all kinds of jamming patterns of MSK signal, and simulate the model by Matlab. Finally, the bit error rate curves of MSK signals under different jamming modes are obtained.

Small particle reconstruction method via SCA

With the continuous development of software defined radio(SDR) technology, the hunger for the reconstruction performance of the SDR system is getting higher and higher, especially in the area of effective small scale reconstruction. As we all know, software communication architecture(SCA) is a mature development framework for SDR, and the small scale reconstruction via SCA is a challenge currently. In this paper, we propose a small particle reconstruction methods based on the general method of reconstruction for SDR, which improves the reconstruction ability by the way to make the waveform component granular and some of them can be switched if needed.