Design of a miniature broadband internal antenna for PD detection in GIS

According to the analysis of the relationship between the impedance and bandwidth of the dipole antenna, a novel elliptical plane internal antenna feeding by a coaxial line is presented. It consists of an elliptical monopole and a rectangular grounding piece and has the virtues of broad band, high gain and small size. The antenna can be used for ultrahigh frequency (UHF) partial discharge (PD) detection in the gas-insulated switchgear (GIS). The size is achieved by using the simulation software Ansoft HFSS and the optimum size of total antenna is 90mm×45mm. A prototype is constructed and studied, and then measured. The antenna covers a large band from 781MHz to 2.00GHz, with the VSWR less than 2.5 and a max gain of 3.55dB. Simulated and tested results are in good agreement and the radiation pattern and gain characteristics are given.     

Cooperative beamforming algorithms using the assistant information from satellite navigation positioning systems

The application of beamforming in cooperative communication systems can expand the coverage and increase the SNR of the receiver. The conventional beamforming algorithms need full or half knowledge of channel state information(CSI), and get optimal beamforming matrices by complex matrix decomposition algorithms. So, this paper proposes a cooperative beamforming algorithm called the SIA-CBF, based on satellite navigation positioning information, without the CSI. The proposed scheme, with the satellite navigation information assistance, chooses the optimal codebook vector from the fixed codebook as the beamforming matrix. Certainly, the vector should have the maximum correlation with the direction of arrival of signal. Simulation results demonstrate that when the BER is 10^-4, the performance gain is more than 1.5dB, and meanwhile, computational complexity is significantly decreased.     

Improved electromagnetism-like mechanism algorithm

Based on the principle of the electromagnetism-like mechanism(EM) algorithm, the algorithm's optimization mechanism is studied. An improved electromagnetism-like mechanism algorithm is proposed to solve the problems of the original EM algorithm, such as non-uniform initial population, low search efficiency, and pathological feature in the total force formula. The new algorithm generates the initial population with the uniform design method, improves the local search algorithm with the hybrid chaotic pattern search method and calculates the total force between particles with the modified equation. Besides, an adaptive formula of movement is designed to update the locations of those particles. Experimental results show that the improved algorithm has a better convergence result and a higher solution accuracy.     

Intelligent auxiliary function method for multimodal global optimization problems

When solving multimodal global optimization problems, many auxiliary function methods are sensitive to their parameters and of great difficulty in dealing with high dimensional problems. Aiming to overcome these two disadvantages, a new intelligent auxiliary function method is proposed in this paper. Firstly, the smoothing function is employed to eliminate the solutions worse than the best one found so far. Based on the smoothing function, a novel auxiliary function is constructed, in which there is only one easily-adjusted parameter. This auxiliary function can avoid the unwilling “Mexican hat” effect caused by improper parameter settings. Then, properties of the auxiliary function are analyzed. In order to improve the searching ability, the proposed auxiliary function and intelligent optimization techniques are assembled in the designed method, which can help the method deal with high dimensional problems. Finally, 13 different benchmarks are used to test the influence of the parameter and the performance of the searching method. Experimental results indicate the effectiveness of the proposed method.     

Novel method for frequency hopping signals blind identification in the compressed domain

A novel method to blindly identify frequency hopping signals is presented in the compressed domain. The samples obtained by compressive sampling effectively maintain the structure of and the information on the original signal, so the task of identification of the original signal could be done by directly processing the sampling values. The method is based on the difference in numerical characteristic between sampling values. According to the different characteristics of the expectation of sampling values under different hypotheses, identification is accomplished by using the deviation of the actual sampling values from the expectations under the corresponding hypothesis as the criterion. Without reconstructing the frequency hopping signal itself,hopping frequencies can be estimated through a small number of measurements by the compressive sampling algorithm. Simulation results have proved that the proposed method is adequate to the environments in which the signal-to-noise ratio is higher than -2dB. Meanwhile, compared with other traditional methods, the proposed algorithm greatly reduces the amount of data, the computational complexity, and the identification time.     

Novel anti-noise-uncertainty spectrum sensing algorithm based on power spectral density segment cancellation

Since noise uncertainty seriously degrades the spectrum sensing performance of energy detection algorithms, a novel spectrum sensing algorithm based on the power spectral density segment cancellation (PSDSC) is proposed. This spectrum sensing algorithm, which can yield real-time and robust performance, makes use of the un-correlation of different power spectrum lines and takes the ratio of some PSD (power spectral density) lines to the residual PSD lines as the detection statistics. Theoretical analysis and simulation results show that the PSDSC algorithm can overcome the noise uncertainty problem effectively and that the decision threshold does not vary with the ambient noise level of secondary users. The PSDSC algorithm could offer a high probability of detection (P_d) at a low probability of the false alarm (P_fa) for a wide range of signal to noise ratios (SNR) and could be applied to spectrum monitoring and cognitive radio systems in the complex electromagnetic environment.     

Combining the wavelet and second order total generalized variation for the image zooming algorithm

A new image zooming model combining the wavelet and second order total generalized variation is proposed. The original image is regarded as the wavelet low-frequency band for the zoomed image, and the high-frequency bands are estimated. Further processing is implemented for the zoomed image using the second order total generalized variation. The second order total generalized variation may lead to an absence of the staircase effect and keep most details, and therefore, the high quality image is reconstructed. Finally, experimental results have illustrated that our algorithm not only can achieve better zooming but also can produce a very satisfactory denoising effect.     

Analysis and improvement of an authentication protocol for the multi-server architecture

Cryptanalysis of Li et al.'s authentication protocol shows that it is vulnerable to masquerade attack, session key disclosure attack and forge smart card attack. To overcome these security flaws, an improved protocol is presented. This protocol proves secure against some possible attacks. Besides, the improved scheme maintains the features of identity anonymity, concise registration, simple operation, and so on.     

Compressive sensing with sparse domain division using probability

With the development of Compressive Sensing theory in recent years, many new algorithms have been introduced to this field. But still, these algorithms tend to judge the probability of the nonzero signal in each position of the sparse domain as the same, which is in fact not true. In this topic we discuss orthogonal coefficient distribution and divide the whole sparse domain into different parts using probability. With the method called Sparse domain Division using Probability (SDP), the reconstructed speed would increase 20～60 times without producing any negative effect on image quality at the same sampling rate.     

Study of high efficiency of evaluation of a PDP in authorization service

In authorization service, the efficiency of evaluation of a PDP(policy decision point) is a key issue that affects the efficiency of authorization service. However, the efficiencies of evaluation of many PDPs available are frequently influenced by the factors of conditions in rules. Said Marouf et al put forward a method in which the evaluation speed can be increased by adjusting the rules in policies according to user history access records. This paper analyzes the shortcomings of this method in real-time applications, and proposes that the rules order in policies can be instantaneously adjusted by user history access records and indexes as well as self-adaptation are added to a PDP so that the evaluation speed can be increased substantially. Experimental results indicate that when there are 9795 rules in a PDP, the evaluation time and the time consumption taken for a PDP applied with indexes and self-adaptation to complete an authorized operation call are shortened by 93.33％ and 76.32％ respectively, compared with those for a PDP which is not applied with indexes and self-adaptation. When the number of repeat visits from the same user is 7, the time consumption taken for a PDP applied with indexes and adaptation to complete an authorized operation call is shortened by 24.29％ compared with that for a PDP which is applied with indexes only.