Delay bound analysis and splitting strategies of concurrent transmission in heterogeneous networks

We focus our attention on how to get optimal performance of concurrent transmission in heterogeneous networks. An equivalent queuing model is used to analyze the end-to-end delay performance of perfect splitting strategy with the theoretical delay bound found. Furthermore, two splitting algorithms, Minimum Queuing Delay based splitting strategy (MQD) and Unified Queuing Management Based Splitting Strategy (UQM), are presented based on the joint resources scheduled in different RATs (Radio Access Technology). In the two-RAT scenario, the two-dimensional discrete-state continuous-time Markov process is used to analyze our schemes with close-formed solutions found. Simulation results demonstrate that our proposed flow splitting strategies utilize the system resources efficiently and outperform current strategies, getting close to the theoretical delay bound especially in the heavy load region.     

Rate-compatible network LDPC codes

A rate-compatible puncturing algorithm for network LDPC codes is proposed to achieve the minimum error probability, and decoding error probability is derived. The algorithm for finding variable nodes to be deleted based on the tanner graph of network LDPC codes is proposed, which is aimed at minimizing the decoding error probability and optimizing the puncturing pattern. Simulation results illustrate that, at BER=10^-4, the proposed rate-compatible network LDPC codes have a coding gain of about 0.4dB compared with the codes obtained via the existing punctured methods.     

Normal-distribution-test algorithm for range spread target detection

A range spread target detection algorithm based on the normal distribution test is proposed. Based on the fact that the range spread target signal generally does not follow normal distribution, the range spread target detection problem is equivalent to the normal distribution test problem. Analysis show that the normal distribution test detector has the characteristic of constant false alarm rate. The performance of the proposed detector is analyzed. Numerical experimental results based on simulation and measured high range resolution profile data show that the proposed detector outperform the energy integration detector.     

STDMA protocol based on fuzzy control and MIMO for ad hoc networks

In the traditional Space Time Division Multiple Access (STDMA) protocol, the time slot is not allocated dynamically and the idle slots potentially exist. To address the issue, based on fuzzy logic control and Multiple Input Multiple Output (MIMO) technology, a novel STDMA protocol (MIMO-STDMA) is proposed. In MIMO-STDMA, the number of slots and the frame length allocated to a mobile node are determined dynamically through the judgment and calculation based on regulation of the fuzzy controller. Utilizing the reservation and stream control gain of MIMO, in the allocated slots, a node employs full antennas to transmit data. On the contrary, in the unallocated slots the node reserves the transmission by 4-way handshaking with the carrier sense. Finally, simulations are conducted to evaluate the performance of the proposed protocol. The results show that the MIMO-STDMA outperforms the STDMA in terms of throughput and slot utilization.     

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.     

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.