Table of Content

27 July 2013, Volume 31 Issue 4

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Communication Engineering

Bandwidth Allocation for Transmission Power Minimization with Network Coding in Two-Way Transmission Aware Relay-Aided Cellular Networks

DU Guan-yao1, XIONG Ke1,2, LI Dan-dan1, ZHANG Yu1, QIU Zheng-ding1

2013, 31(4):  331-337.  doi:10.3969/j.issn.0255-8297.2013.04.001

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Reducing energy consumption and extending battery life for mobile terminals (MTs) are becoming increasingly important to mobile communications. This paper proposes a bandwidth allocation method to minimize MTs’ average transmission power with the help of network coding (NC) in relay-aided cellular
networks for two-way transmission. We first provide bandwidth allocation methods for direct transmission and relay-aided transmission respectively. An MT path selection strategy is then proposed. An optimization algorithm is presented to jointly optimize RS locations, bandwidth resources allocation, and MT path selection. Numerical results show that relays operating in the NC mode can extend MT battery life by at least 8.59% with respect to those operating in the decode-and-forward (DF) mode.

Conflict Matrix Random Sort Based Channel Allocation for Multi-channel Wireless Networks

YU Xu-tao1, BI Guang-guo2, ZHANG Zai-chen2

2013, 31(4):  338-344.  doi:10.3969/j.issn.0255-8297.2013.04.002

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 Multi-channel wireless network improves network capacity by using multiple channels. Channel allocation is a key in a multi-channel network. This paper presents a conflict matrix random sort (CMRS) based channel allocation algorithm. According to the number of available channels, the CMRS channel allocation algorithm divides a multi-channel network into several subnets based on the number of available channels. Links are sorted randomly and a conflict matrix is obtained from the contention graph of the network. To reduce conflicts in subnets, channels are allocated to each link based on conflict matrix. Analysis and simulation results show that the CMRS channel allocation algorithm effectively decreases the number of conflicts in the
network, and increases the normalized network throughput.

Householder Block Exact Inverse QR-Decomposition Recursive Least Squares Method in Adaptive Digital Predistortion System

LI Ming-yu, LIU Jin-ting, FENG Wen-jiang, JIANG Yang

2013, 31(4):  345-352.  doi:10.3969/j.issn.0255-8297.2013.04.003

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 Digital predistortion has been proposed to linearize the power amplifier (PA) for nonconstant envelope modulation schemes. In this paper, we propose an enhanced memory polynomial model for wideband digital predistortion of nonlinear power amplifiers. By including the cross-combination memory terms of
Volterra model, the proposed model is much less complex while maintains excellent linearity performance as compared to the conventional memory polynomial and generalized memory polynomial model. The adaptive parameter estimation of the predistortion system is realized using a householder block exact QR-decompositionbased recursive least squares (QRD-RLS) algorithm. Performance of the householder block exact inverse QRDRLS
algorithm is studied via computer simulations. Measurements are carried out for a highly nonlinear class-AB PA. The captured IQ baseband signal of the PA is used for behavioral model generation and predistorter performance validation. The results show that correction of an adjacent channel power ratio (ACPR) up to 25 dB is achieved at 5 MHz frequency offset for a WCDMA input having 5 MHz instantaneous bandwidth.

Performance of OFDM-CANC in a Frequency-Selective Fading Channel

WU Ai-ai1, ZHANG Zu-fan1,2, JIANG Hong-jun1

2013, 31(4):  353-360.  doi:10.3969/j.issn.0255-8297.2013.04.004

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 Physical layer network coding is a promising technique for further improving spectral efficiency and network capacity of cooperative relay systems. OFDM is an efficient way to combat selective channel fading.In view of that, an orthogonal frequency division multiplexing-cooperative analog network coding (OFDMCANC)scheme is proposed, which uses network coding to improve the system spectral efficiency, and uses OFDM to cope with channel distortion. An optimal system power allocation method based on the scheme is also presented. Theoretical analysis and simulation results show that the proposed scheme can improve frequency selective fading of the channel.

Monte Carlo-Based Network Traffic Camouflage

WANG Yu, WANG Zhen-xing, MIAO Fu, LIU Hui-sheng, ZHANG Lian-cheng

2013, 31(4):  361-367.  doi:10.3969/j.issn.0255-8297.2013.04.005

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Heavy camouflage cost and low camouflage similarity are major problems in the traffic camouflage research. Network traffic camouflage based on the Monte Carlo method is proposed to deal with the problems. To acquire multiple dynamic characteristics and establish the probability distribution, the normal traffic is analyzed. The given probability distribution is then sampled with the generated random numbers to determine the dynamic characteristic sequences and construct the camouflage traffic flow. Theoretical analysis indicates that no extra rerouting nodes are deployed and no dispersion traffic generated. The network cost is reduced, the transport performance improved, and the efficiency guaranteed. Experiments show that the method can degrade the detection accuracy and reliability. Compared to the packet padding method, camouflage similarity is well improves.

Signal and Information Processing

Extraction and Identification of Radar Emitter Individual Characteristics

CHEN Tao1, YAO Wen-yang1, LIN Jin-qiu2, HU Zhi-hua3

2013, 31(4):  368-374.  doi:10.3969/j.issn.0255-8297.2013.04.006

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 To solve the problem of radar emitter individual identification, we propose to use the wave shape entropy and energy entropy to extract characteristics from surrounding-line integral bispectrum estimate results,based on the 2D characteristic vector composed of the characteristics to identify radar emitter individuals.Then, to identify the 2D characteristic vector, we propose barycenter distance in analyzing the 2D characteristic vector in order to identify homologous radar emitter individuals, and compare it with the fuzzy C-mean clustering method. Computer simulation and experimental results verify the correctness and effectiveness of the proposed method in identifying radar emitter individuals at certain signal-to-noise ratio.

Design of PSWF Pulse Generator Based on Difference Quantitation

LIU Chuan-hui1, WANG Hong-xing1,2, ZHANG Lei1, LIU Xi-guo1

2013, 31(4):  375-380.  doi:10.3969/j.issn.0255-8297.2013.04.007

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 To get higher accuracy of prolate spheroidal wave function (PSWF) pulse generator and reduce quantization bits, quantization error in the traditional PSWF generator based on direct digital waveform synthesis (DDWS) is analyzed. The main factors that affect quantization accuracy are listed. A design method for
PSWF pulse generator based on difference quantitation is proposed. The method uses difference quantitation rather than direct quantization and modifies the DAC module. Theoretical analysis and simulation show that,as the over sampling rate (OSR) is greater than p, difference quantitation can improve the noise spectrum.When OSR is doubled, the noise spectrum is improved by 6 dB, as compared to 3 dB of direct quantitation.The difference quantitation method has higher quantitation accuracy with the same or even less number of quantitation bits. Therefore, PSWF pulse generator based on the difference quantitation is more suitable for high-precision PSWF signal generation with high sampling rate.

Direction-of-Arrival Estimation for Improving Resolution Performance of Spatial Spectrum Algorithm

SI Wei-jian1, LAN Xiao-yu1, LIU Xue2

2013, 31(4):  381-386.  doi:10.3969/j.issn.0255-8297.2013.04.008

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Resolution of the multiple signal classification (MUSIC) algorithm decreases under severe environments such as low SNR, small number of snapshots, and incidence from close angles. To deal with the problem, a modified high-resolution direction-of-arrival (DOA) estimation method is proposed. The algorithm
makes full use of information contained in the subspace. By weighting noise subspace with the corresponding revised eigenvalues, a new spatial spectrum is obtained, which is multiplied by the signal subspace projection. By searching the maximum of the spectrum function, the DOAs are obtained. Simulations and experiments confirm that the proposed method can keep high resolution of noise subspace, and improve robustness of the algorithm.

Optimization of MIMO Radar Arrays in Near Field

CHEN Gang, GU Hong, SU Wei-min, WU Hao

2013, 31(4):  387-393.  doi:10.3969/j.issn.0255-8297.2013.04.009

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This paper optimizes MIMO radar arrays in the near field using the genetic algorithm (GA). GA determines which elements are turned on in the two periodic arrays (transmitting and receiving arrays) to yield the lowest maximum relative sidelobe level. A fitness function of GA for MIMO radar near field pattern is
constructed, and a fast method based FFT is given to calculate the function. A pair crossover strategy is used to make a constant thinned ratio. Simulations are performed to compare the optimization of MIMO radar with symmetric and asymmetric arrays. Analysis shows that, by optimizing the MIMO radar with symmetric arrays and when focusing on a point in the detecting region, they can yield arrays that can maintain the performance when scanning other points in the same range and with a smaller angle.

Steganalysis Based on Image Contents

LI Tao, PING Xi-jian

2013, 31(4):  394-401.  doi:10.3969/j.issn.0255-8297.2013.04.010

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 Digital images are important covers in information hiding. It has been shown that steganalytic methods perform differently on images with different contents. Based on regionally stationary Markov characteristics of natural images, a new steganalysis method based on image segmentation is proposed. Quad-tree
segmentation based on local Variance is used to locate areas sensitive to message embedding. Features based on run length histogram are then extracted and optimized. Finally, detection of steganography is done using support vector machine. Experimental results show that the proposed steganalysis method outperforms previous methods in detection accuracy.

Computer Science and Applications

Environmental-Adaptive Localization Method Based on Virtual Reference Tags

LI Jun-huai, ZHANG Guo-mou, YU Lei, ZHANG Jing

2013, 31(4):  402-410.  doi:10.3969/j.issn.0255-8297.2013.04.011

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 In an RSSI-based RFID indoor localization system, the signal propagation model in each subregion is different from others due to heterogeneity of environmental interference distribution in the area. A region division-based localization method is proposed to divide the localization region into many triangle subregions.A multi-round voting method is used to search the sub-region where the target object is located.We then build a signal propagation model by estimating the environmental factor and path loss value of that sub-region. By introducing virtual reference tags, we construct a virtual signal strength space and find the nearest neighbor tags, and then calculate coordinates of the target with a self-correcting K nearest neighbor algorithm presented in this paper. Simulation experiments show that estimation accuracy and adaptability of the proposed method are significantly higher than that of LANDMARC and VIRE, especially in complex and low tag density environments.

Chaotic Time Series Prediction Based on Optimal Training Subset Online Fuzzy LSSVM

WEN Xiang-xi, MENG Xiang-ru, LI Ming-xun

2013, 31(4):  411-417.  doi:10.3969/j.issn.0255-8297.2013.04.012

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An optimal training subset online fuzzy least squares support vector machine (OTSOF-LSSVM) is proposed for chaotic time series prediction. Samples nearest to the prediction sample in both time and space are chosen to form the optimal training subset. An "-insensitive function is introduced to formulate the fuzzy membership. Thus a prediction model is established by fuzzy LSSVM. The subset and model are updated with the moving time window. Computational complexity is reduced by matrix partitioning. Experiment of predicting the time-variant chaotic time series Ikeda shows that the proposed method has better accuracy and high training speed as compared to offline and online LSSVM.

Control and System

Local Obstacle Avoidance for Unmanned Surface Vehicle Using a Hierarchical Strategy

TANG Ping-peng1, ZHANG Ru-bo1, SHI Chang-ting1, YANG Ge1, LIU De-li2

2013, 31(4):  418-426.  doi:10.3969/j.issn.0255-8297.2013.04.013

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This paper proposes a local obstacle avoidance algorithm for unmanned surface vehicles (USV).It is designed based on the kinetic and basic motion control characteristics of USV. The heading window and linear velocity window are obtained from the dynamic window by using a hierarchical strategy. The angular
velocity and linear velocity are obtained from the heading window and linear velocity window with the tangent method and the curve method. For stability of the vessel, a buffering model of angular velocity is designed. Simulation shows that the proposed algorithm has strong capability of obstacle avoidance and high stability.Results of on-boat experiment demonstrate that the algorithm is suitable for the basic control of actual boats,and can guide USV to realize obstacle avoidance in real environment.

Adaptive Output Feedback Control of Manipulators Based on Neural Network

JIA He-ming1, SONG Wen-long1, GUO Shao-bin2, YANG Li-xin3

2013, 31(4):  427-433.  doi:10.3969/j.issn.0255-8297.2013.04.014

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The position tracking control problem for manipulators is addressed, and an adaptive output feedback controller based on neural network is proposed. The controller does not need an exact model, and is applicable to manipulators control systems with nonlinear uncertain dynamics and environmental disturbances.The controller is composed of three parts: output feedback control based on dynamic compensator, a neural network, and an item of robust control. The adaptive learning law of neural network can be obtained based on the Lyapunov stability theory. Numerical simulations show excellent performance of position control for picking manipulators.

Rapid Optimization of Penetration Trajectory for Hypersonic Reentry Vehicle

WANG Li-ying, ZHANG You-an, ZHAO Guo-rong, HUANG Jie

2013, 31(4):  434-440.  doi:10.3969/j.issn.0255-8297.2013.04.015

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For penetration trajectory optimization of reentry vehicle with constraints of waypoints and no-fly zones, a multi-phase optimization strategy based on adaptive hp pseudospectral method is proposed. The trajectory optimization model considering waypoints, no-fly zones, heating rate, g-load and dynamic pressure
is given. The associated optimization is converted into a nonlinear programming problem by using the Radau pseudospectral method. The concept of linkage nodes is introduced to deal with constraints of waypoints and no-fly zones. Combined with adaptive distribution of nodes, the above idea is implemented with general pseudospectral optimization software. Simulation results show that the proposed method can capture any discontinuities and smoothness in states and control variables as well as the boundary of no-fly zones, and adapt to solve the optimization problem of penetration trajectory with waypoints and no-fly zones.