Journal of Applied Sciences

Outage Probability and Ergodic Capacity of Deep Space Communication with Relay Forwarding and Multiple Antenna Reception

CHEN Xue-qiang, WANG Cheng-hua, ZHANG Xiao-fei, CHEN Xiao-ming, ZHU Qiu-ming

2014, 32(6): 551-558. doi:10.3969/j.issn.0255-8297.2014.06.001

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Multiple antenna reception combined with relay forwarding is an effective way to overcome problems
of large link loss, path delay and frequent interruption in a deep space communication system (DSCS). Outage
probability and ergodic capacity are important performance indexes in DSCS. To the authors’ knowledge,
performance of DSCS with multiple antenna reception and relay forwarding has not been reported. This paper
analyzes outage probability and ergodic channel capacity for DSCS with multiple antenna reception and relay
forwarding. Considering the characteristics of DSCS environment, we use independent non-identical (i.n.i.)
Rayleigh distribution as a fading model for each branch channel including source-relay and relay-destination
channels. Exact SNR expressions for a single source-relay-destination branch are derived. Based on the i.n.i.
Rayleigh model, the probability density function of the received SNR in each branch channel is given. For large
distances between receiving antennas, a selection combing strategy is used at the receiving end. A closed form
expression of system outage probability and an approximate expression of system ergodic channel capacity are
derived. Simulation shows validity of the theoretical analysis.

Pareto-Optimal Power Allocation of Device-to-Device Communication with One-Way Amplify-and-Forward Relay Node

NI Yi-yang, SHAO Shi-xiang, ZHU Hong-bo

2014, 32(6): 559-565. doi:10.3969/j.issn.0255-8297.2014.06.002

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In this paper, we describe the D2D communication strategy assisted by a relay node using a
one-way amplify-and-forward (AF) protocol for the underlay mode. Based on this strategy we propose a
joint-power allocation scheme to maximize the rate of both D2D and cellular link with the constraint of peruser’s
maximum transmit power. To achieve this goal, we derive an expression for the achievable sum-rate
of each link according to the signal-to-interference-plus-noise expressions of end-to-end uplink and downlink.
According to these expressions, we set up an optimization model for jointly power allocation to maximum an
achievable sum-rate. For this model, we transform the dual-objective function into a single-objective function
and propose a low complexity joint-power allocation scheme by using the Pareto-optimal method to maximize
the achievable sum-rate. Numerical results show that a higher gain of the sum-rate of the D2D link can be
obtained by using the relay aided strategy in low and intermediate signal-to-noise regimes as compared with
that of the traditional D2D mode. It is also shown that the power optimal scheme can further be improved for
the achievable sum-rate of D2D and cellular links by using the Pareto-optimal method.

Cross-Layer Design with Adaptive Modulation and Coding Based on Golden Selection in Wireless Networking

ZHAO Jun-hui1,2, TIAN Jing-xiu3, LI Xiu-ping3

2014, 32(6): 566-570. doi:10.3969/j.issn.0255-8297.2014.06.003

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A cross-layer design is developed to reduce the packet loss rate through optimization of the network target PER. Adaptive modulation and coding (AMC) is applied on the physical layer, and a limited data buffer applied on the data link layer to change the fixed target PER of the original network. The network packet
loss rate is studied with the changing target PER beyond different network parameters including the network signal-to-noise ratio, power, bandwidth, and packet arriving rate. The changing rule is then derived. The golden selection method is chosen in search of the optimal target PER to minimize the package loss rate, or equivalently, namely maximize the network throughput.

Energy-Effective Relay Assignment Based on Cognition for Machine-to-Machine Communication

CAO Tian-wei, XIE Wei, WANG Cong, XU You-yun

2014, 32(6): 571-576. doi:10.3969/j.issn.0255-8297.2014.06.004

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In machine-to-machine (M2M) communications, terminal nodes are mostly powered by batteries
that are energy constrained. Therefore energy consumption of the nodes is a crucial issue for the life of communications.
This paper studies how the terminal nodes with cognitive ability can use cooperative transmission
among each other to reduce energy consumption. As communications of secondary users are limited to the
available authorized channel spectrum, the traditional relay assignment based on Shannon channel capacity
is not applicable. Using the concept of effective channel capacity (ECC) and taking into account the nodes’
residual energy, we propose an optimal relay assignment strategy by using a matching algorithm. Simulation
results show that the proposed assignment strategy has advantages in low energy consumption and fairness.

Laser Transmit through Sand and Dust

ZHU Yao-lin1,2, AN Ran1

2014, 32(6): 577-581. doi:10.3969/j.issn.0255-8297.2014.06.005

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By observing laser transmission in sandstorm, it is found that attention decreases with increasing
height and particle impurity. Consider the condition that moisture reaches 50% and the sulfate content is
increased in sand/dust particles. Applying the Mie theory, the relationship between the particle scale and
parameters including absorption, scattering and attenuation efficiency factors of single sand/dust particles is
obtained. Also obtained are the changes in absorption and scattering coefficients of sand/dust group with
different light wavelengths, and the relationship between the attenuation coefficient and the peak radius of the
sand/dust group. The results show that, as water and sulfate content increase, the absorption efficiency factor
increases, scattering efficiency factor decreases, and the total attenuation efficiency factor changes very little.
Optical characteristic of the sand/dust group is the same with signal particles. With changing peak radius,
the attenuation coefficient varies obviously. The attenuation coefficient decreases gradually when the height of
sand/dust aerosol increases.

Automatic Speaker Recognition for Courtroom Based on Adaptive Within-Source-Variance Control

WANG Hua-peng1,2, YANG Jun1, WU Ming1, XU Yong1

2014, 32(6): 582-587. doi:10.3969/j.issn.0255-8297.2014.06.006

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This paper proposes a method to transfer the scores generated from a speaker recognition system to
likelihood ratios (LR) for evaluating the strength of forensic voice evidence. A robust LR estimation algorithm
using adaptive within-source-variance control is developed to accurately estimate a model of the suspect. The
algorithm adaptively combines information of reference speakers and that of the suspect to model the withinsource-
variability of the suspect. Compared with a baseline recognition system, the system using the proposed
algorithm has better discrimination capability and reliability, and the magnitude of evidence strength is also
improved.

Frequency-Modulated and Phase-Modulated Orthogonal Waveform Design for MIMO Radar Based on Chaotic Map

WANG Jia-jia, XIE Ya-nan, TAN Zi-miao

2014, 32(6): 588-595. doi:10.3969/j.issn.0255-8297.2014.06.007

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Based on good correlation and randomness of chaotic sequences, and complexity of double chaotic sequences, this paper proposes a MIMO radar signal model. Inside a sub-pulse, continuous frequency modulation is used with a single Bernouli chaotic map, which can resist interference of Gaussian noise. Between sub-pulses, phase modulation is used with double chaos map, i.e., Logistic and Tent. To analyze the signal model, the signal’s expression is discretized and deduced in detail. The expressions of average ambiguity function and frequency spectrum are derived. Average fuzzy characteristics and orthogonality of the signal waveforms are analyzed in theory. Numerical simulation shows the signal model with good orthogonality and reliability In this paper.

Detecting Compression Traces in Multiple JPEG-Compressed Image

Han Hong-li1, LI Ye-zhou1, NIU Shao-zhang2, SUN Xiao-ting1

2014, 32(6): 596-604. doi:10.3969/j.issn.0255-8297.2014.06.008

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Although some tamper detection methods based on compression characteristics work well for
tampered images that experienced double JPEG compression, they often fail for multiple JPEG compression.
That is because multiple JPEG compression may significantly change the DCT coefficient statistics of the
tampered images. Aimed at low quality network pictures that may be tampered, it is shown that approximate
recovery of the image may be done with a compression-removing method. This is feasible if one can explore
the compression trace of the image that has been compressed with various quality factors. This paper presents
a method to detect compression traces of images by calculating the quantization error of DC coefficient in the
DCT domain. A compression-removing method is then used to approximately recover the image. The same
method is used to detect compression traces in the recovered image afterwards. All compression traces can be
found by repeating the process. If there are different compression traces in different parts of the image, tamper
detection is achieved.

De-noising of SAR Images Based on Wavelet-Contourlet Transform with Recursive Cycle Spinning

FANG Jing1,2, XIAO Yang1, WANG Dong1

2014, 32(6): 605-610. doi:10.3969/j.issn.0255-8297.2014.06.009

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By analyzing a speckle model of synthetic aperture radar (SAR), a de-noising method for SAR
images based on the wavelet-Contourlet transform and recursive cycle spinning is presented. Compared with
wavelet transform and Contourlet transform, wavelet-Contourlet transform can express images more sparsely
and better obtain image structure. Because the Contourlet transform lacks shift invariance, wavelet-Contourlet
transform also lacks shift invariance. Threshold processing on the coefficients may produce pseudo Gibbs
phenomena. Although a cycle spinning algorithm can reduce the pseudo Gibbs phenomena, it is not the
best. In this paper, wavelet transform is used to replace the Laplacian pyramid transform (LPT) for sub-band
decomposition. Recursive cycle spinning is used to replace the cycle spinning. Simulation results show that
the proposed algorithm is efficient, and it performs significantly better in reducing speckle noise, resulting in
higher peak signal-to-noise ratio, more image details and better visual quality.

Vectorization Based on Pixel Corner Searching

ZHANG Peng-lin1, PANG Yu1, Lü Zhi-yong2

2014, 32(6): 611-616. doi:10.3969/j.issn.0255-8297.2014.06.010

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Vectorization is an important technique in remote sensing image processing. The existing vectoriztion
algorithms are mostly insufficient on vectorization of holes. This paper proposes an algorithm based
on corner pixels. A set of pixels consisting of corners is first established, and another set (valid arc set) with
arcs connecting contour points also established for contour search. A closed contour of an object is defined by
searching valid arc sets according to certain rules. Experimental results show validity of the proposed algorithm
in solving the problem of holes.

Real-Time PET Cap Defect Inspection Based on Symmetry Match

WANG Gui-jin1, LIU Bo1, HE Bei1, ZHANG Shu-jun2, MENG Long2

2014, 32(6): 617-624. doi:10.3969/j.issn.0255-8297.2014.06.011

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On a high-speed production line, tilt of bottles, burrs on the bottleneck, and residual droplets after
cleaning affect accuracy of PET bottle inspection. To deal with the problem, a bottle detection algorithm
based on symmetry matching is proposed. Considering symmetry of the bottle image, the bottle axis can
be determined accurately by registering the images before and after horizontal flipping. Thus tilts can be
compensated. Burrs and droplets are eliminated by using correlation of pixels on both sides of the axis.
Consequently, the support rings can be detected and bottle caps can be classified precisely. Experimental
results show high accuracy, speed and robustness of the proposed algorithm as compared with the state-of-theart
techniques. For images sized 640×480, the average detection time is 27.4 ms, which meets the requirement
of high-speed production lines.

Stray Light Analysis Based on Layer Imaging

RAO Peng1,2, WANG Cheng-liang3

2014, 32(6): 625-630. doi:10.3969/j.issn.0255-8297.2014.06.012

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With changing time and external scenes and based on a dynamic imaging process, the stray light
layer images are simulated by computing the stray light with the Monte Carlo method. Compared with
traditional methods for stray light analyses, the proposed method can simulate two-dimensional stray light
distribution images, and directly compare with remote-sensing images obtained by a space optical system.
Based on the experiments on the simulation images of stray light for FY-2 meteorological satellite at midnight,
the simulation results show that the method can evaluate the mechanism, path and suppression of the stray
light effectively.

Entropy Analysis of EEG for Elderly Patients with Mild Cognitive Impairment

WEI Ling1, ZHAO Jian-qiang1, SHI Jun1, XUE Qing2,3, WANG Yu-ping2,3, LI Ying-jie1

2014, 32(6): 631-638. doi:10.3969/j.issn.0255-8297.2014.06.013

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In this study, eight elderly patients with mild cognitive impairment (MCI) and 17 normal controls
participated in a cognition task. The subjects were asked to judge whether the color of two graphics is matched
or not, and their scalp electroencephalographs (EEG) were recorded. We calculated the relative power, sample
entropy (SEn) and cumulative residual entropy (CREn) of the event-related EEG signals to explore differences
between the MCI patients and normal controls. The following results were obtained. 1) There was no
difference in alpha relative power, while the MCI patients had higher complexity at medial-frontal and medialposterior
regions than the normal controls. 2) The frontal region showed significantly higher complexity than
other regions and the center hemisphere had lower complexity than left and right hemisphere in both groups
throughout the task. 3) Complexity in anterior brain in match task was higher than that in mismatch task
in both groups. Normal controls had more complex EEG activity during the match task in the right-center
region. 4) Relative to SEn, the analysis of CREn found more specific nonlinear characteristic in the EEG of
MCI patients. All these results show the MCI patients have abnormal EEG activity in brain, and CREn is
more suitable for describing the nonlinear characteristic of EEG than SEn.

H1 Control of Complex Dynamical Networks with Communication Noise and Random Time-Delays

WEI Qing-yang, FAN Chun-xia, GU Yu

2014, 32(6): 639-644. doi:10.3969/j.issn.0255-8297.2014.06.014

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A novel H1 control strategy is proposed to stabilize complex networks coupled with communication
noise and random time delays. Time delays in the node’s information transmitted over the network can be
described with Markov chains. Based on the theories of Lyapunov stability and stochastic analysis, and using
an H1 control approach, a criterion for the controller design is derived. Numerical simulation shows that the
proposed controller is valid in stabilizing complex networks in which a chaotic Lorenz system is used as the
node dynamics, and a certain H1 index is satisfied.

Cloud Workflow Model for Collaborative Design Based on Hybrid Petri Net

JIAO He-jun1,3,4, ZHANG Jing1, LI Jun-huai1, SHI Jin-fa2, LI Jian3

2014, 32(6): 645-651. doi:10.3969/j.issn.0255-8297.2014.06.015

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For business processes, there are problems in collaborative design such as inadequate description
and poor flexibility. By analyzing features in a cloud workflow model in terms of concurrency, scalability,
collaborative, dynamic and compositability, a workflow model of three-dimensional distribution in space is
established. A Petri net with compositability, color and timing constraints is introduced into the process
modeling. A hybrid Petri net (HPN) model is designed, which can dispose the cloud workflow business
processes. Using the idea of stochastic Petri net, the process flow and efficiency are explained, performance of
the model is analyzed. Reachability of the model is verified. An optimization scheme is proposed to deal with
business conflicts and model decomposition.

Dual Decomposition in Subspace Predictive Control under Fault Condition

WANG Jian-hong1, XU Ying1, XIONG Zhao-hua1, XU Bo2

2014, 32(6): 652-660. doi:10.3969/j.issn.0255-8297.2014.06.016

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This paper studies design of controllers in subspace predictive control structure under faulty conditions.
Having derived the output predictive estimations, statistic distribution of the residual and the expression
are analyzed. To optimize the prediction controller with equalities and inequalities, dual decomposition is used
to convert the former constrained optimization into unconstrained optimization. The incremental proximal
method is applied to solve the primal-dual optimization problem. With a helicopter as an example, effectiveness
of the proposed control strategy is verified.

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