2016 Vol. 25, No. 1

Display Method:
A Point-to-Point Tracking Algorithm Based on the Theory of Floating Pixels
WANG Shoujue, JIANG Yuwen, TAN Leyi
2016, 25(1): 1-5. doi: 10.1049/cje.2016.01.001
Abstract(177) PDF(1033)
Abstract:
Based on the theory of floating pixels, a point-to-point tracking algorithm based on local features is presented. A novel texture-based feature set is proposed in a form of high dimensional vector which describes each single point. Point-to-point matching is applied in a way of vector operation at multiple scales. Each match is verified by variance analysis, and unreliable matches are corrected with candidates available. Experimental results demonstrate that this algorithm maintains strong robustness when target-appearance is varying and environment is complex.
Incremental Verification of Evolving BPEL-Based Web Composite Service
JI Shunhui, LI Bixin, QIU Dong
2016, 25(1): 6-12. doi: 10.1049/cje.2016.01.002
Abstract(95) PDF(581)
Abstract:
Web composite services inevitably evolve to meet various requirements. However, most researchers only considered the verification of single versions. Simply reapplying the original verification techniques on subsequent versions of composite service as they evolve is costly, especially for large-scale services. In this paper, a new approach called Incremental verification (ICV) is proposed to incrementally verify the non-conflict property of evolved versions of Business process execution language (BPEL) based composite service. With a kind of eXtensible control flow graph (XCFG) as the formal model to describe the BPEL process, ICV compares the new version with the old one to identify the process changes which bring threats to the non-conflict property. Then it concentrates on the changed elements to perform the verification, which reduces the cost by skipping the analysis of unchanged elements. Case study shows that the proposed approach is effective and more efficient than the original verification method.
Privacy-Preserving Collaborative Filtering Based on Time-Drifting Characteristic
ZHAO Feng, XIONG Yan, LIANG Xiao, GONG Xudong, LU Qiwei
2016, 25(1): 20-25. doi: 10.1049/cje.2016.01.004
Abstract(134) PDF(734)
Abstract:
Recommendation has become increasingly important because of the information overload. Collaborative filtering (CF) technique, as the most popular recommendation method, utilizes the historical preferences of users to predict their future interests on other items. However, CF technique requires collecting users' rating information, which may lead to the disclosure of privacy. We propose a new randomized perturbation approach Time-drifting privacy-preserving collaborative filtering (TPPCF) to well balance privacy of users and accuracy of recommendation. Since users' recent ratings can better represent their interests and preferences, we incorporate a varying weight into the approach. Specifically, we assign higher weights to more recent ratings both when computing user similarity and perturbing users' ratings. To further improve the efficiency, we cluster the users into several groups to reduce computation cost. We demonstrate the effectiveness and efficiency of our method through experiments on MovieLens dataset, which shows TPPCF can achieve higher privacy while generating more accurate recommendation.
Research of Mechanism of Inductive Maglev Spherical Driving Joint
ZENG Li, CHEN Qiuyue, ZHANG Xiaohong
2016, 25(1): 26-32. doi: 10.1049/cje.2016.01.005
Abstract(88) PDF(1292)
Abstract:
The multi-degree-of-freedom inductive spherical driving joint owns high mechanical integrity and has advantages such as control and trajectory planning. Because of its limit of rotor pose, instant stepping angle and inability to spin around any axis through center of sphere, the suspension and rotation precision of spherical reluctance driving joint isn't high and the response speed can't reach the best. Based on mechanism of rotation and suspension, due to distribution of air gap magnetic induction intensity, a novel inductive maglev spherical driving joint was presented, and electromagnetic suspending force and electromagnetic torque were established. Analyze the magnetic induction intensity, electromagnetic suspending force and electromagnetic torque through finite element simulation, build a bench test of maglev spherical driving joint, and do testing research on displacement characters and suspension and rotation characters of joint rotor.
Undelayed Initialization Using Dual Channel Vision for Ego-Motion in Power Line Inspection
WU Hua, WU Yanxiong, LIU Changan, YANG Guotian, LI Zhichen
2016, 25(1): 33-39. doi: 10.1049/cje.2016.01.006
Abstract(77) PDF(512)
Abstract:
This paper presents a novel approach to the initialization of an ego-motion estimation technique for autonomous power line inspection. Dual channel vision, consisting of an infrared and optical camera, is typically adopted during inspection. The infrared camera is far more proficient at reliably detecting heated regions of the power tower which can be regarded as a prior relationship between the tower and cameras. Using the infrared camera, which is equipped parallel to the optical camera, an incomplete correspondence between the optical image and a 3D CAD model is established. Depending on the degree of correspondence, the initial pose of the CAD model in the optical image is estimated through two stages of coarse-to-fine estimation. The primary contributions of this paper include: 1) using dual vision for partial initialization; 2) incorporating two-stage algorithms to estimate an accurate pose quickly; 3) implementing an algorithm which functions correctly regardless of the motion blur or background texture. Experimental results consistently show that the initial pose can be estimated efficiently and robustly.
Travel Patterns Analysis of Urban Residents Using Automated Fare Collection System
WANG Ya, DU Bowen, RONG Qiannan, LIN Xia
2016, 25(1): 40-47. doi: 10.1049/cje.2016.01.007
Abstract(110) PDF(741)
Abstract:
As one of the essential information, passenger Origin-destination (OD) matrix is crucial for transit system planning. Automated fare collection (AFC) system is widely used in big cities all around the world, OD data not only can be collected in dynamic way but also through citywide. It is only a byproduct of AFC and have the imperfection. This paper proposes a novel method to infer trip chain information of each commuter's OD matrix based on travel pattern identify, and then the relationship between lines which have the character of the geographical proximity is used to calibrate the result of inferring. A serious of experiment results based on the real data show that the method has relatively high accuracy and can be use to practical application.
Mining and Harvesting High Quality Topical Resources from the Web
ZHAO Wei, GUAN Ziyu, CAO Zhengwen, LIU Zheng
2016, 25(1): 48-57. doi: 10.1049/cje.2016.01.008
Abstract(116) PDF(949)
Abstract:
Focused crawlers aim to effectively prioritize uncrawled URLs to harvest relevant pages while avoiding irrelevant ones. In practice, harvesting high quality topical Web resources is more important due to the explosion of Web information. Our study shows that the popular focused crawling strategy cannot achieve this goal. In this paper we develop a new focused crawler, namely On-line topical quality estimation (OTQE), which intelligently evaluates the topical quality of uncrawled pages by the observed link and content evidences and prioritize their URLs accordingly. The new crawler is scalable and requires fewer additional resources to do link-based analysis. The experimental results on crawling 3.6 million Web pages demonstrate the advantages of our proposed method over traditional focused crawlers.
Efficiently Exploring FPGA Design Space Based on Semi-Supervised Learning
YANG Liqun, YANG Haigang, LI Wei, LI Zhihua
2016, 25(1): 58-63. doi: 10.1049/cje.2016.01.009
Abstract(110) PDF(500)
Abstract:
Design space exploration (DSE) is an important step before the physical level design of Field programmable gate arrays (FPGA). An optimum architecture is usually selected from the whole space. As the architecture parameters increase, the huge time cost to explore an exponentially increasing space makes this method unrealistic. We propose a novel predictive modeling approach called ECOMT to estimate the area and delay of a circuit which is mapped onto an FPGA with certain architecture. Semi-supervised model tree is adopted to model the performance with respect to architecture parameters. Combined with nonlinear programming, the area and delay model obtained can be used to guide the DSE. Experimental results show that the model trained through ECOMT has Mean relative error (MRE) below 5% compared to VTR. Meanwhile the time used to attain the model is less than 3 minutes, which reduces the time of DSE considerably.
On-Chip Generating FPGA Test Configuration Bitstreams to Reduce Manufacturing Test Time
WANG Fei, WANG Da, YANG Haigang, XIE Xianghui, FAN Dongrui
2016, 25(1): 64-70. doi: 10.1049/cje.2016.01.010
Abstract(135) PDF(993)
Abstract:
Statistics shows that over 95% of FPGA manufacturing test time is spent on loading test configuration bitstreams. Reducing the test time that spent on loading test configuration bitstreams could significantly reduce FPGA test time. A new approach which can significantly reduce the FPGA test time is presented. Experimental results show that the proposed technique can at least reduce the configuration loading time by 96%, while getting 100% test coverage with less than 1.2% hardware overhead.
Feedforward Neural Network Models for FPGA Routing Channel Width Estimation
LIU Qiang, GAO Ming, ZHANG Tao, ZHANG Qijun
2016, 25(1): 71-76. doi: 10.1049/cje.2016.01.011
Abstract(113) PDF(869)
Abstract:
Since interconnects play the increasingly important role in delay and area of the Field-programmable gate array (FPGA) implementations, routing architecture design has become the focus of much work related to FPGA architecture development. This paper leverages feedforward neural networks to derive accurate models of the routing channel width in homogeneous FPGA architecture with two advanced intelligence learning techniques: Gradient-based learning algorithm (GLA) and Extreme learning machine (ELM). The resultant models can be used in the early stages of FPGA architecture development to facilitate fast design space exploration which is difficult to achieve in the traditional experiment-based method. The proposed models are evaluated by comparing the estimated channel widths to the real values generated from a CAD tool VTR over IWLS2005 benchmark circuits. Results show that the GLA model achieves the estimation accuracy 3.98% and the ELM model has the accuracy 3.91%, which show significant improvement over existing estimation approaches.
A Piezoresistive Sensor for Measuring Tongue Pressure
WANG Shaojie, FENG Yongjian, CHEN Yifei, ZHANG Rong, HUANG Yuanqing
2016, 25(1): 77-80. doi: 10.1049/cje.2016.01.012
Abstract(83) PDF(577)
Abstract:
Dysphagia is common after a cerebral vascular accident (or stroke), and it seriously affects the prognosis. Timely diagnosis in clinical, scientific assessment of dysphagia and correct treatment given to patients are essential. This study is aimed to develop a sensor for measuring tongue pressure during swallowing or other times, and to help doctors make a scientific assessment of dysphagia grade. It is a kind of miniaturization of piezoresistive pressure sensor with an outer diameter of 10mm and a thickness of 3mm. A calibration and data acquisition ARM system is designed, which can continuously record tongue pressure in 8 hours. The sensor has a detection range from 0 to 30kPa, and the measurement error can be controlled in 5%.
Orthogonal-Gradient Measurement Matrix Construction Algorithm
TIAN Shujuan, FAN Xiaoping, LI Zhetao, PAN Tian, CHOI Youngjune, SEKIYA Hiroo
2016, 25(1): 81-87. doi: 10.1049/cje.2016.01.013
Abstract(106) PDF(676)
Abstract:
An orthogonal-gradient measurement matrix construction algorithm is proposed for reducing the maximum and average mutual-coherence of sensing matrix. It shrinks Gram matrix based on equiangular tight frame theory. An orthogonal-gradient factor matrix is deduced. It obtains an optimized measurement matrix with the orthogonal-gradient factor matrix. The results of experiments show that the proposed algorithm effectively reduces the maximum and average mutual-coherence of sensing matrix. This leads to a better reconstruction performance for signals with different sparsities compared with Gaussian matrix, Elad's, Xu's, Vahid's and Li's methods.
Silent Speech Interface Design Methodology and Case Study
LI Wenshi
2016, 25(1): 88-92. doi: 10.1049/cje.2016.01.014
Abstract(103) PDF(731)
Abstract:
Silent speech interfaces (SSI) will face unable talking or silent cell phoning ones, or used in military scenarios. The best sensors and their positions glued information sources of imagined words will be reviewed under decoding model and Figure of merits (FOM) with new features toward multimodal Brain-brain interface (BBI) fitting consciousness communication. The data probing channels of known SSIs can be outlined into three logic categories of traditional articulators, intrinsic brain and neurovascular pathways. Eight kinds of corresponding sensors are evaluated importantly with six-axes spider-web charts. Our novel case of NIRS-based SSI showcased is with millisecond resolution. Above works may enhance the base of Brain Health Microelectronics.
Secure and Efficient Multi-proxy Signature Scheme in the Standard Model
GU Ke, JIA Weijia, DENG Yueming, NIE Xiaoyi
2016, 25(1): 93-99. doi: 10.1049/cje.2016.01.015
Abstract(99) PDF(487)
Abstract:
Multi-proxy signature is a variant of proxy signature, which allows that a delegator may delegate his signing rights to many proxy signers. Compared with proxy signature, multi-proxy signature can effectively prevent that some of proxy signers abuse signing rights. In this paper, we propose an efficient multi-proxy signature scheme in the standard model, which is based on the Waters' signature scheme. Compared with other multi-proxy signature schemes in the standard model, the proposed scheme further reduces the amount of computations and communications.
Fast Algorithm for Inverse Two-Dimensional S Transform and Its Application in Time-Frequency Filtering for SAR Image Despeckling
GAO Fei, ZHANG Ye, WANG Jun, SUN Jinping
2016, 25(1): 100-105. doi: 10.1049/cje.2016.01.016
Abstract(110) PDF(619)
Abstract:
S transform is a time-frequency representation which has been applied in various fields, yet suffers the problem of time and resource consumption. In order to overcome this problem and facilitate its application in image analysis, we introduce a fast algorithm for inverse two-dimensional S transform. A two-dimensional S transform time-frequency filter for Synthetic aperture radar (SAR) image despeckling is proposed on the basis of this fast algorithm. Synthetic and actual SAR images are both used to quantitatively evaluate its performance. The proposed algorithm is compared with several classical algorithms with better results both in speckle noise reduction and detail preservation.
Visual Computing of Complicated Target with Radar Absorbing Material
CUI Junwei, YANG Yang
2016, 25(1): 106-113. doi: 10.1049/cje.2016.01.017
Abstract(70) PDF(455)
Abstract:
Radar-absorbing materials (RAM), which effectively reduce the radar cross section of targets, are extensively used in stealth optimization of targets. Graphic electromagnetic computing (GRECO) uses graphic acceleration cards and Z-Buffer techniques to address blanking and non-visibility issues in traditional electronic magnetic algorithms. The traditional GRECO is improved to overcome its inability to precisely extract geometric information on visible surfaces and the dependence of calculation accuracy on screen resolution. An algorithm that can calculate the multiple scattering of metal dihedral-coated RAM is proposed. In addition, the element search method used in traditional dihedral calculation is improved, and calculation time is reduced by a significant margin. After the experimental results were compared, the accuracy of the algorithm is examined. The proposed algorithm, combined with the improved GRECO, can used to analyze the stealth performance of complicated targets coated single- or multi-layered RAM.
A Novel Single-Feature and Synergetic-Features Selection Method by Using ISE-Based KDE and Random Permutation
ZHANG Jingxiang, WANG Shitong
2016, 25(1): 114-120. doi: 10.1049/cje.2016.01.018
Abstract(91) PDF(400)
Abstract:
The Integrated square error (ISE), as a robust criterion for measuring the difference of densities between two datasets, have been commonly used in pattern recognition. In this paper, two different criteria for evaluating candidate feature subsets are investigated: first, a novel supervised feature selection criterion based on ISE and random permutation of a single feature is proposed, which presents a feature ranking criterion to measure the importance of each feature by computing the ISE over the feature space. Second, a synergetic feature selection criterion is developed. Experimental results on synthetic and real data set show the superior or at least comparable performance compared with existing feature selection algorithms.
Towards Practical Distributed Video Coding for Energy-Constrained Networks
CAO Yue, GAO Shaoshuai, ZHANG Can, QIU Gengfeng
2016, 25(1): 121-130. doi: 10.1049/cje.2016.01.019
Abstract(81) PDF(442)
Abstract:
Most of current distributed video codecs are developed based on the structure of Stanford scheme that employs channel coding like LDPC and Turbo codes. However, they need many times of iteration and feedback, which bring high decoding complexity and latency that make them less practical in energy-constrained networks. In this paper, a new distributed video codec based on modulo operation in the pixel domain is proposed, which only needs one feedback request and has a much lower decoding complexity. Mathematical proof of the equivalence between modulo operation and coset partition in the M-ary field is given, which means that the modulo operation in the M-ary field is a good substitute for channel codes in the distributed video coding systems. A system is built based on the proposed scheme. Simulation results show that the proposed scheme outperforms the state-of-the-art distributed video codecs with the decoding complexity as low as 1% to 10% of them.
Depth and Residual Images Based Rendering
DENG Xiangdong, CAO Xun, DAI Qionghai
2016, 25(1): 131-138. doi: 10.1049/cje.2016.01.020
Abstract(143) PDF(424)
Abstract:
This paper proposes a novel representation method which is called Depth and residual images based representation (DRIBR) for virtual image rendering in 3D video. The proposed DRIBR is composed of three parts: a single view image from one particular viewpoint, its corresponding depth map as well as a residual image. The residual image is pre-calculated from the combination of the above two components plus an image taken from the other viewpoint. The proposed DRIBR achieves low data redundancy, and resolves the occlusion problem which is one of the most annoying artifacts during the rendering of virtual image in traditional Depth image based rendering (DIBR). This paper addresses details of DRIBR and virtual image rendering algorithms based on the proposed format. We test the DRIBR on various stereo datasets and the experimental results demonstrate that our method can achieve better performance on both subjective and objective quality assessment.
A Sequential Converted Measurement Kalman Filter with Doppler Measurements in ECEF Coordinate System
WU Weihua, JIANG Jing, FENG Xun, QIN Xing
2016, 25(1): 139-145. doi: 10.1049/cje.2016.01.021
Abstract(155) PDF(706)
Abstract:
When there is the correlation between Doppler and slant range, previous literatures have presented some sequential filter algorithms. However, they are only applied to simplified fixed radar' s local coordinate system. As a result, a Sequential converted measurement Kalman filter (SCMKF) with Doppler measurements based on the Earth centered earth fixed (ECEF) coordinate system applicable to a moving airborne platform which has time varying attitude is proposed. Firstly, the correlated Doppler and range are decorrelated using the Cholesky factorization, then the converted position measurements are obtained by a series of coordinate transformation with unchanged range component and other observations, such as azimuth and elevation angles; the corresponding error covariances are derived which are used to the Converted measurement Kalman filter (CMKF). Finally the sequential filter is implemented for changed pseudo-Doppler measurements. The proposed method is validated through Monte Carlo test compared with the performance of CMKF with just converted position measurements and traditional SCMKF with Doppler which ignores the correlation between Doppler and range noises, and the conclusion is obtained that utilizing Doppler information correctly can improve tracking performance, nevertheless, the improvement gain of filter accuracy is limited, which can provide some references for engineering application.
An AP-DE Algorithm Based on Multi-step Gradient Method
DAI Dameng, MU Dejun
2016, 25(1): 146-151. doi: 10.1049/cje.2016.01.022
Abstract(176) PDF(699)
Abstract:
Aim to improve the convergence of the adaptive filtering, based on the multi-step gradient method, a new affine projection algorithm with direction error is presented. The statistical behavior of the proposed algorithm is analyzed. The deterministic recursive equations for the weight error and for the Mean-square error (MSE) are derived in the weight update direction of the adaptive filtering. The steady-state MSE is also obtained. Simulation results show that the proposed algorithm improve the adaptive filtering convergence and corroborate the theoretical analytical results.
DropConnect Regularization Method with Sparsity Constraint for Neural Networks
LIAN Zifeng, JING Xiaojun, WANG Xiaohan, HUANG Hai, TAN Youheng, CUI Yuanhao
2016, 25(1): 152-158. doi: 10.1049/cje.2016.01.023
Abstract(142) PDF(970)
Abstract:
DropConnect is a recently introduced algorithm to prevent the co-adaptation of feature detectors. Compared to Dropout, DropConnect gains state-of-the-art results on several image recognition benchmarks. Motivated by the success of DropConnect, we extended this algorithm with the ability of sparse feature selection. In DropConnect algorithm, the dropping masks of weights are generated using Bernoulli gating variables that are independent of the weights and activations. We introduce a new strategy to generate masks depending on the outputs of previous layer. Using this method, neurons which are promising to produce sparser features will be assigned a bigger possibility to keep active in the forward and backward propagations. We then evaluate such sparsity constrained DropConnect on MNIST and CIFAR datasets in comparison with ordinary DropConnect and Dropout method. The results show that our new method improves the sparsity of features significantly, while not degrading the precision.
Near-Field Source Localization Using Spherical Microphone Arrays
HUANG Qinghua, ZHANG Guangfei, LIU Kai
2016, 25(1): 159-166. doi: 10.1049/cje.2016.01.024
Abstract(153) PDF(1192)
Abstract:
A new method is proposed for joint range and bearing (azimuth and elevation) estimation of multiple near-field acoustic sources using observations collected by a spherical microphone array. First, Spherical Fourier transform (SFT) is used to construct the array signal model in the spherical harmonics domain to decouple range and bearing information. Then the relation among the spherical harmonics of three adjacent degrees is exploited to build the recursive relationship of the signal subspace. Using Eigenvalue decomposition (EVD), bearings are estimated based on the eigenvalues and simultaneously the steering matrix can be represented by the signal subspace. Finally, range is estimated using the energy ratios of the elements of the steering matrix in the spherical harmonics domain. The algorithm can avoid parameter pairing and multi-dimensional searching. It has lower computational complexity than that of the Multiple signal classification (MUSIC) method. The performance is evaluated by Monte-Carlo simulations and the estimation root mean-square errors are compared to the corresponding Cramer-Rao bounds (CRBs) and those of MUSIC range estimates, which demonstrate the validity of the proposed algorithm.
On Nonlinearity of S-Boxes and Their Related Binary Codes
LIU Jian, CHEN Lusheng
2016, 25(1): 167-173. doi: 10.1049/cje.2016.01.025
Abstract(116) PDF(419)
Abstract:
The nonlinearity of S-boxes and their related supercodes of the first order Reed-Muller code are discussed. Based on the properties of multi-output bent functions and almost bent functions, we determine the maximum size of linear supercodes of the first order Reed-Muller code which have optimal or suboptimal minimum distance, and we also give the weight distributions of these supercodes which achieve the best possible size. Furthermore, an upper bound on the minimum distance of a class of binary linear codes is presented, which yields a new upper bound on the nonlinearity of S-boxes. The new bound on nonlinearity improves a bound given by Carlet et al. in 2007.
A (t,m,n)-Group Oriented Secret Sharing Scheme
MIAO Fuyou, FAN Yuanyuan, WANG Xingfu, XIONG Yan, Moaman Badawy
2016, 25(1): 174-178. doi: 10.1049/cje.2016.01.026
Abstract(83) PDF(417)
Abstract:
Basic (t,n)-Secret sharing (SS) schemes share a secret among n shareholders by allocating each a share. The secret can be reconstructed only if at least t shares are available. An adversary without a valid share may obtain the secret when more than t shareholders participate in the secret reconstruction. To address this problem, the paper introduces the notion and gives the formal definition of (t,m,n)-Group oriented secret sharing (GOSS); and proposes a (t,m,n)-GOSS scheme based on Chinese remainder theorem. Without any share verification or user authentication, the scheme uses Randomized components (RC) to bind all participants into a tightly coupled group, and ensures that the secret can be recovered only if all m (mt) participants in the group have valid shares and release valid RCs honestly. Analysis shows that the proposed scheme can guarantee the security of the secret even though up to m-1 RCs or t-1 shares are available for adversaries. Our scheme does not depend on any assumption of hard problems or one way functions.
Joint Design of QC-LDPC Codes for Coded Relay Cooperation
TANG Lei, YANG Fengfan, ZHANG Shunwai, SAQIB Ejaz, LUO Lin
2016, 25(1): 179-184. doi: 10.1049/cje.2016.01.027
Abstract(124) PDF(523)
Abstract:
This paper proposes an effective method to jointly design girth-4 cycle-free Quasi-cyclic (QC) Low-density parity-check (LDPC) codes for multi-relay cooperation in a Rayleigh fading channel, where the joint iterative decoding by Min-sum algorithm (MSA) based on the introduced joint Tanner graph is also presented at the destination. Theoretical analysis and simulation show that the proposed QC-LDPC coded cooperation outperforms the randomly coded cooperation under the same conditions.
Cognitive Frequency Hopping Sequences
GUAN Lei, LI Zan, HAO Benjian, SI Jiangbo, NING Ben
2016, 25(1): 185-191. doi: 10.1049/cje.2016.01.028
Abstract(112) PDF(595)
Abstract:
Since the immutable conventional Frequency hopping (FH) sequence cannot keep high FH communication reliability in complex electromagnetic environment, we propose an algorithm that can generate high-performance Cognitive frequency hopping sequence (CFHS) for Cognitive frequency hopping (CFH) system. By employing the pseudo-random perturbation mapping, the CFHS is generated by remapping the block cipher FH sequence with the adaptive frequency slot number and frequency gap. The CFHS inherits the great integrated performance and its parameters could change with the electromagnetic environment. The statistics properties of Markov and uniformity are analyzed based on the Markov process theory and probability theory. Simulation results show that CFHS outperforms the widely-used FH sequences on the performance of uniformity, randomness, Hamming correlation, complexity and sensitivity. The proposed CFHS could be extensively applied in high reliable CFH system.
A Convolutional Network Coding Oriented Four-Stage Contention Protocol for All-to-All Broadcasting Networks
LIU Yun, WANG Shan, ZHU Bocheng
2016, 25(1): 192-198. doi: 10.1049/cje.2016.01.029
Abstract(91) PDF(547)
Abstract:
Most practical networks are cyclic and demand Convolutional network coding (CNC). Researches on application of CNC in practical networks are still insufficient. Conventional graph theories cannot model the multicast channel properly. This paper introduces a multicast graph with multicast edges to model the multicast networks, and proposes a Multicast edge generation and max-flow detection (MEGAMAD) algorithm to approach the lower bound of necessary multicast edge number for a multicast network. Based on the algorithm we designed a new Media access control (MAC) protocol, the CNC oriented four-stage contention protocol (NC-FSCP) for the all-to-all broadcasting networks. The protocol runs a four stage reservation procedure to reserve time slots for encoded data transmission. Simulation proves that the reserved slot number approaches the lower bound for data dispersion in an all-to-all broadcasting network.