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25 April 2017, Volume 38 Issue 4

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Papers

Amplitude and phase errors calibration method in satellite-borne dynamic power allocation network

Qi TANG,Jun-min JIANG,Meng XIA

2017, 38(4):  1-07.  doi:10.11959/j.issn.1000-436x.2017078

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For the mobile communication satellite each beam communication traffic distribution was not balanced,leading to differences in transmission power of downlink beam.The implementation architectures of dynamic power allocation network was given,which could allocate the transmitting beam power automatically according to the traffic demand,at the same time ensured the high efficiency of power amplifier.Because the performance of dynamic power allocation network was severely impaired by the mutual coupling among signals when amplitude/phase mismatch was existed,which led to a sharp drop in beam performance.A calibration method for the amplitude and phase errors was proposed.The decoupling of calibration signal was realized by using the cross-correlation orthogonal characteristic of the orthogonal zero-correlation zone (ZCZ) sequences in the zero correlation interval,and communication was free from calibration by reducing the transmit power for the excellent self-correlation characteristic of the ZCZ sequences.Performance simulation and far field test show that under the condition that the calibration signal power is less than the normal signal 10 dB,the amplitude error is less than 0.1 dB,the phase error is less than 0.3°,and the gain loss within the main lobe is less than 0.2 dB after calibration.

Android malware detection based on improved random forest

Hong-yu YANG,Jin XU

2017, 38(4):  8-16.  doi:10.11959/j.issn.1000-436x.2017073

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Aiming at the defect of vote principle in random forest algorithm which is incapable of distinguishing the differences between strong classifier and weak classifier,a weighted voting improved method was proposed,and an improved random forest classification (IRFCM) was proposed to detect Android malware on the basis of this method.The IRFCM chose Permission information and Intent information as attribute features from AndroidManifest.xml files and optimized them,then applied the model to classify the final feature vectors.The experimental results in Weka environment show that IRFCM has better classification accuracy and classification efficiency.

Adaptive Gaussian back-end based on LDOF criterion for language recognition

Zhong-fu YE,Ting QI,Sai-feng LI,Yan SONG

2017, 38(4):  17-24.  doi:10.11959/j.issn.1000-436x.2017096

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In order to alleviate the mismatch in model between training and testing samples caused by inter-language variations,adaptive Gaussian back-end based on LDOF criterion was proposed for language recognition.The local distance-based outlier factor (LDOF) criterion was defined to find the appropriate model parameters and dynamically select the training data subset similar to the testing samples from multiple class training sets.Then original back-end was adjusted to obtain a more matched recognition model.Experimental results on NIST LRE 2009 easily-confused language data set show that proposed method achieves an obvious performance improvement on both the equal error rate (ERR) and average decision cost function.

Data dissemination of VANET based on lower bound of road delay

Xin PENG,Ren-fa LI,Zhe-tao LI,Guo-qi XIE

2017, 38(4):  25-34.  doi:10.11959/j.issn.1000-436x.2017093

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A reliable VANET data dissemination method was proposed.The method used the traffic information to estimate data transmission delay in each road.Compressive sensing method was used to deduce the lower bound of data transmission delay among each intersection.These information could assist carrier to choose forward routing.In the process of data forward,the vehicle that its route more similar with the forwarding data will be chosen as the next carrier.Furthermore,data forward probability at intersection was deduced based on Markov model.The simulation results demonstrate that presented method achieves lower-delay and higher reliable performance than existed packet forward protocols.

Certificateless generalized signcryption scheme in the standard model

Shu-fen NIU,Ling NIU,Cai-fen WANG,Ya-hong LI

2017, 38(4):  35-45.  doi:10.11959/j.issn.1000-436x.2017072

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In 2010,Liu,et al.proposed a certificateless signcryption scheme in the standard model,but many analyses revealed that Liu's scheme was insecure in fact.To overcome the disadvantages,the scheme was improved and a certificateless generalized signcryption scheme was constructed.In addition,a formal security model for the proposed scheme against the malicious-but-passive KGC attacks was introduced.Furthermore,the proposed scheme was proven to be secure under the decisional bilinear Diffie-Hellman and the computational Diffie-Hellman intractability assumptions in the standard model.Numerical results illustrate that the proposed algorithm is efficient.

Blind recognition of STBC-OFDM signals based on modified K-S test

Qing LING,Li-min ZHANG,Wen-jun YAN

2017, 38(4):  46-54.  doi:10.11959/j.issn.1000-436x.2017082

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Aiming at the problem that existed blind classification of STBC-OFDM in multiple input single output (MISO) communication system,an efficient method for blind classification of space-time block coded orthogonal frequency-division multiplexing (STBC-OFDM) signals based on modified Kolmogorov-Smirnov (K-S) test was proposed,when a single receiver antenna was employed at the receiver.Firstly,the model of received STBC-OFDM signals in MISO systems was given.Secondly,with the correlation of the coding matrix of STBC-OFDM signals,and the discrimination features function provided by the empirical cumulative distribution (CDFs) of the received OFDM blocks was constructed.Finally,the distance between CDFs was tested by the two-sample K-S test,which could blindly classify the STBC-OFDM signals.The proposed algorithm didn't need the estimation of channel,noise statistics and modulation type,and consequently,was well suited for non-cooperative communication context.Theoretical analysis and experimental verify its validity.

Attribute-based fully homomorphic encryption scheme over rings

Yong-hui ZHENG,Yuan-ji KANG,Chun-xiang GU,Hui DONG

2017, 38(4):  55-63.  doi:10.11959/j.issn.1000-436x.2017077

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The fully homomorphic encryption has important applications in the area of data security and privacy security of cloud computing,but the size of secret keys and ciphertext in most of current homomorphic encryption schemes were too large,which restricted its practical.To improve these drawbacks,a recoding scheme and a attribute-based encryption scheme based on learning with errors problem over rings were provided,then a attribute-based fully homomorphic encryption was constructed.The new scheme overcame the above mentioned drawbacks,because it did't need public key certificate,meanwhile,it can achieve the fine-grained access control to the ciphertext.Compared with similar results,proposed method decreases the size of keys and ciphertext greatly.

Data sharing scheme supporting secure outsourced computation in wireless body area network

Wei-wei ZHANG,Yu-zhao ZHANG,Chao HUANG,Ru ZHANG,Yi-xian YANG

2017, 38(4):  64-75.  doi:10.11959/j.issn.1000-436x.2017085

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How to effectively protect the security of data sharing in WBAN was a key problem to be solved urgently.The traditional CP-ABE mechanism had a 〝one to many〝 data security communication function which was suitable for access control in WBAN,but it had high computational complexity and did not support attribute revocation.Fully considering of limitations on computation and storage of sensor nodes and dynamic user attribute in WBAN,a CP-ABE scheme was proposed which was provably secure against CPA under the standard model and supported attributes revocation,outsourced encryption and decryption.Compared with the proposed schemes,the computation burden on senor nodes is greatly reduced and the user's attribution can be revoked immediately and fine grained while meeting the demand of its security in the proposed scheme.

Efficient algorithm for calculating short cycles in Tanner graph based on matrix computation

Qing ZHU,Le-nan WU,Yong-biao YANG,Jie LI,Shi-ming XU

2017, 38(4):  76-85.  doi:10.11959/j.issn.1000-436x.2017083

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Loop distribution of Tanner graph affects the BER performance of low-density parity-check codes(LDPC) decoding.To count short cycles in the Tanner graph efficiently,a side by side recursion algorithm based on matrix computation was proposed.Firstly,5 basic graph structures were defined to realize recursive calculate in the implementation process.Compared with previous works,the algorithm provided many methods for counting the same length of cycles.The same result confirmed the correctness of the algorithm.The new algorithm could not only calculate the total number of cycles,but also gave the number each edge participating in fixed-length cycles.Its complexity was proportional to the product of D and square of N,where D was the average degree of variable nodes,and N denoted the code length.For LDPC codes,D was far less than N.For most of the LDPC codes,the calculation for numbers of cycle-length g、g+2、g+4 was only several seconds.

New method of text representation model based on neural network

Shui-fei ZENG,Xiao-yan ZHANG,Xiao-feng DU,Tian-bo LU

2017, 38(4):  86-98.  doi:10.11959/j.issn.1000-436x.2017088

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Method of text representation model was proposed to extract word-embedding from text feature.Firstly,the word-embedding of the dual word-embedding list based on dictionary index and the corresponding part of speech index was created.Then,feature vectors was obtained further from these extracted word-embeddings by using Bi-LSTM recurrent neural network.Finally,the sentence vectors were processed by mean-pooling layer and text categorization was classified by softmax layer.The training effects and extraction performance of the combination model of Bi-LSTM and double word-embedding neural network were verified.The experimental results show that this model not only performs well in dealing with the high-quality text feature vector and the expression sequence,but also significantly outperforms other three kinds of neural networks,which includes LSTM,LSTM+context window and Bi-LSTM.

Communication emitter individual identification based on 3D-Hibert energy spectrum and multi-scale fractal features

Jie HAN,Tao ZHANG,Huan-huan WANG,Dong-fang REN

2017, 38(4):  99-109.  doi:10.11959/j.issn.1000-436x.2017080

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For communication emitter identification,a novel method based on Hilbert-Huang transform (HHT) and multi-scale fractal features was proposed.First,the time frequency energy spectrum was derived via HHT,which was called a complicated curved surface in the three-dimension space,namely,3D-Hilbert energy spectrum.Then,the differential box dimension and the multi-fractal dimension was extracted to compose the feature vector under multi-scale segmentation using fractal theory.Finally,communication emitter individual identification was obtained using the two dimensions of features above and the support vector machine (SVM).Moreover,the novel method was compared with two existing methods to identify simulated and actual signals with different and the same modulation modes,respectively.Results show that the identification rate of the novel method is higher than that of the two other methods.The features extracted by the novel method have high stability,sufficiency,and identifiability,also outweigh the negative effects of the change of signal-to-noise ratio and the number of training samples and emitters.

Position related lightweight Sybil detection approach in VANET

Yan XIN,Xia FENG,Ting-ting LI

2017, 38(4):  110-119.  doi:10.11959/j.issn.1000-436x.2017055

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In VANET,the Sybil attack simultaneously using multiple forged identities can easily cause the injustice of resource usage and make networks in a mess by distributing false messages.To solve this problem,an event-driven lightweight algorithm was proposed,which could identify vehicles false position quickly.When one vehicle appeared inside another's safety zone,a geometrical cross-recognition algorithm to calculate the overlap between vehicles to detect false position claiming was presented.At the same time,according to the neighbors within the confirming vehicle's radio range,position deviation matrix was established further to identify the Sybil node of two overlap vehicles.The performance analysis and simulation results show that the lightweight algorithm driven by safety zone demonstrates fast identification and high detection rate,especially when GPS error is very low.The imported safety zone can also balance the communication load impacting by heavy vehicular density.And the communication processing delay is lower than other approaches.

Sparse signal transmission under lossy wireless links based on double process of compressive sensing

Peng SUN,Gui-nan LI,Lian-tao WU,Zhi WANG

2017, 38(4):  120-128.  doi:10.11959/j.issn.1000-436x.2017074

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In resource-limited wireless sensor networks,links with poor quality hinder its large-scale applications seriously.Thanks to the inherent sparse property of signals in WSN,the framework of sparse signal transmission based on double process of compressive sensing was proposed,providing an insight into a new way of real-time,accurate and energy-efficient sparse signal transmission.Firstly,the random packet loss during transmission under lossy wireless links was modeled as a linear dimension-reduced measurement process of CS (a passive process of CS).Then,considering that a large packet was often adopted in WSN for higher transmission efficiency,a random linear dimension-reduced projection (a simple source coding operation) was employed at the sender node (an active process of CS) to prevent block data loss.Now,the raw signal could be recovered from the lossy data at the receiver node using CS reconstruction algorithms.Furtherly,according to the theory of CS reconstruction and the formula of packet reception rate in wireless communication,the minimum compression ratio and the maximum packet length allowed were obtained.Extensive simulations demonstrate that the reliability of data transmission and its accuracy,the data transmission volume,the transmission delay and energy consumption could be greatly optimized by means of proposed method.

SAPA-based approach for defending DoS attacks in cloud computing

Meng YUE,Kun LI,Zhi-jun WU

2017, 38(4):  129-139.  doi:10.11959/j.issn.1000-436x.2017079

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Denial of service (DoS) attack was one of the major threats to cloud computing.Security access path algorithm (SAPA) used node route table (NRT) to compose security access path.It simplified role nodes of traditional secure overlay services (SOS),and periodically updated role nodes,and cached security access paths.Therefore,SAPA was more appropriate for cloud computing to defend DoS attacks.Based on the turn routing architecture of cloud computing,the mathematical model of SAPA was built and its performance was analyzed in theory.The performance of SAPA was tested in OMNeT++ experimental platform.Also,the Test-bed experiments were performed to evaluate the effectiveness of SAPA for defending DoS attack.Experimental results show that comparing with SOS,SAPA can degrade the impact of communication success rate caused by DoS attack effectively,and guarantees the access delay small enough.

Study on an improved naive Bayes algorithm in spam filtering

Lei YANG,Cui-ling CAO,Jian-guo SUN,Li-guo ZHANG

2017, 38(4):  140-148.  doi:10.11959/j.issn.1000-436x.2017084

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A method of improved support vector machine naive Bayes algorithm was proposed——TSVM-NB algorithm.

Moving anchor node localization algorithm based on network connectivity

Ying LIU,Zhi-hong QIAN

2017, 38(4):  149-157.  doi:10.11959/j.issn.1000-436x.2017090

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In order to better solve the contradiction between precision of localization and the number of anchor nodes in wireless sensor network,a mobile anchor node localization technology based on connectivity was proposed.First,the coverage characteristic of the network nodes was analyzed,and a critical value was found between the mobile step and the anchor node communication radius,mobile anchor nodes＇ coverage characteristic would change when near this critical value.Second,a mobile anchor node followed a planning path to form a positioning area seamless coverage was used.Finally,when there was no need for high-precision technology,node position would been estimated according with the connectivity of the network and the receiving information of the node.The simulation results show that the proposed algorithm can realize coarse-grained localization,and paths perform complete localization.

Optimum hierarchical segmentation of OCT images in retina based on macular distance

Jian-feng LI,Yi-zhou LU

2017, 38(4):  158-165.  doi:10.11959/j.issn.1000-436x.2017087

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Retina layering was the basis of optic disc structure analysis and 3D feature extraction of glaucoma.In order to improve the layering effect of retinal OCT images,an intensity based multilayer segmentation algorithm for two-dimensional retinal OCT images was proposed.Through preprocessing and filtering operation,the segmentation algorithm calculated the intensity and intensity gradient of each A-scan in the retinal OCT image to obtain the upper bound RNFL,the dividing line IS and OS,and the lower bound RPE.Then macular distance strategy,calculated by the shortest distance,was used to further optimize the layering result of macular area,so as to achieve layering segmentation of the retinal OCT images.The experimental results show the algorithm has good optimization effect,low time complexity and fast running speed.

Correspondences

Actor-critic algorithm with incremental dual natural policy gradient

Peng ZHANG,Quan LIU,Shan ZHONG,Jian-wei ZHAI,Wei-sheng QIAN

2017, 38(4):  166-177.  doi:10.11959/j.issn.1000-436x.2017089

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The existed algorithms for continuous action space failed to consider the way of selecting optimal action and utilizing the knowledge of the action space,so an efficient actor-critic algorithm was proposed by improving the natural gradient.The objective of the proposed algorithm was to maximize the expected return.Upper and the lower bounds of the action range were weighted to obtain the optimal action.The two bounds were approximated by linear function.Afterward,the problem of obtaining the optimal action was transferred to the learning of double policy parameter vectors.To speed the learning,the incremental Fisher information matrix and the eligibilities of both bounds were designed.At three reinforcement learning problems,compared with other representative methods with continuous action space,the simulation results show that the proposed algorithm has the advantages of rapid convergence rate and high convergence stability.

Blind separation of asymmetric PCMA signal based on soft information joint correction

Qiang HUANG,Hua PENG,Tian-yun LI,Ke-xian GONG

2017, 38(4):  178-189.  doi:10.11959/j.issn.1000-436x.2017044

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On the basis of a blind separation structure with low complexity,an efficient blind separation algorithm based on soft information joint correction was proposed for asymmetric PCMA to improve the demodulation performance of strong and weak signals.By utilizing the demodulation mutual influence between the strong and weak signals,this algorithm tried to correct the receiving symbols of strong signal with high error probability.Comparing the symbol constellation quality (soft information) of signals before and after correction,it can be decided whether the hard decision values of strong and weak signals need to be modified,which efficiently reduce the demodulation error rate of strong and weak signals.The simulation results show that,the demodulation error rate of strong and weak signals can be reduced by nearly two orders of magnitude after joint correction especially when the signal to noise ratio of strong signal is higher than 17 dB,and the computational complexity of this algorithm is lower than that of the conventional reconstruction cancellation algorithm.

Low-complexity FTN receivers based on frequency domain iterative decision feedback equalization

Juan ZENG,Ying WANG,Xiao-na LI,Zhong-fang WANG,Yong-ming WANG

2017, 38(4):  190-198.  doi:10.11959/j.issn.1000-436x.2017052

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Faster-than-Nyquist (FTN) signaling can improve the system effectiveness without reducing the system reliability,but the fierce inter-symbol interference (ISI) introduced by it may cause that the complexity of the optimal receiver is intolerable.An effective low-complexity FTN receiver is iterative block decision feedback equalizer (IBDFE),which can achieve performance close to the optimal receiver with much lower complexity,but its complexity can be further reduced.Therefore,a reduced-complexity IBDFE (RC-IBDFE) was proposed for FTN communication systems,which was based on IBDFE,but introduced a simplified method to design the feedforward and feedback filters.When packing factor is τ={0.8,0.7},numerical results and analysis indicate that,compared with IBDFE,RC-IBDFE has stronger robustness,its complexity is reduced by {45.7%,25%},and its performance gain is {0.605 4,0.193 6} dB when the bit error rate (BER) is 10^-5.Compared with the existing low-complexity IBDFE (LC-IBDFE),RC-IBDFE has stronger robustness,its complexity is reduced by {13.6%,-25.8%},and its performance gain is {0.289 7,0.531 2} dB when the BER is 10^-5.