China Communications

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  • October 2017 Vol. 14 No. 9
      
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  • Environmental Sound Event Detection in Wireless Acoustic Sensor Networks for Home Telemonitoring
    Hyoung-Gook Kim, Jin Young Kim
    2017, 14(9): 1-10.
    Abstract ( )   Knowledge map   Save
    In this paper, we present an approach to improve the accuracy of environmental sound event detection in a wireless acoustic sensor network for home monitoring. Wireless acoustic sensor nodes can capture sounds in the home and simultaneously deliver them to a sink node for sound event detection. The proposed approach is mainly composed of three modules, including signal estimation, reliable sensor channel selection, and sound event detection. During signal estimation, lost packets are recovered to improve the signal quality. Next, reliable channels are selected using a multi-channel cross-correlation coefficient to improve the computational efficiency for distant sound event detection without sacrificing performance. Finally, the signals of the selected two channels are used for environmental sound event detection based on bidirectional gated recurrent neural networks using two-channel audio features. Experiments show that the proposed approach achieves superior performances compared to the baseline.
  • A Model-Based Soft Decision Approach for Speech Enhancement
    Xianyun Wang, Feng Bao
    2017, 14(9): 11-22.
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    Many speech enhancement algorithms that deal with noise reduction are based on a binary masking decision (termed as the hard decision), which may cause some regions of the synthesized speech to be discarded. In view of the problem, a soft decision is often used as an optimal technique for speech restoration. In this paper, considering a new fashion of speech and noise models, we present two model-based soft decision techniques. One technique estimates a ratio mask generated by the exact Bayesian estimators of speech and noise. For the second technique, we consider one issue that an optimum local criterion (LC) for a certain SNR may not be appropriate for other SNRs. So we estimate a probabilistic mask with a variable LC. Experimental results show that the proposed method achieves a better performance than reference methods in speech quality.
  • Long Short-Term Memory Recurrent Neural Network-Based Acoustic Model Using Connectionist Temporal Classification on a Large-Scale Training Corpus
    Donghyun Lee, Jeong-Sik Park,*
    2017, 14(9): 23-31.
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    A Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model (GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model (HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate (WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.
  • High Quality Audio Object Coding Framework Based on Non-Negative Matrix Factorization
    Tingzhao Wu, Ruimin Hu
    2017, 14(9): 32-41.
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    Object-based audio coding is the main technique of audio scene coding. It can effectively reconstruct each object trajectory, besides provide sufficient flexibility for personalized audio scene reconstruction. So more and more attentions have been paid to the object-based audio coding. However, existing object-based techniques have poor sound quality because of low parameter frequency domain resolution. In order to achieve high quality audio object coding, we propose a new coding framework with introducing the non-negative matrix factorization (NMF) method. We extract object parameters with high resolution to improve sound quality, and apply NMF method to parameter coding to reduce the high bitrate caused by high resolution. And the experimental results have shown that the proposed framework can improve the coding quality by 25%, so it can provide a better solution to encode audio scene in a more flexible and higher quality way.
  • A Novel Two-Layer Model for Overall Quality Assessment of Multichannel Audio
    Jiyue Liu, Jing Wang, Min Liu, Xiang Xie, Jingming Kuang
    2017, 14(9): 42-51.
    Abstract ( )   Knowledge map   Save
    With the development of multichannel audio systems, corresponding audio quality assessment techniques, especially the objective prediction models, have received increasing attention. Existing methods, such as PEAQ (Perceptual Evaluation of Audio Quality) recommended by ITU, usually lead to poor results when assessing multichannel audio, which have little correlation with subjective scores. In this paper, a novel two-layer model based on Multiple Linear Regression (MLR) and Neural Network (NN) is proposed.Through the first layer, two indicators of multichannel audio, Audio Quality Score (AQS) and Spatial Perception Score (SPS) are derived,and through the second layer the overall score is output. The final results show that this model can not only improve the correlation with the subjective test score by 30.7% and decrease the Root Mean Square Error (RMSE) by 44.6%, but also add two new indicators:AQS and SPS, which can help reflect the multichannel audio quality more clearly.
  • Optimal Power Allocation for Multiuser OFDM-Based Cognitive Heterogeneous Networks
    Yongjun Xu
    2017, 14(9): 52-61.
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    Heterogeneous network (HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference management in multicell network structures. Although some works have been done for power allocation in heterogeneous femtocell networks, most of them focus centralized schemes for single-cell network under interference constraint of macrocell user. In this paper, a sum-rate maximization based power allocation algorithm is proposed for a downlink cognitive HetNet with one macrocell network and multiple microcell networks. The original power allocation optimization problem with the consideration of cross-tier interference constraint, maximum transmit power constraint of microcell base station and inter-cell interference of microcell networks is converted into a geometric programming problem which can be solved by Lagrange dual method in a distributed way. Simulation results demonstrate the performance and effectiveness of the proposed algorithm by comparing with the equal power allocation scheme.
  • Self-Interference Elimination by Physical Feedback Channel in CCFD for 3-D Beamforming Communication
    Naveed Ali Kaimkhani, Fuliang Yin*
    2017, 14(9): 62-71.
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    The 3-D beamforming scheme has elite as evolving interest because of its efficiency to empower assorted techniques such as vertical and horizontal domains and emanation beamforming according to subscriber’s provisions. Usually, 3-D beamforming communication is set up on FDD/TDD approach those effects on the performance of spectrum and energy efficiency. Co-frequency and Co-Time Full Duplex (CCFD) is an effective solution to improve the spectrum and energy efficiency by transmitting and receiving simultaneously in frequency and time domain. While, CCFD communication often face the self-interference issue when communication occurs, simultaneously. Consequently, in this paper a self-interference elimination by physical feedback channel in CCFD for 3-D Beamforming communication scheme is proposed to improve the over-all system performance in terms of energy and spectrum efficiency. The simulation and analytical outcomes demonstrated that the proposed system is superior than the traditional one.
  • Differential Game Based Link Resource Management for Next Generation Optical Network
    Haitao Xu, Xianwei Zhou
    2017, 14(9): 72-79.
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    In this paper, we investigate the link resource management problem for optical networks, to achieve the resource cost during the information transmission. We use the differential game to formulate the cost control problem for the link resource management, to minimize the resource allocation cost functions, which dynamic behaviours are described by differential equations. Each link controls its transmission bandwidth based on the Nash equilibriums of the differential game. The effectiveness of the proposed model is given through numerical simulations.
  • Generalized Block Markov Superposition Transmission over Free-Space Optical Links
    Jinshun Zhu, Xiao Ma
    2017, 14(9): 80-93.
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    In free-space optical (FSO) communications, the performance of the communication systems is severely degraded by atmospheric turbulence. Channel coding and diversity techniques are commonly used to combat channel fading induced by atmospheric turbulence. In this paper, we present the generalized block Markov superposition transmission (GBMST) of repetition codes to improve time diversity. In the GBMST scheme, information sub-blocks are transmitted in the block Markov superposition manner, with possibly different transmission memories. Based on analyzing an equivalent system, a lower bound on the bit-error-rate (BER) of the proposed scheme is presented. Simulation results demonstrate that, under a wide range of turbulence conditions, the proposed scheme improves diversity gain with only a slight reduction of transmission rate. In particular, with encoding memory sequence (0, 0, 8) and transmission rate 1/3, a diversity order of eleven is achieved under moderate turbulence conditions. Numerical results also show that, the GBMST systems with appropriate settings can approach the derived lower bound, implying that full diversity is achievable.
  • An Improved Empirical Mode Decomposition for Power Analysis Attack
    Han Gan, Hongxin Zhang
    2017, 14(9): 94-99.
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    Correlation power analysis (CPA) has become a successful attack method about crypto- graphic hardware to recover the secret keys. However, the noise influence caused by the random process interrupts (RPIs) becomes an important factor of the power analysis attack efficiency, which will cost more traces or attack time. To address the issue, an improved method about empirical mode decomposition (EMD) was proposed. Instead of restructuring the decomposed signals of intrinsic mode functions (IMFs), we extract a certain intrinsic mode function (IMF) as new feature signal for CPA attack. Meantime, a new attack assess- ment is proposed to compare the attack effectiveness of different methods. The experiment shows that our method has more excellent performance on CPA than others. The first and the second IMF can be chosen as two optimal feature signals in CPA. In the new method, the signals of the first IMF increase peak visibility by 64% than those of the tradition EMD method in the situation of non-noise. On the condition of different noise interference, the orders of attack efficiencies are also same. With external noise interference, the attack effect of the first IMF based on noise with 15dB is the best.
  • Empathizing with Emotional Robot Based on Cognition Reappraisal
    Xin Liu, Zhiliang Wang
    2017, 14(9): 100-113.
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    This paper proposes a continuous cognitive emotional regulation model for robot in the case of external emotional stimulus from interactive person’s expressions. It integrates a guiding cognitive reappraisal strategy into the HMM (Hidden Markov Model) emotional interactive model for empathizing between robot and person. The emotion is considered as a source in the 3D space (Arousal, Valence, and Stance). State transition and emotion intensity can be quantitatively analyzed in the continuous space. This cognition-emotion interactive model have been verified by the expression and behavior robot. Empathizing is the main distinguishing feature of our work, and it is realized by the emotional regulation which operated in a continuous 3D emotional space enabling a wide range of intermediate emotions. The experiment results provide evidence with acceptability, accuracy, richness, fluency, interestingness, friendliness and exaggeration that the robot with cognition and emotional control ability could be better accepted in the human-robot interaction (HRI).
  • Light Weight Cryptographic Address Generation (LW-CGA) Using System State Entropy Gathering for IPv6 Based MANETs
    Reshmi T.R, Murugan K
    2017, 14(9): 114-126.
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    In IPv6 based MANETs, the neighbor discovery enables nodes to self-configure and communicate with neighbor nodes through autoconfiguration. The Stateless address autoconfiguration (SLAAC) has proven to face several security issues. Even though the Secure Neighbor Discovery (SeND) uses Cryptographically Generated Addresses (CGA) to address these issues, it creates other concerns such as need for CA to authenticate hosts, exposure to CPU exhaustion attacks and high computational intensity. These issues are major concern for MANETs as it possesses limited bandwidth and processing power. The paper proposes empirically strong Light Weight Cryptographic Address Generation (LW-CGA) using entropy gathered from system states. Even the system users cannot monitor these system states; hence LW-CGA provides high security with minimal computational complexity and proves to be more suitable for MANETs. The LW-CGA and SeND are implemented and tested to study the performances. The evaluation shows that LW-CGA with good runtime throughput takes minimal address generation latency.
  • A Flow-Based Authentication Handover Mechanism for Multi-Domain SDN Mobility Environment
    Ke Ding, Ming Chen
    2017, 14(9): 127-143.
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    The long authentication handover delay is the greatest challenge in multi-domain SDN environment. In order to solve this problem, an authentication handover mechanism under multi-SDN domain (AHMMD) is proposed in this paper. In AHMMD, firstly, when the mobility entity accesses the network for the first time, its identity and service attributes are authenticated by the flow authentication protocol, which is designed based on the asymmetric encryption key; secondly, when the mobility entity moves to the neighbor domain, the authentication information will be delivered from the current controller to the neighborhood controller through a security communication channel. In order to promote the efficiency, a handover time prediction algorithm is adopted in AHMMD. Experimental results based on our AHMMD prototype have shown that the handover delay decreases by 50% while the handover cost decreases by 60%.
  • An Aware-Scheduling Security Architecture with Priority-Equal Multi-Controller for SDN
    Chao Qi, Shuo Zhao
    2017, 14(9): 144-154.
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    Current SDN controllers suffer from a series of potential attacks. For example, malicious flow rules may lead to system disorder by introducing unexpected flow entries. In this paper, we propose Mcad-SA, an aware decision-making security architecture with multiple controllers, which could coordinate heterogeneous controllers internally as a “big” controller. This architecture includes an additional plane, the scheduling plane, which consists of transponder, sensor, decider and scheduler. Meanwhile it achieves the functions of communicating, supervising and scheduling between data and control plane. In this framework, we adopt the vote results from the majority of controllers to determine valid flow rules distributed to switches. Besides, an aware dynamic scheduling (ADS) mechanism is devised in scheduler to intensify security of Mcad-SA further. Combined with perception, ADS takes advantage of heterogeneity and redundancy of controllers to enable the control plane operate in a dynamic, reliable and unsteady state, which results in significant difficulty of probing systems and executing attacks. Simulation results demonstrate the proposed methods indicate better security resilience over traditional architectures as they have lower failure probability when facing attacks.
  • A Privacy-Based SLA Violation Detection Model for the Security of Cloud Computing
    Shengli Zhou , Canghong Jin
    2017, 14(9): 155-165.
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    A Service Level Agreement (SLA) is a legal contract between any two parties to ensure an adequate Quality of Service (QoS). Most research on SLAs has concentrated on protecting the user data through encryption. However, these methods can not supervise a cloud service provider (CSP) directly. In order to address this problem, we propose a privacy-based SLA violation detection model for cloud computing based on Markov decision process theory. This model can recognize and regulate CSP’s actions based on specific requirements of various users. Additionally, the model could make effective evaluation to the credibility of CSP, and can monitor events that user privacy is violated. Experiments and analysis indicate that the violation detection model can achieve good results in both the algorithm’s convergence and prediction effect.
  • Polar-Coded Modulation Based on the Amplitude Phase Shift Keying Constellations
    Dekun Zhou, Jingyuan Sun, Hao Guan
    2017, 14(9): 166-177.
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    In this paper, we investigate the polarization effect of the amplitude phase shift keying (APSK) constellations. We find that the polarization effect of the APSK constellations is affected by the bit mapping and the bit loading. Traditionally, the Gray mapping is usually adopted in APSK constellations. Based on the given Gray mapping, we firstly propose the bit interleaved coded modulation polar-APSK (BICM-PA) scheme, which neglects the correlations between the bit levels by using the bit interleaver. In the BICM-PA scheme, a new metric called cumulative Bhattacharyya parameter is introduced to optimize the bit loading of the APSK constellations under the Gray mapping. Second, the multilevel coded modulation polar-APSK (MLCM-PA) is proposed to further improve the performance. A two-stage optimization approach is adopted to select the bit mapping and the bit loading in the MLCM-PA scheme. The semi-set partitioning mapping is introduced to achieve a better system performance in the MLCM-PA scheme. Simulation results verify the effectiveness of all the proposed metrics. In addition to this, BICM-PA and MLCM-PA both outperform the coded modulation Turbo-APSK scheme up to 1dB.
  • Homomorphic Error-Control Codes for Linear Network Coding in Packet Networks
    Xiaodong Han, Fei Gao*
    2017, 14(9): 178-189.
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    In this work, the homomorphism of the classic linear block code in linear network coding for the case of binary field and its extensions is studied. It is proved that the classic linear error-control block code is homomorphic network error-control code in network coding. That is, if the source packets at the source node for a linear network coding are precoded using a linear block code, then every packet flowing in the network regarding to the source satisfies the same constraints as the source. As a consequence, error detection and correction can be performed at every intermediate nodes of multicast flow, rather than only at the destination node in the conventional way, which can help to identify and correct errors timely at the error-corrupted link and save the cost of forwarding error-corrupted data to the destination node when the intermediate nodes are ignorant of the errors. In addition, three examples are demonstrated which show that homomorphic linear code can be combined with homomorphic signature, McEliece public-key cryptosystem and unequal error protection respectively and thus have a great potential of practical utility.
  • An Iterative Detection/Decoding Algorithm of Correlated Sources for the LDPC-Based Relay Systems
    Haiqiang Chen, Haibin Wan, Tuanfa Qin*
    2017, 14(9): 190-198.
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    An iterative detection/decoding algorithm of correlated sources for the LDPC-based relay systems is presented. The signal from the source-destination (S-D) link is formulated as a highly correlated counterpart from the relay-destination (R-D) link. A special XOR vector is defined using the correlated hard decision information blocks from two decoders and the extrinsic information exchanged between the two decoders is derived by the log-likelihood ratio (LLR) associated with the XOR vector. Such the decoding scheme is different from the traditional turbo-like detection/decoding algorithm, where the extrinsic information is computed by the side information and the soft decoder outputs. Simulations show that the presented algorithm has a slightly better performance than the traditional turbo-like algorithm (Taking the (255,175) EG-LDPC code as an example, it achieves about 0.1dB performance gains around BLER=10-4). Furthermore, the presented algorithm requires fewer computing operations per iteration and has faster convergence rate. For example, the average iteration of the presented algorithm is 33 at SNR=1.8dB, which is about twice faster than that of the turbo-like algorithm, when decoding the (961,721) QC-LDPC code. Therefore, the presented decoding algorithm of correlated sources provides an alternative decoding solution for the LDPC-based relay systems.