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    COVER PAPER
  • COVER PAPER
    A Theory of Semantic Information
    Yixin Zhong
    2017, 14(1): 1-17.
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    The information really useful to humans must be the trinity of its three components: the form termed syntactic information, the meaning termed semantic information, and the utility termed pragmatic information. But the theory of information set up by Shannon in 1948 is a statistical theory of syntactic information. Thus, the trinity of information theories needs to be established as urgently as possible. Such a theory of semantic information will be presented in the paper and it will also be proved that it is the semantic information that is the unique representative of the trinity. This is why the title of the paper is set to “a theory of semantic information” without mentioning the pragmatic information.
    • FEATURE TOPIC: SELECTED PAPERS FROM EEE/CIC ICCC 2016
  • FEATURE TOPIC: SELECTED PAPERS FROM EEE/CIC ICCC 2016
    SELECTED PAPERS FROM IEEE/CIC ICCC 2016
    2017, 14(1): 18-19.
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  • FEATURE TOPIC: SELECTED PAPERS FROM EEE/CIC ICCC 2016
    Secure Beamforming Design for SWIPT in Cooperative D2D Communications
    Li Jiang, Cheng Qin, Xixi Zhang, Hui Tian
    2017, 14(1): 20-33.
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    In device-to-device (D2D) communications, device terminal relaying makes it possible for devices in a network to function as transmission relays for each other to enhance the spectral efficiency. In this paper we consider a cooperative D2D communication system with simultaneous wireless information and power transfer (SWIPT). The cooperative D2D communication scheme allows two nearby devices to communicate with each other in the licensed cellular bandwidth by assigning D2D transmitters as half-duplex (HD) relay to assists cellular downlink transmissions. In particular, we focus on secure information transmission for the cellular users when the idle D2D users are the potential eavesdroppers. We aim to design secure beamforming schemes to maximize the D2D users data rate while guaranteeing the secrecy rate requirements of the cellular users and the minimum required amounts of power transferred to the idle D2D users. To solve this non-convex problem, a semi-definite programming relaxation (SDR) approach is adopted to obtain the optimal solution. Furthermore, we propose two suboptimal secure beamforming schemes with low computational complexity for providing secure communication and efficient energy transfer. Simulation results demonstrate the superiority of our proposed scheme.
  • FEATURE TOPIC: SELECTED PAPERS FROM EEE/CIC ICCC 2016
    Hybrid Gene Expression Programming-Based Sensor Data Correlation Mining
    Lechan Yang, Zhihao Qin, Kun Wang, Song Deng
    2017, 14(1): 34-49.
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    This paper deals with the reflectance estimation model issue to improve the estimation accuracy. We propose a model containing two core procedures: dimensionality reduction and model mining. First, the dimensionality reduction algorithm of hyperspectral data based on dependence degree (DRND-DD) is proposed to reduce the redundant hyperspectral band. DRND-DD solves the selection of suitable hyperspectral band via rough set theory. Furthermore, to improve the computation speed and accuracy of the model, based on DRND-DD, this paper proposes reflectance estimation model mining of leaf nitrogen concentration (LNC) for hyperspectral data by using hybrid gene expression programming (REMLNC-HGEP). Experimental results on three datasets demonstrate that the DRND-DD algorithm can obtain good results with a very short running time compared with principal component analysis (PCA), singular value decomposition (SVD), a dimensionality reduction algorithm based on the positive region (AR-PR) and a dimensionality reduction algorithm based on a discernable matrix (AR-DM), and REMLNC-HGEP has low average time-consumption, high model mining success ratio and estimation accuracy. It was concluded that the REMLNC-HGEP performs better than the regression methods.
  • FEATURE TOPIC: SELECTED PAPERS FROM EEE/CIC ICCC 2016
    Power Allocation and Performance Analysis of the Collaborative NOMA Assisted Relaying Systems in 5G
    Xin Liu, Xianbin Wang, Yanan Liu
    2017, 14(1): 50-60.
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    Serving multiple cell-edge mobile terminals poses multifaceted challenges due to the increased transmission power and interferences, which could be overcome by relay communications. With the recent advancement of 5G technologies, non-orthogonal multiple access (NOMA) has been used at relay node to transmit multiple messages simultaneously to multiple cell-edge users. In this paper, a Collaborative NOMA Assisted Relaying (CNAR) system for 5G is proposed by enabling the collaboration of source-relay (S-R) and relay-destination (R-D) NOMA links. The relay node of the CNAR decodes the message for itself from S-R NOMA signal and transmits the remaining messages to the multiple cell-edge users in R-D link. A simplified-CNAR (S-CNAR) system is then developed to reduce the relay complexity. The outage probabilities for both systems are analyzed by considering outage behaviors in S-R and R-D links separately. To guarantee the data rate, the optimal power allocation among NOMA users is achieved by minimizing the outage probability. The ergodic sum capacity in high SNR regime is also approximated. Our mathematical analysis and simulation results show that CNAR system outperforms existing transmission strategies and S-CNAR reaches similar performance with much lower complexity.
  • FEATURE TOPIC: SELECTED PAPERS FROM EEE/CIC ICCC 2016
    Privacy Protection Based Access Control Scheme in Cloud-Based Services
    Kai Fan, Qiong Tian, Junxiong Wang, Hui Li, Yintang Yang
    2017, 14(1): 61-71.
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    With the rapid development of computer technology, cloud-based services have become a hot topic. They not only provide users with convenience, but also bring many security issues, such as data sharing and privacy issue. In this paper, we present an access control system with privilege separation based on privacy protection (PS-ACS). In the PS-ACS scheme, we divide users into private domain (PRD) and public domain (PUD) logically. In PRD, to achieve read access permission and write access permission, we adopt the Key-Aggregate Encryption (KAE) and the Improved Attribute-based Signature (IABS) respectively. In PUD, we construct a new multi-authority ciphertext policy attribute-based encryption (CP-ABE) scheme with efficient decryption to avoid the issues of single point of failure and complicated key distribution, and design an efficient attribute revocation method for it. The analysis and simulation result show that our scheme is feasible and superior to protect users’ privacy in cloud-based services.
  • FEATURE TOPIC: SELECTED PAPERS FROM EEE/CIC ICCC 2016
    Priority-Based Real-Time Stream Coding over Multi-Channel with Packet Erasures
    Yunkai Wei, Qianyu Liu, Zhoucha Hu, Yuming Mao
    2017, 14(1): 72-85.
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    Multi-channel can be used to provide higher transmission ability to the bandwidth-intensive and delay-sensitive real-time streams. However, traditional channel capacity theories and coding schemes are seldom designed for the real-time streams with strict delay constraint, especially in multi-channel context. This paper considers a real-time stream system, where real-time messages with different importance should be transmitted through several packet erasure channels, and be decoded by the receiver within a fixed delay. Based on window erasure channels and i.i.d. (identically and independently distributed) erasure channels, we derive the Multi-channel Real-time Stream Transmission (MRST) capacity models for Symmetric Real-time (SR) streams and Asymmetric Real-time (AR) streams respectively. Moreover, for window erasures, a Maximum Equilibrium Intra-session Code (MEIC) is presented for SR and AR streams, and is shown able to asymptotically achieve the theoretical MRST capacity. For i.i.d. erasures, we propose an Adaptive Maximum Equilibrium Intra-session Code (AMEIC), and then prove AMEIC can closely approach the MRST transmission capacity. Finally, the performances of the proposed codes are verified by simulations.
    • SIGNAL PROCESSING FOR COMMUNICATIONS
  • SIGNAL PROCESSING FOR COMMUNICATIONS
    A Block Parallel l0-Norm Penalized Shrinkage and Widely Linear Affine Projection Algorithm for Adaptive Filter
    Youwen Zhang, Shuang Xiao, Lu Liu, Dajun Sun
    2017, 14(1): 86-95.
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    To improve the identification capability of AP algorithm in time-varying sparse system, we propose a block parallel l0-SWL-DCD-AP algorithm in this paper. In the proposed algorithm, we first introduce the l0-norm constraint to promote its application for sparse system. Second, we use the shrinkage denoising method to improve its track ability. Third, we adopt the widely linear processing to take advantage of the non-circular properties of communication signals. Last, to reduce the high computational complexity and make it easy to implemented, we utilize the dichotomous coordinate descent (DCD) iterations and the parallel processing to deal with the tap-weight update in the proposed algorithm. To verify the convergence condition of the proposed algorithm, we also analyze its steady-state behavior. Several simulation are done and results show that the proposed algorithm can achieve a faster convergence speed and a lower steady-state misalignment than similar APA-type algorithm. When apply the proposed algorithm in the decision feedback equalizer (DFE), the bite error rate (BER) decreases obviously.
    • COMMUNICATIONS THEORIES & SYSTEMS
  • COMMUNICATIONS THEORIES & SYSTEMS
    Joint Optimal Energy-Efficient Cooperative Spectrum Sensing and Transmission in Cognitive Radio
    Weizhi Zhong, Kunqi Chen, Xin Liu
    2017, 14(1): 98-110.
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    In order to improve the energy efficiency (EE) in cognitive radio (CR), a joint optimal energy-efficient cooperative spectrum sensing (CSS) and transmission in multi-channel CR is proposed in this paper. EE is described as a tradeoff between the throughput and the entirely consumed power. A joint optimization problem is formulated to maximize EE by jointly optimizing local sensing time, number of cooperative sensing secondary users (SU), transmission bandwidth and power. A combined optimization algorithm of bi-level optimization, Polyblock optimization and Dinkelbach’s optimization is proposed to solve the proposed non-convex optimization problem effectively. The simulation results show that, compared with throughput maximization model (TMM), the energy efficiency maximization model (EEMM) improves EE of the CR system and limits the excessive power consumption effectively.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Toward a Scalable SDN Control Mechanism via Switch Migration
    Guozhen Cheng, Hongchang Chen, Hongchao Hu, Zhiming Wang
    2017, 14(1): 111-123.
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    Dynamic Controller Provisioning Problem (DCPP) is a key problem for scalable SDN. Previously, the solution to this problem focused on adapting the number of controllers and their locations with changing network conditions, but ignored balancing control loads via switch migration. In this paper, we study a scalable control mechanism to decide which switch and where it should be migrated for more balanced control plane, and we define it as Switch Migration Problem (SMP). The main contributions of this paper are as follows. First, we define a SDN model to describe the relation between controllers and switches from the view of loads. Based on this model, we form SMP as a Network Utility Maximization (NUM) problem with the objective of serving more requests under available control resources. Second, we design a synthesizing distributed algorithm for SMP --- Distributed Hopping Algorithm (DHA), by approximating our optimal objective via Log-Sum-Exp function. In DHA, individual controller performs algorithmic procedure independently. With the solution space F, we prove that the optimal gap caused by approximation is at most 1βlog|F|, and DHA procedure is equal to implementation of a time-reversible Markov Chain process. Finally, the results are corroborated by several numerical simulations.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Reputation-Based Cooperative Spectrum Sensing Algorithm for Mobile Cognitive Radio Networks
    Xinyu Wang, Min Jia, Qing Guo, Xuemai Gu, Guangyu Zhang
    2017, 14(1): 124-134.
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    Identifying malicious users accurately in cognitive radio networks (CRNs) is the guarantee for excellent detection performance. However, existing algorithms fail to take the mobility of secondary users into consideration. If applied directly in mobile CRNs, those conventional algorithms would overly punish reliable users at extremely bad or good locations, leading to an obvious decrease in detection performance. To overcome this problem, we divide the whole area of interest into several cells to consider the location diversity of the network. Each user’s reputation score is updated after each sensing slot and is used for identifying whether it is malicious or not. If so, it would be removed away. And then our algorithm assigns users in cells with better channel conditions, i.e. larger signal-to-noise ratios (SNRs), with larger weighting coefficients, without requiring the prior information of SNR. Detailed analysis about the validity of our algorithm is presented. The simulation results show that in a CRN with 60 mobile secondary users, among which, 18 are malicious, our solution has an improvement of detection probability by 0.97-dB and 3.57-dB when false alarm probability is 0.1, compared with a conventional trust-value-based algorithm and a trusted collaborative spectrum sensing for mobile CRNs, respectively.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Identifying the Unknown Tags in a Large RFID System
    Yu Fu, Zhihong Qian, Xue Wang, Guiqi Liu
    2017, 14(1): 135-145.
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    Radio frequency identification (RFID) technology has been extensively used in various practical applications, such as inventory management and logistics control, with its outstanding features (e.g. non-line-of-sight reading and fast identification). And in a large RFID system, unknown tag identification uses total execution time as the performance criterion. However, the performance of existing protocols in terms of execution time is not ideal. To get better time efficiency, a novel unknown tag identification protocol (NUTIP) is proposed. The novelty of NUTIP is demonstrated mainly in two aspects: i) NUTIP deactivates some known tags and identifies or labels some unknown tags during its first phase to prevent these tags from interfering unknown tag identification. ii) We optimize the parameter settings to minimize the total execution time. Simulation experiments show that the proposed protocol is far superior to other relevant protocols and suitable for both sparse unknown tags environment and dense unknown tags environment.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Offline Urdu Nastaleeq Optical Character Recognition Based on Stacked Denoising Autoencoder
    Ibrar Ahmad, Xiaojie Wang, Ruifan Li, Shahid Rasheed
    2017, 14(1): 146-157.
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    Offline Urdu Nastaleeq text recognition has long been a serious problem due to its very cursive nature. In order to get rid of the character segmentation problems, many researchers are shifting focus towards segmentation free ligature based recognition approaches. Majority of the prevalent ligature based recognition systems heavily rely on hand-engineered feature extraction techniques. However, such techniques are more error prone and may often lead to a loss of useful information that might hardly be captured later by any manual features. Most of the prevalent Urdu Nastaleeq test recognition was trained and tested on small sets. This paper proposes the use of stacked denoising autoencoder for automatic feature extraction directly from raw pixel values of ligature images. Such deep learning networks have not been applied for the recognition of Urdu text thus far. Different stacked denoising autoencoders have been trained on 178573 ligatures with 3732 classes from un-degraded (noise free) UPTI (Urdu Printed Text Image) data set. Subsequently, trained networks are validated and tested on degraded versions of UPTI data set. The experimental results demonstrate accuracies in range of 93% to 96% which are better than the existing Urdu OCR systems for such large dataset of ligatures.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Directional Routing Algorithm for Deep Space Optical Network
    Lei Guo, Xiaorui Wang, Yejun Liu, Pengchao Han, Yamin Xie, Yuchen Tan
    2017, 14(1): 158-168.
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    With the development of science, economy and society, the needs for research and exploration of deep space have entered a rapid and stable development stage. Deep Space Optical Network (DSON) is expected to become an important foundation and inevitable development trend of future deep-space communication. In this paper, we design a deep space node model which is capable of combining the space division multiplexing with frequency division multiplexing. Furthermore, we propose the directional flooding routing algorithm (DFRA) for DSON based on our node model. This scheme selectively forwards the data packets in the routing, so that the energy consumption can be reduced effectively because only a portion of nodes will participate the flooding routing. Simulation results show that, compared with traditional flooding routing algorithm (TFRA), the DFRA can avoid the non-directional and blind transmission. Therefore, the energy consumption in message routing will be reduced and the lifespan of DSON can also be prolonged effectively. Although the complexity of routing implementation is slightly increased compared with TFRA, the energy of nodes can be saved and the transmission rate is obviously improved in DFRA. Thus the overall performance of DSON can be significantly improved.
    • NETWORKS & SECURITY
  • NETWORKS & SECURITY
    Dynamic Weapon Target Assignment Based on Intuitionistic Fuzzy Entropy of Discrete Particle Swarm
    Yi Wang, Jin Li, Wenlong Huang, Tong Wen
    2017, 14(1): 169-179.
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    Aiming at the problems of convergence-slow and convergence-free of Discrete Particle Swarm Optimization Algorithm (DPSO) in solving large scale or complicated discrete problem, this article proposes Intuitionistic Fuzzy Entropy of Discrete Particle Swarm Optimization (IFDPSO) and makes it applied to Dynamic Weapon Target Assignment (WTA). First, the strategy of choosing intuitionistic fuzzy parameters of particle swarm is defined, making intuitionistic fuzzy entropy as a basic parameter for measure and velocity mutation. Second, through analyzing the defects of DPSO, an adjusting parameter for balancing two cognition, velocity mutation mechanism and position mutation strategy are designed, and then two sets of improved and derivative algorithms for IFDPSO are put forward, which ensures the IFDPSO possibly search as much as possible sub-optimal positions and its neighborhood and the algorithm ability of searching global optimal value in solving large scale 0-1 knapsack problem is intensified. Third, focusing on the problem of WTA, some parameters including dynamic parameter for shifting firepower and constraints are designed to solve the problems of weapon target assignment. In addition, WTA Optimization Model with time and resource constraints is finally set up, which also intensifies the algorithm ability of searching global and local best value in the solution of WTA problem. Finally, the superiority of IFDPSO is proved by several simulation experiments. Particularly, IFDPSO, IFDPSO1~IFDPSO3 are respectively effective in solving large scale, medium scale or strict constraint problems such as 0-1 knapsack problem and WTA problem.
  • NETWORKS & SECURITY
    A Non-Cooperative Differential Game-Based Security Model in Fog Computing
    Zhi Li, Xianwei Zhou, Yanzhu Liu, Haitao Xu, Li Miao
    2017, 14(1): 180-189.
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    Fog computing is a new paradigm providing network services such as computing, storage between the end users and cloud. The distributed and open structure are the characteristics of fog computing, which make it vulnerable and very weak to security threats. In this article, the interaction between vulnerable nodes and malicious nodes in the fog computing is investigated as a non-cooperative differential game. The complex decision making process is reviewed and analyzed. To solve the game, a fictitious play-based algorithm is which the vulnerable node and the malicious nodes reach a feedback Nash equilibrium. We attain optimal strategy of energy consumption with QoS guarantee for the system, which are conveniently operated and suitable for fog nodes. The system simulation identifies the propagation of malicious nodes. We also determine the effects of various parameters on the optimal strategy. The simulation results support a theoretical foundation to limit malicious nodes in fog computing, which can help fog service providers make the optimal dynamic strategies when different types of nodes dynamically change their strategies.