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  • REVIEW PAPER
    Mao Haobin, Liu Yanming, Zhu Lipeng, Mao Tianqi, Xiao Zhenyu, Zhang Rui, Han Zhu, Xia Xianggen
    Abstract ( )   Knowledge map   Save
    Space/air communications have been envisioned as an essential part of the next-generation mobile communication networks for providing highquality global connectivity. However, the inherent broadcasting nature of wireless propagation environment and the broad coverage pose severe threats to the protection of private data. Emerging covert communications provides a promising solution to achieve robust communication security. Aiming at facilitating the practical implementation of covert communications in space/air networks, we present a tutorial overview of its potentials, scenarios, and key technologies. Specifically, first, the commonly used covertness constraint model, covert performance metrics, and potential application scenarios are briefly introduced. Then, several efficient methods that introduce uncertainty into the covert system are thoroughly summarized, followed by several critical enabling technologies, including joint resource allocation and deployment/trajectory design, multi-antenna and beamforming techniques, reconfigurable intelligent surface (RIS), and artificial intelligence algorithms. Finally, we highlight some open issues for future investigation.
  • COMMUNICATIONS THEORIES & SYSTEMS
  • COMMUNICATIONS THEORIES & SYSTEMS
    Mao Yinyou, Yang Dong, Liu Xingcheng, Zou En
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    Belief propagation list (BPL) decoding for polar codes has attracted more attention due to its inherent parallel nature. However, a large gap still exists with CRC-aided SCL (CA-SCL) decoding. In this work, an improved segmented belief propagation list decoding based on bit flipping (SBPL-BF) is proposed. On the one hand, the proposed algorithm makes use of the cooperative characteristic in BPL decoding such that the codeword is decoded in different BP decoders. Based on this characteristic, the unreliable bits for flipping could be split into multiple sub-blocks and could be flipped in different decoders simultaneously. On the other hand, a more flexible and effective processing strategy for the priori information of the unfrozen bits that do not need to be flipped is designed to improve the decoding convergence. In addition, this is the first proposal in BPL decoding which jointly optimizes the bit flipping of the information bits and the code bits. In particular, for bit flipping of the code bits, a H-matrix aided bit-flipping algorithm is designed to enhance the accuracy in identifying erroneous code bits. The simulation results show that the proposed algorithm significantly improves the error-correction performance of BPL decoding for medium and long codes. It is more than $0.25$ dB better than the state-of-the-art BPL decoding at a block error rate (BLER) of $10^{-5}$, and outperforms CA-SCL decoding in the low signal-to-noise (SNR) region for (1024, 0.5) polar codes.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Pan Hao, Chen Yu, Qi Xiaogang, Liu Meili
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    Owing to the ubiquity of wireless networks and the popularity of WiFi infrastructures, received signal strength (RSS)-based indoor localization systems have received much attention. The placement of access points (APs) significantly influences localization accuracy and network access. However, the indoor scenario and network access are not fully considered in previous AP placement optimization methods. This study proposes a practical scenario modeling-aided AP placement optimization method for improving localization accuracy and network access. In order to reduce the gap between simulation-based and field measurement-based AP placement optimization methods, we introduce an indoor scenario modeling and Gaussian process-based RSS prediction method. After that, the localization and network access metrics are implemented in the multiple objective particle swarm optimization (MOPSO) solution, Pareto front criterion and virtual repulsion force are applied to determine the optimal AP placement. Finally, field experiments demonstrate the effectiveness of the proposed indoor scenario modeling method and RSS prediction model. A thorough comparison confirms the localization and network access improvement attributed to the proposed anchor placement method.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Liu Jinru, Tian Yongqing, Liu Danpu, Zhang Zhilong
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    Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) plays an important role in the fifth-generation (5G) mobile communications and beyond wireless communication systems owing to its potential of high capacity. However, channel estimation has become very challenging due to the use of massive MIMO antenna array. Fortunately, the mmWave channel has strong sparsity in the spatial angle domain, and the compressed sensing technology can be used to convert the original channel matrix into the sparse matrix of discrete angle grid. Thus the high-dimensional channel matrix estimation is transformed into a sparse recovery problem with greatly reduced computational complexity. However, the path angle in the actual scene appears randomly and is unlikely to be completely located on the quantization angle grid, thus leading to the problem of power leakage. Moreover, multiple paths with the random distribution of angles will bring about serious inter-path interference and further deteriorate the performance of channel estimation. To address these off-grid issues, we propose a parallel interference cancellation assisted multi-grid matching pursuit (PIC-MGMP) algorithm in this paper. The proposed algorithm consists of three stages, including coarse estimation, refined estimation, and inter-path cyclic iterative interference cancellation. More specifically, the angular resolution can be improved by locally refining the grid to reduce power leakage, while the inter-path interference is eliminated by parallel interference cancellation (PIC), and the two together improve the estimation accuracy. Simulation results show that compared with the traditional orthogonal matching pursuit (OMP) algorithm, the normalized mean square error (NMSE) of the proposed algorithm decreases by over 14dB in the case of 2 paths.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Fu Zihao, Liu Yinsheng, Duan Hongtao
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    Spatial covariance matrix (SCM) is essential in many multi-antenna systems such as massive multiple-input multiple-output (MIMO). For multi-antenna systems operating at millimeter-wave bands, hybrid analog-digital structure has been widely adopted to reduce the cost of radio frequency chains. In this situation, signals received at the antennas are unavailable to the digital receiver, and as a consequence, traditional sample average approach cannot be used for SCM reconstruction in hybrid multi-antenna systems. To address this issue, beam sweeping algorithm (BSA) which can reconstruct the SCM effectively for a hybrid uniform linear array, has been proposed in our previous works. However, direct extension of BSA to a hybrid uniform circular array (UCA) will result in a huge computational burden. To this end, a low-complexity approach is proposed in this paper. By exploiting the symmetry features of SCM for the UCA, the number of unknowns can be reduced significantly and thus the complexity of reconstruction can be saved accordingly. Furthermore, an insightful analysis is also presented in this paper, showing that the reduction of the number of unknowns can also improve the accuracy of the reconstructed SCM. Simulation results are also shown to demonstrate the proposed approach.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Zhang Yu, Chen Yong, He Panfeng, Cai Yueming
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    To solve the problem of delayed update of spectrum information (SI) in the database assisted dynamic spectrum management (DB-DSM), this paper studies a novel dynamic update scheme of SI in DB-DSM. Firstly, a dynamic update mechanism of SI based on spectrum opportunity incentive is established, in which spectrum users are encouraged to actively assist the database to update SI in real time. Secondly, the information update contribution (IUC) of spectrum opportunity is defined to describe the cost of accessing spectrum opportunity for heterogeneous spectrum users, and the profit of SI update obtained by the database from spectrum allocation. The process that the database determines the IUC of spectrum opportunity and spectrum user selects spectrum opportunity is mapped to a Hotelling model. Thirdly, the process of determining the IUC of spectrum opportunities is further modelled as a Stackelberg game by establishing multiple virtual spectrum resource providers (VSRPs) in the database. It is proved that there is a Nash Equilibrium in the game of determining the IUC of spectrum opportunities by VSRPs. Finally, an algorithm of determining the IUC based on a genetic algorithm is designed to achieve the optimal IUC. Theoretical analysis and simulation results show that the proposed method can quickly find the optimal solution of the IUC, and ensure that the spectrum resource provider can obtain the optimal profit of SI update.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Chu Hongyun, Pan Xue, Li Baijiang
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    It is assumed that reconfigurable intelligent surface (RIS) is a key technology to enable the potential of mmWave communications. The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS. In this paper, we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems, i.e., the two-stage estimation method where the cascaded channel is separated into the base station (BS)-RIS and the RIS-user (UE) ones. Specifically, we first reveal the cascaded sparsity, i.e., the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels, to construct the specific sparsity structure for RIS enabled multi-user systems. Then, we formulate the channel estimation problem using atomic norm minimization (ANM) to enhance the proposed sparsity structure in the continuous angular domains, where a low-complexity channel estimator via Alternating Direction Method of Multipliers (ADMM) is proposed. Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Wang Hui, Yu Xiangbin, Liu Fuyuan, Bai Jiawei
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    In this paper, we optimize the spectrum efficiency (SE) of uplink massive multiple-input multiple-output (MIMO) system with imperfect channel state information (CSI) over Rayleigh fading channel. The SE optimization problem is formulated under the constraints of maximum power and minimum rate of each user. Then, we develop a near-optimal power allocation (PA) scheme by using the successive convex approximation (SCA) method, Lagrange multiplier method, and block coordinate descent (BCD) method, and it can obtain almost the same SE as the benchmark scheme with lower complexity. Since this scheme needs three-layer iteration, a suboptimal PA scheme is developed to further reduce the complexity, where the characteristic of massive MIMO (i.e., numerous receive antennas) is utilized for convex reformulation, and the rate constraint is converted to linear constraints. This suboptimal scheme only needs single-layer iteration, thus has lower complexity than the near-optimal scheme. Finally, we joint design the pilot power and data power to further improve the performance, and propose an two-stage algorithm to obtain joint PA. Simulation results verify the effectiveness of the proposed schemes, and superior SE performance is achieved.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Dai Lin, Fang Yi, Guan Yongliang, Mohsen Guizani
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    This paper investigates the bit-interleaved coded generalized spatial modulation (BICGSM) with iterative decoding (BICGSM-ID) for multiple-input multiple-output (MIMO) visible light communications (VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain (SiD) symbols and the spatial-domain (SpD) light emitting diode (LED)-index patterns are coded by a protograph low-density parity-check (P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating (SSER) method for constructing a type of novel generalized spatial modulation (GSM) constellations, referred to as SSERGSM constellations , so as to boost the performance of the BICGSM-ID MIMO-VLC systems. Moreover, by applying a modified PEXIT (MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate (EARA) codes, which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSM-ID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.
  • NETWORKS & SECURITY
  • NETWORKS & SECURITY
    Lu Yin, Xue Yongtao, Li Qingyuan, Wu Luocheng, Li Taosen, Yang Peipei, Zhu Hongbo
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    Traditional IoT systems suffer from high equipment management costs and difficulty in trustworthy data sharing caused by centralization. Blockchain provides a feasible research direction to solve these problems. The main challenge at this stage is to integrate the blockchain from the resource-constrained IoT devices and ensure the data of IoT system is credible. We provide a general framework for intelligent IoT data acquisition and sharing in an untrusted environment based on the blockchain, where gateways become Oracles. A distributed Oracle network based on Byzantine Fault Tolerant algorithm is used to provide trusted data for the blockchain to make intelligent IoT data trustworthy. An aggregation contract is deployed to collect data from various Oracle and share the credible data to all on-chain users. We also propose a gateway data aggregation scheme based on the REST API event publishing/subscribing mechanism which uses SQL to achieve flexible data aggregation. The experimental results show that the proposed scheme can alleviate the problem of limited performance of IoT equipment, make data reliable, and meet the diverse data needs on the chain.
  • NETWORKS & SECURITY
    Zhang Lejun, Peng Minghui, Su Shen, Wang Weizheng, Jin Zilong, Su Yansen, Chen Huiling, Guo Ran, Sergey Gataullin
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    With the rapid development of information technology, IoT devices play a huge role in physiological health data detection. The exponential growth of medical data requires us to reasonably allocate storage space for cloud servers and edge nodes. The storage capacity of edge nodes close to users is limited. We should store hotspot data in edge nodes as much as possible, so as to ensure response timeliness and access hit rate; However, the current scheme cannot guarantee that every sub-message in a complete data stored by the edge node meets the requirements of hot data; How to complete the detection and deletion of redundant data in edge nodes under the premise of protecting user privacy and data dynamic integrity has become a challenging problem. Our paper proposes a redundant data detection method that meets the privacy protection requirements. By scanning the cipher text, it is determined whether each sub-message of the data in the edge node meets the requirements of the hot data. It has the same effect as zero-knowledge proof, and it will not reveal the privacy of users. In addition, for redundant sub-data that does not meet the requirements of hot data, our paper proposes a redundant data deletion scheme that meets the dynamic integrity of the data. We use Content Extraction Signature (CES) to generate the remaining hot data signature after the redundant data is deleted. The feasibility of the scheme is proved through safety analysis and efficiency analysis.
  • NETWORKS & SECURITY
    Long Qingyue, Wang Huandong, Chen Huiming, Jin Depeng, Zhu Lin, Yu Li, Li Yong
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    Human mobility prediction is important for many applications. However, training an accurate mobility prediction model requires a large scale of human trajectories, where privacy issues become an important problem. The rising federated learning provides us with a promising solution to this problem, which enables mobile devices to collaboratively learn a shared prediction model while keeping all the training data on the device, decoupling the ability to do machine learning from the need to store the data in the cloud. However, existing federated learning-based methods either do not provide privacy guarantees or have vulnerability in terms of privacy leakage. In this paper, we combine the techniques of data perturbation and model perturbation mechanisms and propose a privacy-preserving mobility prediction algorithm, where we add noise to the transmitted model and the raw data collaboratively to protect user privacy and keep the mobility prediction performance. Extensive experimental results show that our proposed method significantly outperforms the existing state-of-the-art mobility prediction method in terms of defensive performance against practical attacks while having comparable mobility prediction performance, demonstrating its effectiveness.
  • NETWORKS & SECURITY
    Xu Yinbo, Gao Mingyi, Zhu Huaqing, Chen Bowen, Xiang Lian, Shen Gangxiang
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    Orthogonal frequency division multiplexing passive optical network (OFDM-PON) has superior anti-dispersion property to operate in the C-band of fiber for increased optical power budget. However, the downlink broadcast exposes the physical layer vulnerable to the threat of illegal eavesdropping. Quantum noise stream cipher (QNSC) is a classic physical layer encryption method and well compatible with the OFDM-PON. Meanwhile, it is indispensable to exploit forward error correction (FEC) to control errors in data transmission. However, when QNSC and FEC are jointly coded, the redundant information becomes heavier and thus the code rate of the transmitted signal will be largely reduced. In this work, we propose a physical layer encryption scheme based on polar-code-assisted QNSC. In order to improve the code rate and security of the transmitted signal, we exploit chaotic sequences to yield the redundant bits and utilize the redundant information of the polar code to generate the higher-order encrypted signal in the QNSC scheme with the operation of the interleaver. We experimentally demonstrate the encrypted 16/64-QAM, 16/256-QAM, 16/1024-QAM, 16/4096-QAM QNSC signals transmitted over 30-km standard single mode fiber. For the transmitted 16/4096-QAM QNSC signal, compared with the conventional QNSC method, the proposed method increases the code rate from 0.1 to 0.32 with enhanced security.
  • NETWORKS & SECURITY
    Lyu Bin, Cao Yi, Wang Shuai, Guo Haiyan, Hao Chengyao
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    This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon (PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point (AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two sub-problems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation (SDR) and variable substitution techniques are applied to find a near-optimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.
  • NETWORKS & SECURITY
    Zhang Yue, Zheng Fuchun, Luo Jingjing
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    Due to the limited uplink capability in heterogeneous networks (HetNets), the decoupled uplink and downlink access (DUDA) mode has recently been proposed to improve the uplink performance. In this paper, the random discontinuous transmission (DTX) at user equipment (UE) is adopted to reduce the interference correlation across different time slots. By utilizing stochastic geometry, we analytically derive the mean local delay and energy efficiency (EE) of an uplink HetNet with UE random DTX scheme under the DUDA mode. These expressions are further approximated as closed forms under reasonable assumptions. Our results reveal that under the DUDA mode, there is an optimal EE with respect to mute probability under the finite local delay constraint. In addition, with the same finite mean local delay as under the coupled uplink and downlink access (CUDA) mode, the HetNets under the DUDA mode can achieve a higher EE with a lower mute probability.
  • EMERGING TECHNOLOGIES & APPLICATIONS
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Gu Shushi, Chen Zihan, Wu Yaonan, Zhang Qinyu, Wang Ye
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    Cooperative utilization of multi-dimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks (STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing (TSS) links and inter-satellite sharing (ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency (EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios (only TSS and TSS-ISS), and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively. Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Tong Minglei, Li Song, HanWanjiang, Wang Xiaoxiang
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    Mobile edge computing (MEC)-enabled satellite-terrestrial networks (STNs) can provide Internet of Things (IoT) devices with global computing services. Sometimes, the network state information is uncertain or unknown. To deal with this situation, we investigate online learning-based offloading decision and resource allocation in MEC-enabled STNs in this paper. The problem of minimizing the average sum task completion delay of all IoT devices over all time periods is formulated. We decompose this optimization problem into a task offloading decision problem and a computing resource allocation problem. A joint optimization scheme of offloading decision and resource allocation is then proposed, which consists of a task offloading decision algorithm based on the devices cooperation aided upper confidence bound (UCB) algorithm and a computing resource allocation algorithm based on the Lagrange multiplier method. Simulation results validate that the proposed scheme performs better than other baseline schemes.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Geng Yuhui, Wang Niwei, Chen Xi, Xu Xiaofan, Zhou Changsheng, Yang Junyi, Xiao Zhenyu, Cao Xianbin
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    With the advancements of software defined network (SDN) and network function virtualization (NFV), service function chain (SFC) placement becomes a crucial enabler for flexible resource scheduling in low earth orbit (LEO) satellite networks. While due to the scarcity of bandwidth resources and dynamic topology of LEO satellites, the static SFC placement schemes may cause performance degradation, resource waste and even service failure. In this paper, we consider migration and establish an online migration model, especially considering the dynamic topology. Given the scarcity of bandwidth resources, the model aims to maximize the total number of accepted SFCs while incurring as little bandwidth cost of SFC transmission and migration as possible. Due to its NP-hardness, we propose a heuristic minimized dynamic SFC migration (MDSM) algorithm that only triggers the migration procedure when new SFCs are rejected. Simulation results demonstrate that MDSM achieves a performance close to the upper bound with lower complexity.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Zhang Mengjiao, Liu Yu, Huang Jie, He Ruisi, Zhang Jingfan, Yu Chongyang, Wang Chengxiang
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    A large amount of mobile data from growing high-speed train (HST) users makes intelligent HST communications enter the era of big data. The corresponding artificial intelligence (AI) based HST channel modeling becomes a trend. This paper provides AI based channel characteristic prediction and scenario classification model for millimeter wave (mmWave) HST communications. Firstly, the ray tracing method verified by measurement data is applied to reconstruct four representative HST scenarios. By setting the positions of transmitter (Tx), receiver (Rx), and other parameters, the multi-scenarios wireless channel big data is acquired. Then, based on the obtained channel database, radial basis function neural network (RBF-NN) and back propagation neural network (BP-NN) are trained for channel characteristic prediction and scenario classification. Finally, the channel characteristic prediction and scenario classification capabilities of the network are evaluated by calculating the root mean square error (RMSE). The results show that RBF-NN can generally achieve better performance than BP-NN, and is more applicable to prediction of HST scenarios.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Tong Lili, Zeng Jia, Di Ying, Wang Nan
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    The social transformation brought about by digital technology is deeply impacting various industries. Digital education products, with core technologies such as 5G, AI, IoT (Internet of Things), etc., are continuously penetrating areas such as teaching, management, and evaluation. Apps, mini-programs, and emerging large-scale models are providing excellent knowledge performance and flexible cross-media output. However, they also expose risks such as content discrimination and algorithm commercialization. This paper conducts an evidence-based analysis of digital education product risks from four dimensions: "digital resources-information dissemination-algorithm design-cognitive assessment". It breaks through corresponding identification technologies and, relying on the diverse characteristics of governance systems, explores governance strategies for digital education products from the three domains of "regulators-developers-users".
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Zheng Quan, YanWenliang, Wu Rong, Tan Xiaobin, Yang Jian, Yuan Liu, Xu Zhenghuan
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    As users' access to the network has evolved into the acquisition of mass contents instead of IP addresses, the IP network architecture based on end-to-end communication cannot meet users' needs. Therefore, the Information-Centric Networking (ICN) came into being. From a technical point of view, ICN is a promising future network architecture. Researching and customizing a reasonable pricing mechanism plays a positive role in promoting the deployment of ICN. The current research on ICN pricing mechanism is focused on paid content. Therefore, we study an ICN pricing model for free content, which uses game theory based on Nash equilibrium to analysis. In this work, advertisers are considered, and an advertiser model is established to describe the economic interaction between advertisers and ICN entities. This solution can formulate the best pricing strategy for all ICN entities and maximize the benefits of each entity. Our extensive analysis and numerical results show that the proposed pricing framework is significantly better than existing solutions when it comes to free content.