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30 March 2024, Volume 8 Issue 1
Theory and Technology
Survey on the research progress of generative adversarial networks for 6G
Chanyuan MENG, Ke XIONG, Bo GAO, Yu ZHANG, Pingyi FAN
2024, 8(1):  1-16.  doi:10.11959/j.issn.2096-3750.2024.00369
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The deep integration of artificial intelligence (AI) and communication technology is the typical feature of the 6G network.On the one hand, AI injects new vitality into the development of the 6G network, which can effectively use the data generated by the historical operation of the network.It enables the network to be self-maintained and selfoptimized, and accelerates the process of network intelligence.On the other hand, the rich scenarios and IoT devices of the 6G network provide a large number of application fields and massive data for AI.These can enable the better deployment of AI, fully demonstrate the performance advantages of AI, and provide high-quality services for users.However, in practice, it is difficult to give full play to the performance advantages of AI due to the difficulty of sample collection, high cost of the collection, and lack of universality which caused by the complexity of the environment.Therefore, academia and industry introduce generative adversarial network (GAN) into the design of wireless networks.The powerful feature learning and feature expression ability of GAN can generate a large number of generated samples, which realizes the expansion of the wireless database.The introduction of GAN can effectively improve the generalization ability of AI models for wireless networks.Owing to the excellent performance of GAN, the generative model represented by GAN has attracted increased attention in the field of wireless networks, and rapidly became the new research hotspot of 6G networks.Firstly, the principle of GAN and its different versions of improved derived models were summarized.Then, the framework, advantages and disadvantages of each model were analyzed.Secondly, the research and application status of these models in wireless networks were reviewed.Finally, the research trends of GAN were proposed for the 6G network requirements, which provided some valuable exploration for future research.

Transmission optimization scheme of aerial intelligent reflecting surface-aided massive MIMO systems based on statistical CSI
Lujie MA, Yan LIANG, Fei LI
2024, 8(1):  17-28.  doi:10.11959/j.issn.2096-3750.2024.00002
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The intelligent reflecting surface (IRS) is considered a core technology of next-generation mobile communication.It has significant advantages in enhancing network coverage, spectrum efficiency, energy efficiency and deployment cost.The aerial intelligent reflecting surface (AIRS), which combines the high mobility of the air platform and the highquality link characteristics provided by the intelligent reflecting surface, can effectively assist the transmission from the base station to the users in complex communication scenarios and enhance the network coverage.A joint optimization problem of the base station beamforming, AIRS deployment location and phase shift design for the AIRS was studied for AIRS assisted multi-user massive multiple input multiple output (MIMO) systems.Under the condition of the statistical channel state information (CSI) being known, an optimization scheme of system ergodic sum rate based on block coordinate descent (BCD) was proposed.Firstly, an optimization model was established by jointly optimizing the transmit beamforming at base station, the placement and the phase shift for AIRS.Secondly, the nonconvex optimization problem was decoupled into three subproblems that were easy to deal with by BCD algorithm.Finally, lagrange multiplier method, relaxation variable method and RMSProp gradient descent algorithm were used to solve the subproblems respectively.The simulation results show that the proposed optimization scheme can effectively improve the ergodic sum rate of the system with good convergence properties.

Mode selection and resource optimization for UAV-assisted cellular networks
Daquan FENG, Canjian ZHENG, Xiangqi KONG
2024, 8(1):  29-39.  doi:10.11959/j.issn.2096-3750.2024.00380
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The resource allocation and optimization scheme was studied in a coexistence scenario of unmanned aerial vehicle (UAV) and cellular communication network.To improve spectrum efficiency of the system, UAV users could reuse the cellular spectrum resources to access the network through full duplex or half duplex device-to-device technique.Additionally, a joint access control, mode selection, power control and resource allocation optimization problem was formulated to maximize the overall throughput of the network while ensuring quality of service requirements for both UAV users and ground cellular users.Specifically, the phase 1 method in the convex optimization was adopted for access control and feasibility check, and then the convex and concave procedure (CCCP) iterative algorithm was used to solve the power control problem for feasible UAV user pairs.By using this local optimum value, the original optimization problem can be simplified into a weighted maximization problem.Finally, the Kuhn-Munkres (KM) algorithm was used to match the optimal channel resources and obtain the global optimal throughput value of the system.Numerical results show that the proposed scheme can significantly improve the performance of system.

Multi-data fusionaided indoor localization based on continuous action space deep reinforcement learning
Xuechen CHEN, Jiaxuan YI, Aixiang WANG, Xiaoheng DENG
2024, 8(1):  40-48.  doi:10.11959/j.issn.2096-3750.2024.00358
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Significant attention has been paid to indoor localization using smartphones in both research and industry.However, the accuracy and robustness of localization remain challenging issues, particularly in complex indoor environments.In light of the prevalent incorporation of pedestrian dead reckoning (PDR) devices in contemporary smartphones, an advanced indoor localization fusion method, anchored in the twin delayed deep deterministic policy gradient (TD3) framework, was proposed.In this approach, a seamless integration of Wi-Fi information and PDR data was achieved.The localization process of PDR was modeled as a Markov process, and a comprehensive continuous action space was introduced for the agent.To evaluate the performance of the proposed method, experiments were conducted and this approach was compared with three state-of-the-art deep Q network (DQN) based indoor localization methods.The experimental results demonstrate that the proposed method significantly reduces localization errors and enhances overall localization accuracy.

Design of nodes importance assessment method for complex network based on neighborhood information
Xing LI, Jie ZHAN, Baoquan REN, Siqi ZHU
2024, 8(1):  49-59.  doi:10.11959/j.issn.2096-3750.2024.00335
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Accurate identification of influential nodes in complex networks is crucial for network management and network security.The local centrality method is concise and easy to use, but ignores the topological relationship between neighboring nodes and cannot provide globally optimal results.A node importance assessment method was proposed to correlate the node edge relationship and topology, which firstly applied the H-index and information entropy to assess the nodes, then combined the structural holes of the nodes with the structural characteristics of the nodes, and took into account the attribute of “bridging” while focusing on the node’s own quality and the amount of information about the neighboring nodes.The algorithm was validated by simulating the propagation process using the SIR model, and the Kendall correlation coefficient, complementary cumulative distribution function and propagation influence were applied to validate the validity and applicability of the method.Comparison of the experimental results on six real network datasets shows that the proposed method is more accurate than the traditional centrality methods in identifying and ordering the key nodes in the network.

Robust transmission algorithm for IRS-assisted NOMA network with hardware impairments and imperfect CSI
Qilie LIU, Jiacheng FANG, Yanan XIN, Qianbin CHEN
2024, 8(1):  60-70.  doi:10.11959/j.issn.2096-3750.2024.00370
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To improve the robustness and reduce the energy consumption of non-orthogonal multiple access (NOMA) networks, based on hardware impairments (HWI) of transceiver and non-perfect channel state information (CSI), an intelligent reflecting surface (IRS) assisted transmission power minimization algorithm for NOMA networks was proposed.The joint optimization problem of active beam assignment at the base station and passive beam assignment at the IRS was modeled based on HWI and non-perfect CSI.The system considered the user quality of service (QoS) constraint, the serial interference cancellation constraint and the reflection phase shift constraint of the IRS.To solve this nonconvex optimization problem, the QoS constraints were firstly transformed using linear approximation and S-Procedure methods.Then the optimization problem was decomposed into two subproblems.The active beam assignment subproblem was solved using the successive convex approximation (SCA) method.The passive beam assignment subproblem was solved using the penalized convex-concave process algorithm.Finally, the final solution was obtained by iterating the subproblems alternately using alternating optimization.The simulation results show that the proposed algorithm reduces 17.05% compared to the or thogonal multiple access robust algorithm in terms of transmitted power.In terms of system robustness, the proposed algorithm improves by 20.69% and 31.14% compared to the HWI robust algorithm and the CSI robust algorithm, respectively.

Age of information-oriented sampling and power control in vehicular status update networks
Jianhua ZENG, Chongtao GUO, Cheng GUO
2024, 8(1):  71-83.  doi:10.11959/j.issn.2096-3750.2024.00376
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In a vehicular status update network based on broadcast communication, a D/Geo/1/1 queuing mechanism with minimum timestamp priority was adopted to transmit data packets.The queuing theory was used to analyze the age-ofinformation (AoI) outage probability of the receivers and the average transmit power of the transmitter.Based on the monotonicity of the AoI outage probability with respect to packet sampling rate and transmit power, an iterative algorithm for jointly optimizing sampling rate and transmit power was proposed to minimize the maximum AoI outage probability of all receivers under power constraint, which fairly improved information freshness of all receivers under sampling and power control.Simulation results verify the accuracy of theoretical analysis and the efficiency of the algorithm.

Edge server deployment decision based on improved NSGA-Ⅱ in the Internet of vehicles edge computing scenario
Sifeng ZHU, Yu WANG, Hao CHEN, Hai ZHU, Zhengyi CHAI, Chengrui YANG
2024, 8(1):  84-97.  doi:10.11959/j.issn.2096-3750.2024.00382
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In the context of the Internet of vehicles, the placement and deployment number of edge servers directly affect the efficiency of edge computing.Due to the high cost of deploying a large edge server on a macro base station and a base station, it can be complemented by deploying a small edge server on a micro base station, and the cost reduction needs to be optimized by optimizing the placement of large edge servers.In order to minimize the deployment cost and service delay of the edge server, and maximize the operator’s revenue and server load balance, the edge server placement problem combined with the vehicle networking user application service was modeled as a multi-objective optimization problem and a placement scheme based on improved NSGA-Ⅱ algorithm was proposed.The experimental results show that the proposed scheme can reduce the deployment cost of edge servers by about 44%, the latency by about 14.2%, and improve the revenue of operators by 24.2%, which has good application value.

Evaluation and optimization of carbon emission for federal edge intelligence network
Peng ZHANG, Yong XIAO, Jiwei HU, Liang LIAO, Jianxin LYU, Zegang BAI
2024, 8(1):  98-110.  doi:10.11959/j.issn.2096-3750.2024.00375
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In recent years, the continuous evolution of communication technology has led to a significant increase in energy consumption.With the widespread application and deep deployment of artificial intelligence (AI) technology and algorithms in telecommunication networks, the network architecture and technological evolution of network intelligent will pose even more severe challenges to the energy efficiency and emission reduction of future 6G.Federated edge intelligence (FEI), based on edge computing and distributed federated machine learning, has been widely acknowledged as one of the key pathway for implementing network native intelligence.However, evaluating and optimizing the comprehensive carbon emissions of federated edge intelligence networks remains a significant challenge.To address this issue, a framework and a method for assessing the carbon emissions of federated edge intelligence networks were proposed.Subsequently, three carbon emission optimization schemes for FEI networks were presented, including dynamic energy trading (DET), dynamic task allocation (DTA), and dynamic energy trading and task allocation (DETA).Finally, by utilizing a simulation network built on real hardware and employing real-world carbon intensity datasets, FEI networks lifecycle carbon emission experiments were conducted.The experimental results demonstrate that all three optimization schemes significantly reduce the carbon emissions of FEI networks under different scenarios and constraints.This provides a basis for the sustainable development of next-generation intelligent communication networks and the realization of low-carbon 6G networks.

Research on multi-user identity recognition based on Wi-Fi sensing
Zhongcheng WEI, Wei CHEN, Yanhu DONG, Bin LIAN, Wei WANG, Jijun ZHAO
2024, 8(1):  111-121.  doi:10.11959/j.issn.2096-3750.2024.00381
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With the advancement of wireless sensing technology, research on Wi-Fi-based identity recognition has garnered significant attention in fields such as human-computer interaction and home security.While identity recognition based on Wi-Fi signals has achieved initial success, it is currently primarily suitable for scenarios involving individual user behavior.Identity recognition for multiple users in concurrent behavior scenarios still faces a series of challenges, including issues related to mutual interference between users and poor model robustness.Therefore, a Wiblack system for recognizing multiple user identities in a concurrent distribution behavior scenario was proposed.The core idea was to train a multi-branch deep neural network (Wiblack-Net) to extract unique features for each individual user.Firstly, the common features among multiple users were extracted using the backbone network.Then, a binary classifier was assigned to each user to determine the presence of the target user within a given group, thereby achieving identity recognition for multiple users based on concurrent behavior.In addition, experiments comparing Wiblack with several independent binary classification models and a single multiclassification model were conducted to analyze operational efficiency.System performance experimental results demonstrate that when simultaneously identifying the identities of three users, Wibalck achieves an average accuracy of 92.97%, an average precision of 93.71%, an average recall of 93.24%, and an average F1 score of 92.43%.

Preamble retransmission assisted control-based mMTC dynamic random access
Bin SHEN, Yan ZHANG, Changmiao LI, Yu ZENG
2024, 8(1):  122-135.  doi:10.11959/j.issn.2096-3750.2024.00377
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To address the issue of severe network congestion in the scenario of massive machine-type communications (mMTC), where machine-type communication devices (MTCD) employing traditional random access schemes often encountered challenges leading to a large number of MTCD failing to access the network successfully, a novel approach called preamble retransmission-based dynamic access class barring (PRT-ACB) was proposed.By utilizing the number of MTCD preamble retransmissions, the MTCD attempting to initiate access in each random access opportunity (RAO) were categorized into different sets of high and low priority.In conjunction with an estimation model for the number of payloads in each RAO, high and low-priority limiting factors and available preamble pools were dynamically adjusted based on the access load in each RAO.This allowed more MTCD to successfully access the network before reaching the maximum number of preamble transfers.Simulation results have demonstrated that the proposed scheme effectively enhances the MTCD successful access rate and reduces the time delay required for MTCD to access the network.The proposed scheme can serve as a solution to alleviate the congestion caused by a massive influx of communication devices attempting simultaneous network access.

Joint beamforming optimization algorithm for secure cognitive radio based on STARS
Chenchi WEN, Jiakuo ZUO, Nan BAO, Pengfei ZHAO
2024, 8(1):  136-146.  doi:10.11959/j.issn.2096-3750.2024.00347
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Secure cognitive radio (SCR) system based on reconfigurable intelligent surface (RIS) assumes that secondary user (SU) and primary user (PU) locate on the same side of the base station (BS), which can only cover part of the communication area and limits the deployment flexibility and effectiveness of the RIS.In order to solve the above problem, a new SCR system based on simultaneously transmitting and reflecting surface (STARS) was proposed.In the system, STARS could achieve full coverage of communication area, improve the received signal strength of the SU with the transmission beamforming vector and reduce the interference of the SU to the PU with the reflection beamforming vector, which provided new optimization degree of freedom (DoF) for the design of the SCR system.Considering secrecy rate constraint of the SU, interference power constraint (IPC) of the PU and transmission/reflection parameters constraint of the STARS, BS active beamforming vector and STARS transmission/reflection beamforming vectors were jointly optimized to minimize the BS’s transmit power from the perspective of reducing the total power consumption of the system.The minimization problem is a variable coupling non-convex problem, which is difficult to tackle directly.An alternating optimization (AO) algorithm based on difference-of-convex relaxation (DCR) method and sequential rank-one constraint relaxation (SROCR) method was proposed to jointly design the BS active beamforming vector and STARS transmission/reflection beamforming vectors.Simulation results show that the proposed algorithm has good convergence performance and effectively reduces the interference of SU on PU.Compared with the traditional RIS, random phase, maximum-ratio transmission (MRT) and equal energy splitting (Equal ES) schemes, the BS transmitting power is reduced by 8.3%, 15.4%, 5.9% and 5.3%, respectively.

Compact RFID tag antenna based on square spiral resonator
Libin DAI, Zhimeng XU, Jiade YUAN
2024, 8(1):  147-152.  doi:10.11959/j.issn.2096-3750.2024.00379
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A miniaturized ultra-high frequency (UHF) radio frequency identification (RFID) tag antenna was designed.The antenna was composed of two square spiral resonators shorted inside and outside.By adjusting the edge length of the outer ring spiral resonator and the spacing between the inner and outer ring spiral resonators, the resonant frequency of the proposed tag antenna could be effectively tuned.The simulation results show that the proposed tag antenna has good impedance matching and the frequency band range covers the whole UHF band (840~960 MHz).It has a dimension of 7.60 mm×7.60 mm×0.05 mm, which is 96% smaller than the traditional spiral resonator (SR) antenna.The measure result shows that the proposed tag antenna achieves the maximum reading distance at 910 MHz in 4 W effective isotropic radiated power.The proposed UHF RFID tag antenna has some advantages of small size, wide frequency band, low cost and easy batch fabrication, and is suitable for applications with small size requirements.

Outage performance of multi-RIS-assisted NOMA system with imperfect serial interference cancellation
Jiaqing QIN, Liping LUO, Jing ZHOU
2024, 8(1):  153-160.  doi:10.11959/j.issn.2096-3750.2024.00384
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Considering the practical communication environments, the outage performance and the throughput were investigated for multiple reconfigurable intelligent surfaces (RIS) assisted non-orthogonal multiple access (NOMA) system with imperfect serial interference cancellation (SIC).The channel coefficients of the RIS-assisted NOMA system including the direct and the reflecting paths were approximated by Gamma distribution.An approximate closed-form expressions of outage probability were derived and validated through Monte Carlo simulations.The study investigated the relationship between the outage performance and system parameters, including the impact of imperfect SIC, the number of RIS and the number of reflecting units.The simulation results demonstrate that, compared with the single RIS-assisted NOMA and the traditional NOMA system, the multi-RIS-assisted system achieves a 14.2 dBm gain in signal-to-noise ratio (SNR) for a given outage probability.Thus, employing multiple RISs can improve the outage performance and the system throughput effectively, thereby compensating for the performance degradation caused by imperfect SIC.

2024 Vol.8 No.1
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2021 Vol.5 No.4 No.3 No.2 No.1
2020 Vol.4 No.4 No.3 No.2 No.1
2019 Vol.3 No.4 No.3 No.2 No.1
2018 Vol.2 No.4 No.3 No.2 No.1
2017 Vol.1 No.3 No.2 No.1
Internet of things and pan-healthcares
Jianguo MA,Hengyue JIN
Chinese Journal on Internet of Things. 2018 Vol. 2 (1): 42-55 doi: 10.11959/j.issn.2096-3750.2018.00040
Abstract3829)   HTML85)    PDF (8173KB)(22374)    Knowledge map   
Development trend of IoT industry in China
Yu SUN
Chinese Journal on Internet of Things. 2017 Vol. 1 (3): 1-5 doi: 10.11959/j.issn.2096-3750.2017.00024
Abstract3046)   HTML307)    PDF (903KB)(4083)    Knowledge map   
Technology and application progress on Internet of Things
WU He-quan
Chinese Journal on Internet of Things. 2017 Vol. 1 (1): 1-6 doi: 10.11959/j.issn.2096-3750.2017.00001
Abstract3376)      PDF (673KB)(3834)    Knowledge map   
Space-air-ground integrated networks:review and prospect
Xuemin(Sherman) SHEN,Nan CHENG,Haibo ZHOU,Feng LYU,Wei QUAN,Weisen SHI,Huaqing WU,Conghao ZHOU
Chinese Journal on Internet of Things. 2020 Vol. 4 (3): 3-19 doi: 10.11959/j.issn.2096-3750.2020.00142
Abstract3817)   HTML571)    PDF (4834KB)(3537)    Knowledge map   
Development status and challenges of LEO IoT
Geng-xin ZHANG,Xiao JIE,Zhi-cheng QU
Chinese Journal on Internet of Things. 2017 Vol. 1 (3): 6-9 doi: 10.11959/j.issn.2096-3750.2017.00025
Abstract5971)   HTML156)    PDF (457KB)(3390)    Knowledge map   
Smart Internet of things aided by“terminal-edge-cloud” cooperation
Dapeng WU,Puning ZHANG,Ruyan WANG
Chinese Journal on Internet of Things. 2018 Vol. 2 (3): 21-28 doi: 10.11959/j.issn.2096-3750.2018.00060
Abstract8765)   HTML443)    PDF (6218KB)(3329)    Knowledge map   
Security of the industrial Internet of things and localization of the core technology
Guangnan NI
Chinese Journal on Internet of Things. 2018 Vol. 2 (2): 1-7 doi: 10.11959/j.issn.2096-3750.2018.00046
Abstract1946)   HTML75)    PDF (1165KB)(3041)    Knowledge map   
Space-air-ground integrated vehicular network for immersive driving experience
Zhi-sheng NIU,SHEN Sherman,Qin-yu ZHANG,Yu-liang TANG
Chinese Journal on Internet of Things. 2017 Vol. 1 (2): 17-27 doi: 10.11959/j.issn.2096-3750.2017.00014
Abstract4611)   HTML159)    PDF (4544KB)(2984)    Knowledge map   
On 6G and wide-area IoT
Xiaohu YOU, Hao YIN, Hequan WU
Chinese Journal on Internet of Things. 2020 Vol. 4 (1): 3-11 doi: 10.11959/j.issn.2096-3750.2020.00158
Abstract2410)   HTML639)    PDF (1690KB)(2974)    Knowledge map   
Backscatter communication technology and Internet of Things
WANG Gong-pu, XIONG Ke, LIU Ming, GAO Fei-fei, ZHONG Zhang-dui
Chinese Journal on Internet of Things. 2017 Vol. 1 (1): 67-75 doi: 10.11959/j.issn.2096-3750.2017.00009
Abstract8207)      PDF (1257KB)(2881)    Knowledge map   
Kernel of Internet of Things:Internet of Data
Qi ZHANG,Hao YANG,Q.S.Quek Tony,Shi JIN,Hong-bo ZHU
Chinese Journal on Internet of Things. 2017 Vol. 1 (3): 10-16 doi: 10.11959/j.issn.2096-3750.2017.00026
Abstract2555)   HTML63)    PDF (1057KB)(2797)    Knowledge map   
Research on wireless access technologies for Internet of things
Jianchi ZHU,Bei YANG,Peng CHEN,Xiaoming SHE,Qi BI
Chinese Journal on Internet of Things. 2018 Vol. 2 (2): 73-84 doi: 10.11959/j.issn.2096-3750.2018.00056
Abstract1845)   HTML105)    PDF (2128KB)(2761)    Knowledge map   
Global IoT development status and development proposals of IoT in China
LUO Song, JIA Xue-qin, XU He-yuan, LIU Duo
Chinese Journal on Internet of Things. 2017 Vol. 1 (1): 7-12 doi: 10.11959/j.issn.2096-3750.2017.00002
Abstract2173)      PDF (623KB)(2731)    Knowledge map   
Tramway obstacles detection based on information fusion of MMV radar and machine vision
Guang-yao ZHAI,Rong CHEN,Jian-feng ZHANG,Ji-guang ZHANG,Cheng WU,Yi-ming WANG
Chinese Journal on Internet of Things. 2017 Vol. 1 (2): 76-83 doi: 10.11959/j.issn.2096-3750.2017.00021
Abstract4829)   HTML142)    PDF (1622KB)(2697)    Knowledge map   
Internet of vehicles empowered by edge intelligence
Yan ZHANG,Ke ZHANG,Jiayu CAO
Chinese Journal on Internet of Things. 2018 Vol. 2 (4): 40-48 doi: 10.11959/j.issn.2096-3750.2018.00080
Abstract3147)   HTML162)    PDF (2184KB)(2631)    Knowledge map   
Research progress and trend of big data-driven intelligent transportation system
Chen YU,Lijuan ZHANG,Hai JIN
Chinese Journal on Internet of Things. 2018 Vol. 2 (1): 56-63 doi: 10.11959/j.issn.2096-3750.2018.00041
Abstract2498)   HTML147)    PDF (754KB)(2610)    Knowledge map   
State of the art of industrial network technologies: a review and outlook
ZHANG Hong-ke, CHENG Yu-jun, YANG Dong
Chinese Journal on Internet of Things. 2017 Vol. 1 (1): 13-20 doi: 10.11959/j.issn.2096-3750.2017.00003
Abstract2421)      PDF (2891KB)(2523)    Knowledge map   
The innovation and development strategy of the Internet of Things science and technology industry based on the “3S” mode
Hong-bo ZHU, Hao YIN
Chinese Journal on Internet of Things. 2017 Vol. 1 (2): 1-16 doi: 10.11959/j.issn.2096-3750.2017.00013
Abstract2092)   HTML76)    PDF (1536KB)(2522)    Knowledge map   
Indoor localization system based on multi-information fusion
NIU Jian-wei, QI Zhi-ping, LYU Wei-feng, LI Hui-yong, SHENG Hao
Chinese Journal on Internet of Things. 2017 Vol. 1 (1): 55-66 doi: 10.11959/j.issn.2096-3750.2017.00008
Abstract3468)      PDF (1788KB)(2493)    Knowledge map   
Application and development of Internet of things in medical service
Zhibiao WANG, Peng RAN, Qiao CHEN
Chinese Journal on Internet of Things. 2018 Vol. 2 (3): 1-10 doi: 10.11959/j.issn.2096-3750.2018.00058
Abstract3852)   HTML367)    PDF (4926KB)(2359)    Knowledge map   
Comprehensive sensing system of new smart city
Jing YANG,Zuwei ZHANG,Daoyuan YAO,Yang HU,Junjiang QIAN,Zhe ZHOU,Xubo HU,Yupeng YUAN,Xiaofei LI
Chinese Journal on Internet of Things. 2018 Vol. 2 (3): 91-97
doi: 10.11959/j.issn.2096-3750.2018.00068
Abstract( 10762 )   HTML PDF (5806KB) (2136 Knowledge map   
Smart Internet of things aided by“terminal-edge-cloud” cooperation
Dapeng WU,Puning ZHANG,Ruyan WANG
Chinese Journal on Internet of Things. 2018 Vol. 2 (3): 21-28
doi: 10.11959/j.issn.2096-3750.2018.00060
Abstract( 8765 )   HTML PDF (6218KB) (3329 Knowledge map   
Backscatter communication technology and Internet of Things
WANG Gong-pu, XIONG Ke, LIU Ming, GAO Fei-fei, ZHONG Zhang-dui
Chinese Journal on Internet of Things. 2017 Vol. 1 (1): 67-75
doi: 10.11959/j.issn.2096-3750.2017.00009
Abstract( 8207 )   PDF (1257KB) (2881 Knowledge map   
Development status and challenges of LEO IoT
Geng-xin ZHANG,Xiao JIE,Zhi-cheng QU
Chinese Journal on Internet of Things. 2017 Vol. 1 (3): 6-9
doi: 10.11959/j.issn.2096-3750.2017.00025
Abstract( 5971 )   HTML PDF (457KB) (3390 Knowledge map   
Self-organization networking technology for 5G ultra-dense wireless network
Jiandong LI,Min SHENG,Junyu LIU,Chenxi ZHAO,Yan ZHANG,Hongguang SUN
Chinese Journal on Internet of Things. 2018 Vol. 2 (1): 24-34
doi: 10.11959/j.issn.2096-3750.2018.00038
Abstract( 4872 )   HTML PDF (5751KB) (2327 Knowledge map   

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Quarterly,started in 2017
Cpmpetent Unit:Ministry of Industry and Information Technology of the People's Republic of China
Sponsor:Posts & Telecom Press Co.,Ltd.
Publisher: China InfoCom Media Group
Editor:Editor Board of Chinese Journal on Internet of Things
Editor-in-Chief:YIN Hao
Executive Editor-in-Chief:ZHU Hongbo
Director:LI Caishan
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