Cited by 105Advanced Wireless Communication TechnologiesAdvanced Data and IoT TechnologiesSoftware-Defined Networks and 5G

The DOI matches its Crossref record; 55 of the 58 references it cites were found in a registry or an index.

6G: Connecting Everything by 1000 Times Price Reduction

Open access

Zhang, Shunqing, Xiang, Chenlu, Xu, Shugong·2020·IEEE Open Journal of Vehicular Technology

DOI 10.1109/ojvt.2020.2980003

Open this paper in CoChat — free account Open PDF

Abstract

The commercial deployment of 5G communication networks makes the industry and academia to seriously consider the possible solutions for the next generation. Although the conventional approach indicates that 6G vision and requirements can be figured out by simply multiplying a certain amount of magnitude on top of the previous generations, we argue in this article that 1000 times price reduction from the customer's view point is the key to success. Guided by this vision, we categorize the current candidate technologies in a well organized manner and select AI-assisted intelligent communications as an example to elaborate the drive-force behind. Although it is impossible to identify every detail of 6G during the current time frame, we believe this article will help to eliminate the technical uncertainties and aggregate the efforts towards key breakthrough innovations for 6G.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1109/ojvt.2020.2980003

Cites

55 of 55 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225
Enhanced Deep Residual Networks for Single Image Super-Resolution
Lim, B. O., Son, S., Kim, H., Nah, S., & Lee, K. M. (2017) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2017.151 · Cited by 8,117
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
Kim, J., Lee, J. K., & Lee, K. M. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.182 · Cited by 7,870 · cited 2×
“To further improve the channel matrix recovery NMSE, deep neural networks based technologies, such as the super-resolution convolutional neural network (SRCNN) [41], the very deep super-resolution network (VDSR) [42] and enhanced deep super-resolution (EDSR) [43] have been applied into channel state interpolation task…”
Method
Image Super-Resolution Via Sparse Representation
Yang, J., Wright, J. N., Huang, T. S., & Ma, Y. (2010) · IEEE Transactions on Image Processing · doi:10.1109/tip.2010.2050625 · Cited by 5,241
A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems
Saad, W., Bennis, M., & Chen, M. (2020) · IEEE Network · doi:10.1109/mnet.001.1900287 · Cited by 4,985
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication
Huang, C., Zappone, A., Alexandropoulos, G. C., Debbah, M. A., & Yuen, C. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2922609 · Cited by 3,774
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., et al. (2018) · Science · doi:10.1126/science.aar6404 · Cited by 3,562 · cited 1×
“deep reinforcement learning [24], has demonstrated their potential to deal with huge scale optimization problems, such as playing chess or Go games, and the famous AlphaZero can beat top Go player even without the prior human experts’ knowledge [25].”
Background
6G Wireless Networks: Vision, Requirements, Architecture, and Key Technologies
Zhang, Z., Xiao, Y., Ma, Z., Xiao, M., Ding, Z., Lei, X., Karagiannidis, G. K., & Fan, P. (2019) · IEEE Vehicular Technology Magazine · doi:10.1109/mvt.2019.2921208 · Cited by 2,575
Example-based super-resolution
Freeman, W. T., Jones, T. R., & Pasztor, E. C. (2002) · IEEE Computer Graphics and Applications · doi:10.1109/38.988747 · Cited by 2,497
The Roadmap to 6G: AI Empowered Wireless Networks
Letaief, K. B., Chen, W., Shi, Y., Zhang, J., & Zhang, Y.-J. A. (2019) · IEEE Communications Magazine · doi:10.1109/mcom.2019.1900271 · Cited by 2,207

Show all 58 references

Research works printed but not linked: 3

saad, 0, A vision of 6G wireless systems: Applications, trends, technologies, and open research problems, IEEE Netw
10.1109/MCOM.2019.1900271 · DOI · Paper page
shi, 0, Real-time single image and video super-resolution using an efficient bub-pixel convolutional neural network, Proc IEEE Conf Comput Vision Pattern Recognit, 1874

Sorted by citations

6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions
Chowdhury, M. Z., Shahjalal, M. A., Ahmed, S., & Jang, Y. M. (2020) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2020.3010270 · Cited by 1,925
The Road Towards 6G: A Comprehensive Survey
Jiang, W., Han, B., Habibi, M. A., & Schotten, H. D. (2021) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2021.3057679 · Cited by 1,757
6G Wireless Communications Networks: A Comprehensive Survey
Alsabah, M. Q., Naser, M. A., Mahmmod, B. M., Abdulhussain, S. H., Eissa, M. R., Al-Baidhani, A., Noordin, N. K., Sait, S. M., Al-Utaibi, K. A., & Hashim, F. (2021) · IEEE Access · doi:10.1109/access.2021.3124812 · Cited by 622
A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks
Bariah, L., Mohjazi, L., Muhaidat, S., Sofotasios, P. C., Kurt, G. K., Yanıkömeroğlu, H., & Dobre, O. A. (2020) · IEEE Access · doi:10.1109/access.2020.3019590 · Cited by 356
6G: A survey on technologies, scenarios, challenges, and the related issues
Lu, Y., & Zheng, X. (2020) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2020.100158 · Cited by 360
6G Ecosystem: Current Status and Future Perspective
Bhat, J. R., & AlQahtani, S. A. (2021) · IEEE Access · doi:10.1109/access.2021.3054833 · Cited by 293
Survey on Aerial Radio Access Networks: Toward a Comprehensive 6G Access Infrastructure
Dao, N., Pham, Q., Tu, N. H., Thanh, T. T., Bao, V. N. Q., Lakew, D. S., & Cho, S. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3059644 · Cited by 263
6G Massive Radio Access Networks: Key Applications, Requirements and Challenges
Lee, Y. L., Qin, D., Wang, L., & Sim, G. H. (2020) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2020.3044569 · Cited by 194
6G Communication Technology: A Vision on Intelligent Healthcare
Nayak, S., & Patgiri, R. (2021) · Studies in Computational Intelligence · doi:10.1007/978-981-15-9735-0_1 · Cited by 143
Review Paper on Hardware of Reconfigurable Intelligent Surfaces
Rana, B., Cho, S., & Hong, I. (2023) · IEEE Access · doi:10.1109/access.2023.3261547 · Cited by 145
Spectrum Options and Allocations for 6G: A Regulatory and Standardization Review
Alsaedi, W. K., Ahmadi, H., Khan, Z., & Grace, D. (2023) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2023.3301630 · Cited by 147
Vehicular intelligence in 6G: Networking, communications, and computing
Guo, H., Zhou, X., Liu, J., & Zhang, Y. (2021) · Vehicular Communications · doi:10.1016/j.vehcom.2021.100399 · Cited by 125
Non-Coherent and Backscatter Communications: Enabling Ultra-Massive Connectivity in 6G Wireless Networks
Nawaz, S. J., Sharma, S. K., Mansoor, B., Patwary, M., & Khan, N. M. (2021) · IEEE Access · doi:10.1109/access.2021.3061499 · Cited by 112
The 6G Ecosystem as Support for IoE and Private Networks: Vision, Requirements, and Challenges
Serôdio, C., Cunha, J., Candela, G., Rodríguez, S., Sousa, X. R., & Branco, F. (2023) · Future Internet · doi:10.3390/fi15110348 · Cited by 111
Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting
Jaafar, W., Naser, S. A., Muhaidat, S., Sofotasios, P. C., & Yanıkömeroğlu, H. (2020) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2020.3032844 · Cited by 86
Key Enabling Technologies for 6G: The Role of UAVs, Terahertz Communication, and Intelligent Reconfigurable Surfaces in Shaping the Future of Wireless Networks
Othman, W. M., Ateya, A. A., NASR, M. E. M., Muthanna, A., ELAffendi, M. A., Koucheryavy, A., & Hamdi, A. A. (2025) · Journal of Sensor and Actuator Networks · doi:10.3390/jsan14020030 · Cited by 86
Shift to 6G: Exploration on trends, vision, requirements, technologies, research, and standardization efforts
Dhinesh Kumar, R., & Chavhan, S. (2022) · Sustainable Energy Technologies and Assessments · doi:10.1016/j.seta.2022.102666 · Cited by 76
A Survey on Handover Optimization in Beyond 5G Mobile Networks: Challenges and Solutions
Alraih, S., Nordin, R., Abu-Samah, A., Shayea, I. A. M., & Abdullah, N. F. (2023) · IEEE Access · doi:10.1109/access.2023.3284905 · Cited by 73
Future outlook on 6G technology for renewable energy sources (RES)
Yap, K. Y., Chin, H. H., & Klemeš, J. J. (2022) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2022.112722 · Cited by 70
A Survey for Possible Technologies of Micro/Nanomachines Used for Molecular Communication Within 6G Application Scenarios
Kong, L., Huang, L., Lin, L., Zheng, Z., Li, Y., Wang, Q., & Liu, G. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3255412 · Cited by 61
AI-Enabled Framework for Fog Computing Driven E-Healthcare Applications
Sodhro, A. H., & Zahid, N. (2021) · Sensors · doi:10.3390/s21238039 · Cited by 57
A Vision on 6G-Enabled NIB: Requirements, Technologies, Deployments, and Prospects
Ray, P. P., Kumar, N., & Guizani, M. (2021) · IEEE Wireless Communications · doi:10.1109/mwc.001.2000384 · Cited by 54
DRL‐Based Intelligent Resource Allocation for Diverse QoS in 5G and toward 6G Vehicular Networks: A Comprehensive Survey
Nguyen, H. T., Nguyễn, M. T., Do, H. T., Hua, H. T., & Nguyen, C. V. (2021) · Wireless Communications and Mobile Computing · doi:10.1155/2021/5051328 · Cited by 56
Towards Enhanced Mobile Broadband Communications: A Tutorial on Enabling Technologies, Design Considerations, and Prospects of 5G and beyond Fixed Wireless Access Networks
Alimi, I. A., Patel, R. K., Muga, N. J., Pinto, A. N., Teixeira, A., & Monteiro, P. P. (2021) · Applied Sciences · doi:10.3390/app112110427 · Cited by 52
A CNN-LSTM-Based Fusion Separation Deep Neural Network for 6G Ultra-Massive MIMO Hybrid Beamforming
Murshed, R. U., Ashraf, Z. B., Hridhon, A. H., Munasinghe, K. S., Jamalipour, A., & Hossain, M. F. (2023) · IEEE Access · doi:10.1109/access.2023.3266355 · Cited by 51
Leveraging AI‐enabled 6G‐driven IoT for sustainable smart cities
Gera, B., Raghuvanshi, Y. S., Rawlley, O., Gupta, S. R., Dua, A., & Sharma, P. (2023) · International Journal of Communication Systems · doi:10.1002/dac.5588 · Cited by 49
Quantum secured 6G technology-based applications in Internet of Everything
Prateek, K., Ojha, N. K., Altaf, F., & Maity, S. (2023) · Telecommunication Systems · doi:10.1007/s11235-022-00979-y · Cited by 45
An Energy-Efficient Power Allocation Scheme for NOMA-Based IoT Sensor Networks in 6G
Raj, R., & Dixit, A. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3153314 · Cited by 44
A Waveform Parameter Assignment Framework for 6G With the Role of Machine Learning
Yazar, A., & Arslan, H. (2020) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2020.2992502 · Cited by 40
Tactile Based Intelligence Touch Technology in IoT Configured WCN in B5G/6G-A Survey
Gupta, M., Jha, R. K., & Jain, S. (2022) · IEEE Access · doi:10.1109/access.2022.3148473 · Cited by 39
Cellular Internet of Things: Use cases, technologies, and future work
Moges, T. H., Lakew, D. S., Nguyen, N. P., Dao, N., & Cho, S. (2023) · Internet of Things · doi:10.1016/j.iot.2023.100910 · Cited by 37
Machine Learning-Based Self-Interference Cancellation for Full-Duplex Radio: Approaches, Open Challenges, and Future Research Directions
Elsayed, M. I., El-Banna, A. A. A., Dobre, O. A., Shiu, W., & Wang, P. (2023) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2023.3331185 · Cited by 37
Policy options for broadband infrastructure strategies: A simulation model for affordable universal broadband in Africa
Oughton, E. J. (2022) · Telematics and Informatics · doi:10.1016/j.tele.2022.101908 · Cited by 36
Exchanging Bandwidth With Aperture Size in Wireless Indoor Localization - Or Why 5G/6G Systems With Antenna Arrays Can Outperform UWB Solutions
Sippel, E., Geiss, J., Bruckner, S., Gröschel, P., Hehn, M., & Vossiek, M. (2021) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2021.3078551 · Cited by 26
Beyond 5G: Exploring key enabling technologies, use cases, and future prospects of 6 G communication
Telagam, N., Kandasamy, N., Manoharan, A. K., Anandhi, P., & Atchudan, R. (2024) · Nano Communication Networks · doi:10.1016/j.nancom.2024.100560 · Cited by 23
AI-Based Vehicular Network toward 6G and IoT: Deep Learning Approaches
Chen, M., Fan, M.-H., & Huang, L. (2021) · ACM Transactions on Management Information Systems · doi:10.1145/3466691 · Cited by 23
6G Wireless Communication Networks
Haque, M. A., Ahmad, S., Abboud, A. J., Hossain, M. A., Kumar, K., Haque, S., Sonal, D., Rahman, M., & Senapathy, M. (2024) · International Journal of Business Data Communications and Networking · doi:10.4018/ijbdcn.339889 · Cited by 22
Reinforcement Learning-Based Mobile AR/VR Multipath Transmission With Streaming Power Spectrum Density Analysis
Xu, C., Qin, J., Zhang, P., Gao, K., & Grieco, L. A. (2021) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2021.3082912 · Cited by 20
Role of 6G Networks: Use Cases and Research Directions
Bajpai, A., & Balodi, A. (2020) · IEEE Bangalore Humanitarian Technology Conference (B-HTC) · doi:10.1109/b-htc50970.2020.9298017 · Cited by 20
Transforming Vehicular Networks: How 6G can Revolutionize Intelligent Transportation?
Anvigh, A. A., Khavan, Y., & Pourghebleh, B. (2024) · Science Engineering and Technology · doi:10.54327/set2024/v4.i1.127 · Cited by 21
6th Generation: Communication, Signal Processing, Advanced Infrastructure, Emerging Technologies and Challenges
Kumar, A., Perveen, S., Singh, S., Kumar, A., Majhi, S., & Das, S. K. (2021) · International Conference on Computing, Communication and Security (ICCCS) · doi:10.1109/icccs51487.2021.9776334 · Cited by 18
Comparison of 4G and 5G Cellular Network Architecture and Proposing of 6G, a new era of AI
Shah, B. M., Murtaza, M., & Raza, M. S. (2020) · International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) · doi:10.1109/citisia50690.2020.9371846 · Cited by 17
The internet-of-vehicle traffic condition system developed by artificial intelligence of things
Wu, H. (2021) · The Journal of Supercomputing · doi:10.1007/s11227-021-03969-0 · Cited by 16
6G for Industry 5.0 and Smart CPS: A Journey from Challenging Hindrance to Opportunistic Future
Basu, D., Ghosh, U., & Datta, R. (2022) · IEEE Silchar Subsection Conference (SILCON) · doi:10.1109/silcon55242.2022.10028927 · Cited by 15
From Standard Policy-Based Zero Trust to Absolute Zero Trust (AZT): A Quantum Leap to Q-Day Security
Raheman, F. (2024) · Journal of Computer and Communications · doi:10.4236/jcc.2024.123016 · Cited by 21
Pricing Powered by Artificial Intelligence: An Assessment Model for the Sustainable Implementation of AI Supported Price Functions
Erdmann, A., Yazdani, M., Iglesias, J. M. M., & Palacios, C. M. (2024) · Informatica · doi:10.15388/24-infor559 · Cited by 15
6G: Enabling the Future of Healthcare Delivery
Karak, A., Chirputkar, A., & Ashok, P. (2024) · IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS) · doi:10.1109/iciteics61368.2024.10625060 · Cited by 10
A Novel Routing Strategy Towards Achieving Ultra-Low End-to-End Latency in 6G Networks
Das, S. R., Sarma, S. S., Khuntia, M., Roy, I., Sinha, K., & Sinha, B. P. (2022) · International journal of Computer Networks & Communications · doi:10.5121/ijcnc.2022.14101 · Cited by 10
Non-Coherent and Backscatter Communications: Enabling Ultra-Massive Connectivity in the Era Beyond 5GPreprint
Nawaz, S. J., Sharma, S. K., Mansoor, B., Patwary, M. N., & Khan, N. M. (2020) · arXiv (Cornell University) · Cited by 10
On the Concept of On-Demand RIS-Assisted 6G Networks: Applications and the Way Forward
Ndjiongue, A. R., Dobre, O. A., & Shin, H. (2025) · IEEE Communications Magazine · doi:10.1109/mcom.001.2400249 · Cited by 9
A Review of the Current Usage of AI/ML for Radio Access Network (RAN)
AlZailaa, A., Corona, J., Teixeira, R., Chi, H. R., Antunes, M., Radwan, A., & Aguiar, R. L. (2025) · IEEE Access · doi:10.1109/access.2025.3586800 · Cited by 9
Blockchain-based distributed operation and incentive solution for P-RAN
Liu, X., Chen, X., Bi, Q., Liang, W. J., Li, J., & Zhang, Z. (2022) · Computer Communications · doi:10.1016/j.comcom.2022.11.008 · Cited by 9
Deep Learning-Based Signal Detection for Rate-Splitting Multiple Access Under Generalized Gaussian Noise
Kowshik, A. K., Raghavendra, A. H., Gurugopinath, S., & Muhaidat, S. (2023) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2023.3238034 · Cited by 9
6G: Envisioning the Key Issues and ChallengesPreprint
Nayak, S., & Patgiri, R. (2020) · arXiv (Cornell University) · Cited by 9
Secrecy Rate Maximization for IRS-Enabled UAV-ISAC Systems via Phase Shifting Adjustment and Resource Allocation
Guo, Y., Jia, X., Xie, M., & Li, Y. (2025) · IEEE Transactions on Green Communications and Networking · doi:10.1109/tgcn.2025.3578453 · Cited by 8
Future 6G communication networks: Typical IoT network topology and Terahertz frequency challenges and research issues
Ndiaye, M., Saley, A. M., Niane, K., & Raimy, A. (2022) · International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET) · doi:10.1109/iraset52964.2022.9744327 · Cited by 8
A Comprehensive Survey on 6G Networks: Key Technologies and Challenges
Patel, A., Shukla, A., & Bhalani, J. K. (2021) · International Conference on Simulation, Automation & Smart Manufacturing (SASM) · doi:10.1109/sasm51857.2021.9841160 · Cited by 7
Miniaturized silicon-based substrate integrated waveguide filter for 6G applications
Wang, F., Lu, Y., Yin, X., Liu, J., Yu, N., & Yang, Y. W. (2023) · Microelectronics Journal · doi:10.1016/j.mejo.2023.105837 · Cited by 7
Intelligent Transportation System Protocol Interoperability Evaluation
Vogt, J., Schotten, H. D., & Wieker, H. (2025) · IEEE Open Journal of Intelligent Transportation Systems · doi:10.1109/ojits.2025.3531549 · Cited by 6
A Partial CSI Estimation Approach for Downlink FDD massive-MIMO System with Different Base Transceiver Station Topologies
Naser, M. A., Alsabah, M. Q., & Taher, M. A. (2021) · Wireless Personal Communications · doi:10.1007/s11277-021-08423-1 · Cited by 6
Synthetizing 6G KPIs for Diverse Future Use Cases: A Comprehensive Review of Emerging Standards, Technologies, and Societal Needs
Ali, S., Abu-Samah, A., Alsharif, M. H., Nordin, R., Saqib, N., Adam, M. S., Techanamurthy, U., Mustafa, M., & Abdullah, N. F. (2026) · Future Internet · doi:10.3390/fi18010063 · Cited by 5
6G Wireless Communication Systems and Its Applications
Swetha, M. S., Muneshwara, M. S., Hegde, A. S. M. M., & Lu, Z. (2023) · Studies in computational intelligence · doi:10.1007/978-981-19-6450-3_25 · Cited by 5
A Complex Network and Evolutionary Game Theory Framework for 6G Function Placement
Scatà, M., Corte, A. L., Marotta, A., Graziosi, F., & Cassioli, D. (2024) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2024.3393848 · Cited by 5
Characterization of Unit Cells of a Reconfigurable Intelligence Surface Integrated with Sensing Capability at the mmWave Frequency Band
Rana, B., Cho, S., & Hong, I. (2024) · Electronics · doi:10.3390/electronics13091689 · Cited by 5
Enhancing flexibility and system performance in 6G and beyond: A user-based numerology and waveform approach
Sayed, M. S., Zakaria, H., & Abdelhady, A. M. (2024) · Digital Communications and Networks · doi:10.1016/j.dcan.2024.10.020 · Cited by 4
Full-Duplex mmWave Radio-Over-Fiber Architecture With Simplified Photonic Frequency Translation
Schrenk, B., & Karinou, F. (2024) · Journal of Lightwave Technology · doi:10.1109/jlt.2024.3386254 · Cited by 4
Navigating the 6G landscape: A systematic review of technology integration, implementation challenges, and strategic solutions
Singh, P., Agarwal, A., & Kumar, P. (2025) · Computer Networks · doi:10.1016/j.comnet.2025.111663 · Cited by 5
A Large-Scale Energy Efficient Time-Domain Pilot Muting Mechanism for Non-Stationary Channels: A Deep Reinforcement Learning Approach
Sun, Y., Ye, X., Tan, H., Zhang, S., Chen, X., & Xu, S. (2023) · IEEE Wireless Communications Letters · doi:10.1109/lwc.2023.3321763 · Cited by 4
Self-citation
A Perspective Toward 6G Connecting Technology
Katiyar, N., Srivastava, J., & Singh, K. P. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-16-8721-1_70 · Cited by 4
Review on 6G communication network technology for sustainable renewable energy system: Implementations, constraints, and recommendations
Rashid, A., Biswas, P., Habib, A. K. M. A., Abadin, A. Z., Ghosh, A., & Motakabber, S. M. A. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.107933 · Cited by 3
Formulating and Supporting a Hypothesis to Address a Catch-22 Situation in 6G Communication Networks
Raheman, F. (2024) · Journal of Information Security · doi:10.4236/jis.2024.153020 · Cited by 5
Applying SDN to Mobile Networks: A NewPerspective for 6G ArchitecturePreprint
Yadav, R., Kamran, R., Jha, P., & Karandikar, A. (2025) · Research Square · doi:10.21203/rs.3.rs-6209238/v1 · Cited by 3
A Survey of AI-Enabled Architectures for Next-Generation Wireless Communication NetworksPreprint
Javed, A. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5508578 · Cited by 3
A concept of future sixth generation wireless networks: 6G
Urošević, U., & Veljović, Z. (2021) · Tehnika · doi:10.5937/tehnika2103335u · Cited by 2
Classification and Recognition of 6G Space-Ground Integrated Network Modulation Modes
Wang, S. (2023) · International Conference on Applied Machine Learning (ICAML) · doi:10.1109/icaml60083.2023.00016 · Cited by 2
Artificial Intelligence and Machine Learning as Pioneers in Advancing 5G/6G Network Capabilities
Syed, Q. S., Hussain, S., & Bashir, I. (2025) · Advances in wireless technologies and telecommunication book series · doi:10.4018/979-8-3693-6725-4.ch009 · Cited by 3
A Model-Data Dual-Driven Resource Allocation Scheme for IREE Oriented 6G Networks
Yu, T., Wang, S., Zhang, S., Chen, X., Xu, Z., Wang, X., Li, J., Liu, J., & Zhang, S. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3577760 · Cited by 2
Self-citation
TSV-based cross-coupled SIW THz bandpass filter with quadrangle components topology
Wang, F., Ke, L., Yin, X., Yu, N., & Yang, Y. W. (2021) · International Conference on Microwave and Millimeter Wave Technology (ICMMT) · doi:10.1109/icmmt52847.2021.9618035 · Cited by 2
A novel energy efficient two‐dimensional pilot muting mechanism for non‐stationary channel fading environment
Sun, Y., Tan, H., Yu, C., Zhang, S., & Chen, X. (2023) · Electronics Letters · doi:10.1049/ell2.12787 · Cited by 1
Self-citation
An experimental information-theoretic framework for cognitive semantic communication: A rate–distortion–relevance study over RIS-enabled wireless links
Yumuşak, S. (2025) · Physical Communication · doi:10.1016/j.phycom.2025.102879 · Cited by 1
Generation rate control with AoI under traffic hole problem in vehicular networks
Gu, J., Song, C., Liao, S., Li, H., Liu, M., & Wu, J. (2022) · ITU Journal on Future and Evolving Technologies · doi:10.52953/difr6805 · Cited by 1
Utilization of Beam Signatures Supporting High User Mobility With Extremely Low Feedback Overhead
Park, S., & Sung, W. (2022) · IEEE Access · doi:10.1109/access.2022.3172307 · Cited by 1
Already 6G? Why?
Rhazal, O. E., & Mazri, T. (2021) · International Conference on Networking, Information Systems & Security (NISS) · doi:10.1145/3454127.3456619
Introduction
Thakur, P., & Singh, G. K. (2021) · doi:10.1002/9781119665458.ch1
6G With Smart Healthcare, Haptic Communication
Kousalya, K., Mohana, R. S., Sasipriyaa, N., Prabha, C., & Udhayakumar, T. (2022) · Advances in wireless technologies and telecommunication book series · doi:10.4018/978-1-7998-9636-4.ch013
Bibliography
Ebrahimzadeh, A., & Maier, M. (2020) · Wiley eBooks · doi:10.1002/9781119658054.biblio
TSV-based SIW bandpass filter for W-band mobile communication applications
Wang, F., Peng, Q. Y., Yu, N., & Yang, Y. W. (2022) · IEICE Electronics Express · doi:10.1587/elex.19.20220187
A Scholastic Comprehensive Study on 6G Wireless Communication System
Gudadhe, K. H., Sirskar, W. P., & Gaikwad, S. (2023) · Algorithms for intelligent systems · doi:10.1007/978-981-99-2854-5_32
Future Intelligent Communication with 6G Technology: A Review
Jain, S., Yadav, A. K., Kumar, R., V, Yadav, V., & Singh, D. (2023) · International Journal of Sensors Wireless Communications and Control · doi:10.2174/0122103279270825231023095946
On-Demand (OnD) RIS-Assisted 6G Networks: Concept, Application, and Future DirectionsPreprint
Ndjiongue, A. R., & Dobre, O. A. (2023) · doi:10.36227/techrxiv.24471673.v1
On-Demand (OnD) RIS-Assisted 6G Networks: Concept, Application, and Future DirectionsPreprint
Ndjiongue, A. R., & Dobre, O. A. (2023) · doi:10.36227/techrxiv.24471673
Future Communication Systems: Toward the Intelligent-based Optimization Approaches
Kouhalvandi, L., Alibakhshikenari, M., Matekovits, L., Shayea, I. A. M., & Özoğuz, S. (2023) · International Conference on Wireless Networks and Mobile Communications (WINCOM) · doi:10.1109/wincom59760.2023.10322916
Reviewing the SAE Levels of Driving Automation and Research Gaps to Accelerate the Development of a Quantum-Safe CCAM Infrastructure
Raheman, F., Bhagat, T., & Batalla, A. (2024) · Journal of Transportation Technologies · doi:10.4236/jtts.2024.144027 · Cited by 1
Exploring 6G Research
Kumar, S. S., Balaji, S., Devi, S. N., & Priyadharsini, V. (2024) · Wiley eBooks · doi:10.1002/9781394230686.ch16
Smart Healthcare Innovations Powered by 6G Networks
Ashok, P., Hallur, G. G., & Chirputkar, A. (2025) · Recent Patents on Engineering · doi:10.2174/0118722121360907250209163714
Graph Convolutional Neural Network-based Modeling of Ultra-Scale MIMO Channels in 6G Networks
Chen, J., He, H., & Xu, Z. W. (2025) · Applied Mathematics and Nonlinear Sciences · doi:10.2478/amns-2025-0470
Path to 6G Technological Advances: Assessment and Perspective
Adnan, M. M., Kumar, A. K., Chaturvedi, R., Kaur, A., Бекнозарова, З. Ф., & Manohar, M. (2024) · International Conference on Communication, Computing and Energy Efficient Technologies (I3CEET) · doi:10.1109/i3ceet61722.2024.10993934
Integrating AI into Key Enabling Technologies for 6G Networks: A Review from SDN to Quantum Computing
Hendaoui, M. (2025) · Journal of applied engineering science & technology. · doi:10.69717/jaest.v5.i1.109
Securing 5G-enabled IoT with Blockchain: A Technical Review
Goswami, B., & Choudhury, H. (2025) · SN Computer Science · doi:10.1007/s42979-025-04295-5
IREE Oriented Resource Allocation for 6G networks: A Model-Data Dual-Driven Approach
Wang, S., Yu, T. E., Li, J., Zhang, S., Chen, X. R., Shao, W., Xu, Z. L., Wang, X., Li, J., Liu, J., et al. (2025) · International Conference on Future Communications and Networks (FCN) · doi:10.1109/fcn66513.2025.11296719
Self-citation

Authors: Zhang, S., Xiang, C., & Xu, S.
Affiliations: Shanghai University (CN)
ORCID: Zhang, Shunqing
Xiang, Chenlu
Xu, Shugong
Venue: IEEE Open Journal of Vehicular Technology
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 2020
Volume: 1
Pages: 107-115
ISSN: 2644-1330 (ISSN-L)
DOI: 10.1109/ojvt.2020.2980003
OpenAlex: W3011296336
Cited by: 105
References: 58
Citations by year: 2026: 5 · 2025: 18 · 2024: 14 · 2023: 20 · 2022: 15 · 2021: 22 · 2020: 11
FWCI: 5.84
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/legalcode (vor)
Locations: IEEE Open Journal of Vehicular Technology (publishedVersion, cc-by)
arXiv (Cornell University) (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
arXiv (Cornell University)
Funders: National Natural Science Foundation of China (61701293, 61871262)
National Science and Technology Major Project (2018ZX03001009)
National Key Research and Development Program of China (2017YFE0121400)
Huawei Innovation Research Program
Shanghai Institute for Advanced Communication and Data Science
Topics: Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Data and IoT Technologies
Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
Keywords: 6G, next-generation wireless networks, cost reduction, customer perspective, network requirements, technology categorization

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

6G: Connecting Everything by 1000 Times Price Reduction

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks