A survey of advanced techniques for spectrum sharing in 5G networks
Abstract
Spectrum efficiency is one of the key performance metrics in 5G communication networks. To enhance spectrum efficiency, advanced spectrum sharing techniques are normally used. In this article, we provide a survey of the recent development of advanced techniques for spectrum sharing. In particular, we elaborate cognitive radio, device-todevice communication, in-band full-duplex communication, non-orthogonal multiple access, and Long Term Evolution on unlicensed spectrum. For each technique, we present the basic principle and research methodology of the state of the art. By considering various promising evolutions in 5G networks, we emphasize challenges to deploy each technique. Finally, we discuss the integration issue of multiple spectrum sharing techniques and identify potential challenges.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Recent studies have revealed inherent security weaknesses in blockchain operations, mostly related to 5G systems.
“However, recent studies have revealed inherent security weaknesses in blockchain operations which are mostly related to 5G systems [296].”
From Blockchain for 5G and beyond networks: A state of the art survey (2020) · cites this paper as [296]
Adversaries can exploit the 51% vulnerability to modify transaction ordering, hamper normal mining operations, or initiate double-spending attacks, degrading the blockchain network.
“Seriously, adversaries can exploit this vulnerability to perform attacks, for example, they can modify the ordering of transactions, hamper normal mining operations or initiate double-spending attack, all of which can degrade the blockchain network [296].”
From Blockchain for 5G and beyond networks: A state of the art survey (2020) · cites this paper as [296]
Cites
Andrews, J. G., Buzzi, S., Choi, W., Hanly, S. V., Lozano, A., Soong, A. C. K., & Zhang, J. C. (2014) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2014.2328098 · Cited by 8,106 · see citing works
Application of Non-Orthogonal Multiple Access in LTE and 5G Networks
Ding, Z., Liu, Y., Choi, J., Sun, Q., Elkashlan, M., Chih‐Lin, I., & Poor, H. V. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1500657cm · Cited by 1,960 · see citing works
Bharadia, D., McMilin, E., & Katti, S. R. (2013) · doi:10.1145/2486001.2486033 · Cited by 1,857 · see citing works
Device-to-Device Communication in LTE-Advanced Networks: A Survey
Liu, J., Kato, N., Ma, J., & Kadowaki, N. (2014) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2014.2375934 · Cited by 643 · see citing works
A Survey of In-Band Full-Duplex Transmission: From the Perspective of PHY and MAC Layers
Kim, D., Lee, H., & Hong, D. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2403614 · Cited by 622 · see citing works
Resource allocation for spectrum underlay in cognitive radio networks
Le, L. B., & Hossain, E. (2008) · IEEE Transactions on Wireless Communications · doi:10.1109/t-wc.2008.070890 · Cited by 482 · see citing works
A Survey on Radio Resource Allocation in Cognitive Radio Sensor Networks
Ahmad, A., Ahmad, S. A., Rehmani, M. H., & Hassan, N. U. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2401597 · Cited by 278 · see citing works
Performance Analysis and Optimization in Downlink NOMA Systems With Cooperative Full-Duplex Relaying
Zhang, L., Liu, J., Xiao, M., Wu, G., Liang, Y., & Li, S. (2017) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2017.2724678 · Cited by 274 · see citing works
Kang, X., Zhang, R., Liang, Y., & Garg, H. K. (2011) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2011.110210 · Cited by 218 · see citing works
Efficient Scheduling and Power Allocation for D2D-Assisted Wireless Caching Networks
Zhang, L., Xiao, M., Wu, G., & Li, S. (2016) · IEEE Transactions on Communications · doi:10.1109/tcomm.2016.2552164 · Cited by 128 · see citing works
Advanced spectrum sharing in 5G cognitive heterogeneous networks
Yang, C., Li, J., Guizani, M., Anpalagan, A., & Elkashlan, M. (2016) · IEEE Wireless Communications · doi:10.1109/mwc.2016.7462490 · Cited by 121 · see citing works
Throughput and Fairness Analysis of Wi-Fi and LTE-U in Unlicensed Band
Wang, X., Quek, T. Q. S., Sheng, M., & Li, J. (2016) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2016.2632629 · Cited by 84 · see citing works
Energy-Efficient Cognitive Transmission With Imperfect Spectrum Sensing
Zhang, L., Xiao, M., Wu, G., Li, S., & Liang, Y. (2016) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2016.2520166 · Cited by 61 · see citing works
Proactive Cross-Channel Gain Estimation for Spectrum Sharing in Cognitive Radio
Zhang, L., Xiao, M., Wu, G., Zhao, P. G., Liang, Y., & Li, S. (2016) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2016.2605298 · Cited by 21 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts
You, X., Wang, C., Huang, J., Gao, X., Zhang, Z., Wang, M., Huang, Y., Zhang, C., Jiang, Y., Wang, J., et al. (2020) · Science China Information Sciences · doi:10.1007/s11432-020-2955-6 · Cited by 2,058 · see citing works
A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions
Parvez, I., Rahmati, A., Güvenç, İ., Sarwat, A. I., & Dai, H. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2841349 · Cited by 883 · see citing works
Chen, S., Liang, Y.-C., Sun, S., Kang, S., Cheng, W., & Peng, M. (2020) · IEEE Wireless Communications · doi:10.1109/mwc.001.1900333 · Cited by 768 · see citing works
In-band full-duplex technology: Techniques and systems survey
Kolodziej, K. E., Perry, B. T., & Herd, J. S. (2019) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2019.2896561 · Cited by 640 · see citing works
Blockchain for 5G and beyond networks: A state of the art survey
Nguyen, D. C., Pathirana, P. N., Ding, M., & Seneviratne, A. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2020.102693 · Cited by 412 · see citing works
Cooperative Ambient Backscatter Communications for Green Internet-of-Things
Yang, G., Zhang, Q., & Liang, Y. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2799848 · Cited by 410 · see citing works
6G Visions: Mobile ultra-broadband, super internet-of-things, and artificial intelligence
Zhang, L., Liang, Y.-C., & Niyato, D. (2019) · China Communications · doi:10.23919/jcc.2019.08.001 · Cited by 354 · see citing works
Self-citationFull spectrum sharing in cognitive radio networks toward 5G: a survey
Hu, F., Chen, B., & Zhu, K. (2018) · IEEE Access · doi:10.1109/access.2018.2802450 · Cited by 321 · see citing works
5G Technology: Towards Dynamic Spectrum Sharing Using Cognitive Radio Networks
Ahmad, W. S. H. M. W., Radzi, N. A. M., Samidi, F. S., Ismail, A., Abdullah, F., Jamaludin, M. Z., & Zakaria, M. N. (2020) · IEEE Access · doi:10.1109/access.2020.2966271 · Cited by 310 · see citing works
Deep CM-CNN for Spectrum Sensing in Cognitive Radio
Liu, C., Wang, J., Liu, X., & Liang, Y. (2019) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2019.2933892 · Cited by 281 · see citing works
Open, Programmable, and Virtualized 5G Networks: State-of-the-Art and the Road Ahead
Bonati, L., Polese, M., D’Oro, S., Basagni, S., & Melodia, T. (2020) · Computer Networks · doi:10.1016/j.comnet.2020.107516 · Cited by 257 · see citing works
Backscatter-NOMA: A Symbiotic System of Cellular and Internet-of-Things Networks
Zhang, Q., Zhang, L., Liang, Y., & Kam, P. (2019) · IEEE Access · doi:10.1109/access.2019.2897822 · Cited by 238 · see citing works
Spectrum Sharing for Internet of Things: A Survey
Zhang, L., Liang, Y., & Xiao, M. (2018) · IEEE Wireless Communications · doi:10.1109/mwc.2018.1800259 · Cited by 219 · see citing works
Intelligence in IoT-Based 5G Networks: Opportunities and Challenges
Javaid, N., Sher, A., Nasir, H., & Guizani, N. (2018) · IEEE Communications Magazine · doi:10.1109/mcom.2018.1800036 · Cited by 189 · see citing works
Interference Management in 5G and Beyond Network: Requirements, Challenges and Future Directions
Siddiqui, M. U. A., Qamar, F., Ahmed, F., Nguyễn, Q. N., & Hassan, R. B. (2021) · IEEE Access · doi:10.1109/access.2021.3073543 · Cited by 176 · see citing works
Resource Allocation for Wireless-Powered IoT Networks With Short Packet Communication
Chen, J., Zhang, L., Liang, Y., Kang, X., & Zhang, R. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2893335 · Cited by 165 · see citing works
A survey of 5G network systems: challenges and machine learning approaches
Fourati, H., Mâaloul, R., & Fourati, L. C. (2020) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-020-01178-4 · Cited by 166 · see citing works
Zhang, L., Tan, J., Liang, Y., Feng, G., & Niyato, D. T. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2912754 · Cited by 151 · see citing works
Constellation Learning-Based Signal Detection for Ambient Backscatter Communication Systems
Zhang, Q., Guo, H., Liang, Y., & Yuan, X. (2018) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2018.2872382 · Cited by 146 · see citing works
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 · see citing works
Deep Reinforcement Learning for Joint Channel Selection and Power Control in D2D Networks
Tan, J., Liang, Y., Zhang, L., & Feng, G. (2020) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2020.3032991 · Cited by 137 · see citing works
New Radio Beam-Based Access to Unlicensed Spectrum: Design Challenges and Solutions
Lagén, S., Giupponi, L., Goyal, S., Patriciello, N., Bojović, B., Demir, A., & Beluri, M. C. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2949145 · Cited by 132 · see citing works
Colosseum: Large-Scale Wireless Experimentation Through Hardware-in-the-Loop Network Emulation
Bonati, L., Johari, P., Polese, M., D’Oro, S., Mohanti, S., Tehrani-Moayyed, M., Villa, D., Shrivastava, S., Tassie, C., Yoder, K., et al. (2021) · IEEE International Symposium on Dynamic Spectrum Access Networks · doi:10.1109/dyspan53946.2021.9677430 · Cited by 125 · see citing works
Qamar, F., Siddiqui, M. U. A., Hindia, M. N., Hassan, R. B., & Nguyễn, Q. N. (2020) · Electronics · doi:10.3390/electronics9091416 · Cited by 123 · see citing works
A Novel IoT Architecture based on 5G-IoT and Next Generation Technologies
Rahimi, H., Zibaeenejad, A., & Safavi, A. (2018) · IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) · doi:10.1109/iemcon.2018.8614777 · Cited by 116 · see citing works
Yang, G., Yuan, D., Liang, Y., Zhang, R., & Leung, V. C. M. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2872515 · Cited by 114 · see citing works
Sufyan, A., Khan, K. B., Khashan, O. A., Mir, T., & Mir, U. (2023) · Electronics · doi:10.3390/electronics12102200 · Cited by 109 · see citing works
Empowering the 6G Cellular Architecture With Open RAN
Polese, M., Döhler, M., Dressler, F., Erol‐Kantarci, M., Jana, R., Knopp, R., & Melodia, T. (2023) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2023.3334610 · Cited by 112 · see citing works
Tanveer, J., Haider, A., Ali, R., & Kim, A. (2022) · Applied Sciences · doi:10.3390/app12010426 · Cited by 106 · see citing works
Bariah, L., Muhaidat, S., & Al‐Dweik, A. (2019) · IEEE Transactions on Communications · doi:10.1109/tcomm.2019.2921360 · Cited by 94 · see citing works
Luo, L., Li, Q., & Cheng, J. (2020) · IEEE Transactions on Communications · doi:10.1109/tcomm.2020.2992471 · Cited by 91 · see citing works
Zhang, L., & Liang, Y. (2018) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2871259 · Cited by 90 · see citing works
Performance Analysis of NOMA-Based Underlay Cognitive Radio Networks With Partial Relay Selection
Aswathi, V., & Babu, A. V. (2021) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2021.3071338 · Cited by 77 · see citing works
QoS-Aware User Association and Resource Allocation in LAA-LTE/WiFi Coexistence Systems
Tan, J., Xiao, S., Han, S., Liang, Y., & Leung, V. C. M. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2904257 · Cited by 76 · see citing works
DeepSense: Fast Wideband Spectrum Sensing Through Real-Time In-the-Loop Deep Learning
Uvaydov, D., D’Oro, S., Restuccia, F., & Melodia, T. (2021) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom42981.2021.9488764 · Cited by 75 · see citing works
Deep Reinforcement Learning for User Association and Resource Allocation in Heterogeneous Networks
Zhao, N., Liang, Y., Niyato, D. T., Pei, Y., & Jiang, Y. (2018) · Globecom · doi:10.1109/glocom.2018.8647611 · Cited by 74 · see citing works
Deep Reinforcement Learning for Multi-Agent Power Control in Heterogeneous Networks
Zhang, L., & Liang, Y. (2020) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2020.3043009 · Cited by 73 · see citing works
Multiple access schemes for Cognitive Radio networks: A survey
Kumar, A., & Kumar, K. (2019) · Physical Communication · doi:10.1016/j.phycom.2019.100953 · Cited by 68 · see citing works
Slamnik–Kriještorac, N., Kremo, H., Ruffini, M., & Márquez-Barja, J. M. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3003818 · Cited by 66 · see citing works
Interference Challenges and Management in B5G Network Design: A Comprehensive Review
Alzubaidi, O. T. H., Hindia, M. N., Dimyati, K., Noordin, K. A., Wahab, A. N. A., Qamar, F., & Hassan, R. B. (2022) · Electronics · doi:10.3390/electronics11182842 · Cited by 65 · see citing works
A perspective on 6G: Requirement, technology, enablers, challenges and future road map
Ray, P. P. (2021) · Journal of Systems Architecture · doi:10.1016/j.sysarc.2021.102180 · Cited by 60 · see citing works
Tan, J., Zhang, L., Liang, Y., & Niyato, D. T. (2020) · IEEE Transactions on Communications · doi:10.1109/tcomm.2020.2971212 · Cited by 58 · see citing works
Unveiling the Potential of NOMA: A Journey to Next-Generation Multiple Access
Ahmed, A., Wang, X., Hawbani, A., Yuan, W., Tabassum, H., Liu, Y., Qaisar, M. U. F., Ding, Z., Al‐Dhahir, N., Nallanathan, A., et al. (2024) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2024.3521647 · Cited by 56 · see citing works
Robust Modulation Classification under Uncertain Noise Condition Using Recurrent Neural Network
Hu, S., Pei, Y., Liang, P. P., & Liang, Y. (2018) · Globecom · doi:10.1109/glocom.2018.8647582 · Cited by 56 · see citing works
An, Z., Zhang, T., Shen, M., de Carvalho, E., Ma, B., Yi, C., & Song, T. (2022) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2022.3164880 · Cited by 54 · see citing works
Optimal Resource Allocation for Multicarrier NOMA in Short Packet Communications
Chen, J., Zhang, L., Liang, Y., & Ma, S. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2960506 · Cited by 51 · see citing works
Kong, D. H., Kil, Y.-S., & Kim, S. (2022) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2022.3158402 · Cited by 51 · see citing works
Modulation-Constrained Clustering Approach to Blind Modulation Classification for MIMO Systems
Tian, J., Pei, Y., Huang, Y., & Liang, Y. (2018) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2018.2879370 · Cited by 50 · see citing works
Pietra-Ricci Index Detector for Centralized Data Fusion Cooperative Spectrum Sensing
Guimarães, D. A. (2020) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2020.3009440 · Cited by 51 · see citing works
Maximum Eigenvalue-Based Goodness-of-Fit Detection for Spectrum Sensing in Cognitive Radio
Liu, C., Wang, J., Liu, X., & Liang, Y. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2923648 · Cited by 50 · see citing works
Learning Driven NOMA Assisted Vehicular Edge Computing via Underlay Spectrum Sharing
Qian, L., Wu, Y., Yu, N., Jiang, F., Zhou, H., & Quek, T. Q. S. (2021) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2021.3049862 · Cited by 50 · see citing works
Multi-Agent Reinforcement Learning-Based Distributed Dynamic Spectrum Access
Hasan, H., Singh, K. K., Biswas, S., & Li, C. (2021) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2021.3120996 · Cited by 49 · see citing works
Coexistence and Spectrum Sharing Above 100 GHz
Polese, M., Cantos-Roman, X., Singh, A., Marcus, M. J., Maccarone, T. J., Melodia, T., & Jornet, J. M. (2023) · Proceedings of the IEEE · doi:10.1109/jproc.2023.3286172 · Cited by 49 · see citing works
Uplink and Downlink NOMA Transmission Using Full-Duplex UAV
Do, D., Nguyen, T. T., Nguyen, T. N., Li, X., & Vozn̆ák, M. (2020) · IEEE Access · doi:10.1109/access.2020.3023163 · Cited by 48 · see citing works
When Machine Learning Meets Spectrum Sharing Security: Methodologies and Challenges
Wang, Q., Sun, H., Hu, R. Q., & Bhuyan, A. (2022) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2022.3146364 · Cited by 47 · see citing works
A Novel Spectrum Sharing Scheme Using Dynamic Long Short-Term Memory With CP-OFDMA in 5G Networks
Jacob, S., Menon, V. G., Joseph, S., Vinoj, P. G., Jolfaei, A., Lukose, J., & Raja, G. (2020) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2020.2970697 · Cited by 47 · see citing works
Asiedu, D. K. P., & Yun, J.-H. (2022) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2022.3228532 · Cited by 46 · see citing works
Joint Spectrum Sensing and Packet Error Rate Optimization in Cognitive IoT
Zhang, L., & Liang, Y. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2907993 · Cited by 40 · see citing works
Hussain, M., & Rasheed, H. (2020) · Wireless Communications and Mobile Computing · doi:10.1155/2020/8845371 · Cited by 39 · see citing works
IRS-Assisted Short Packet Wireless Energy Transfer and Communications
Zhang, B., Wang, K., Yang, K., & Zhang, G. (2021) · IEEE Wireless Communications Letters · doi:10.1109/lwc.2021.3126596 · Cited by 39 · see citing works
Photonic-Enabled RF Canceller for Wideband In-Band Full-Duplex Wireless Systems
Kolodziej, K. E., Yegnanarayanan, S. S., & Perry, B. T. (2019) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2019.2896564 · Cited by 38 · see citing works
5G Implementation: Major Issues and Challenges
Taheribakhsh, M., Jafari, A., Peiro, M. M., & Kazemifard, N. (2020) · International Computer Conference, Computer Society of Iran (CSICC) · doi:10.1109/csicc49403.2020.9050110 · Cited by 38 · see citing works
Full-Duplex Relaying Cognitive Radio Network With Cooperative Nonorthogonal Multiple Access
Wang, X., Jia, M., Guo, Q., Ho, I. W., & Lau, F. C. M. (2019) · IEEE Systems Journal · doi:10.1109/jsyst.2019.2927509 · Cited by 37 · see citing works
A Survey on Technological Trends to Enhance Spectrum-Efficiency in 6G Communications
Iyer, S., Patil, A., Bhairanatti, S., Halagatti, S., & Pandya, R. J. (2022) · Transactions of Indian National Academy of Engineering · doi:10.1007/s41403-022-00372-w · Cited by 37 · see citing works
Tao, J., Chen, J., Xing, J., Fu, S., & Xie, J. (2020) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2020.2991878 · Cited by 36 · see citing works
Energy-Efficient Power Allocation for Millimeter Wave Beamspace MIMO-NOMA Systems
Liu, P., Li, Y., Cheng, W., Zhang, W., & Gao, X. (2019) · IEEE Access · doi:10.1109/access.2019.2935495 · Cited by 35 · see citing works
Cognitive radio based spectrum sharing models for multicasting in 5G cellular networks: A survey
Bhattacharjee, S., Acharya, T., & Bhattacharya, U. (2022) · Computer Networks · doi:10.1016/j.comnet.2022.108870 · Cited by 35 · see citing works
Ghosh, S., De, D., & Deb, P. (2019) · Wireless Personal Communications · doi:10.1007/s11277-019-06179-3 · Cited by 34 · see citing works
Deep CNN for Spectrum Sensing in Cognitive Radio
Liu, C., Liu, X., & Liang, Y. (2019) · International Conference on Communications · doi:10.1109/icc.2019.8761360 · Cited by 33 · see citing works
Novel deep learning framework for wideband spectrum characterization at sub-Nyquist rate
Chandhok, S., Joshi, H., Subramanyam, A. V., & Darak, S. J. (2021) · Wireless Networks · doi:10.1007/s11276-021-02765-1 · Cited by 33 · see citing works
NeutRAN: An Open RAN Neutral Host Architecture for Zero-Touch RAN and Spectrum Sharing
Bonati, L., Polese, M., D’Oro, S., Basagni, S., & Melodia, T. (2023) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2023.3311728 · Cited by 32 · see citing works
Effective Wide Spectrum Sharing Techniques Relying on CR Technology toward 5G: A Survey
Mousa, S. H., Ismail, M. B., Nordin, R., & Abdullah, N. F. (2020) · Journal of Communications · doi:10.12720/jcm.15.2.122-147 · Cited by 32 · see citing works
Energy-Efficient Spectrum Sensing for IoT Devices
Dao, N., Na, W., Tran, A.-T., Nguyen, D. N., & Cho, S. (2020) · IEEE Systems Journal · doi:10.1109/jsyst.2020.2986030 · Cited by 31 · see citing works
Security Enhancement and QoS Provisioning for NOMA-Based Cooperative D2D Networks
Li, Q., Ren, P., & Xu, D. (2019) · IEEE Access · doi:10.1109/access.2019.2939783 · Cited by 30 · see citing works
Deep Learning-Based Wideband Spectrum Sensing: A Low Computational Complexity Approach
Mei, R., & Wang, Z. (2023) · IEEE Communications Letters · doi:10.1109/lcomm.2023.3310715 · Cited by 29 · see citing works
Performance and User Association Optimization for UAV Relay-Assisted mm-Wave Massive MIMO Systems
Belaoura, W., Ghanem, K., Shakir, M. Z., & Hasna, M. O. (2022) · IEEE Access · doi:10.1109/access.2022.3172436 · Cited by 29 · see citing works
On the Performance of Full-Duplex Cooperative NOMA With Non-Linear EH
Ma, L., Li, E., & Yang, Q. (2021) · IEEE Access · doi:10.1109/access.2021.3124090 · Cited by 28 · see citing works
Guest editorial: 6G mobile networks: Emerging technologies and applications
Liang, Y., Niyato, D. T., Larsson, E. G., & Popovski, P. (2020) · China Communications · doi:10.23919/jcc.2020.9205979 · Cited by 31 · see citing works
Approximate Algorithms for 3-D Placement of IBFD Enabled Drone-Mounted Base Stations
Zhang, L., & Ansari, N. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2923143 · Cited by 27 · see citing works
NOMA inspired multicasting in cognitive radio networks
Bhattacharjee, S., Acharya, T., & Bhattacharya, U. (2018) · IET Communications · doi:10.1049/iet-com.2018.5335 · Cited by 26 · see citing works
Nawaz, H., Ahmad, N., & Aslam, J. (2021) · IEEE Transactions on Antennas and Propagation · doi:10.1109/tap.2021.3069570 · Cited by 26 · see citing works
A Survey of Symbiotic Radio: Methodologies, Applications, and Future Directions
Janjua, M. B., & Arslan, H. (2023) · Sensors · doi:10.3390/s23052511 · Cited by 25 · see citing works
Backscatter-NOMA: An Integrated System of Cellular and Internet-of-Things Networks
Zhang, Q., Zhang, L., Liang, Y., & Kam, P. (2019) · International Conference on Communications · doi:10.1109/icc.2019.8761990 · Cited by 25 · see citing works
Future Generation Spectrum Standardization for 5G and Internet of Things
Ali, F., He, Y., Shi, G., Sui, Y., & Yuang, H. (2020) · Journal of Communications · doi:10.12720/jcm.15.3.276-282 · Cited by 25 · see citing works
Deep Reinforcement Learning for the Coexistence of LAA-LTE and WiFi Systems
Tan, J., Zhang, L., Liang, Y., & Niyato, D. T. (2019) · International Conference on Communications · doi:10.1109/icc.2019.8761566 · Cited by 24 · see citing works
Deep Reinforcement Learning for Multi-User Access Control in UAV Networks
Cao, Y., Zhang, L., & Liang, Y. (2019) · International Conference on Communications · doi:10.1109/icc.2019.8761794 · Cited by 24 · see citing works
Adaptive Resource Allocation in SWIPT-Enabled Cognitive IoT Networks
Sun, W., Song, Q., Zhao, J., Guo, L., & Jamalipour, A. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3084472 · Cited by 23 · see citing works
Kim, S.-M., Kim, J., Cha, H., Sim, M. S., Choi, J., Ko, S., Chae, C., & Kim, S. (2020) · IEEE Access · doi:10.1109/access.2020.3015762 · Cited by 22 · see citing works
Auction-based Theory for Dynamic Spectrum Access: a Review
Benedetto, F., Mastroeni, L., & Quaresima, G. (2021) · International Conference on Telecommunications and Signal Processing (TSP) · doi:10.1109/tsp52935.2021.9522600 · Cited by 21 · see citing works
Availability-Aware Channel Allocation for Multi-Cell Cognitive Radio 5G Networks
Halloush, R. D., Salaimeh, R., & Al-Dalqamoni, R. (2022) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2022.3148063 · Cited by 20 · see citing works
Decentralized Caching Schemes and Performance Limits in Two-Layer Networks
Zhang, L., Wang, Z., Xiao, M., Wu, G., Liang, Y., & Li, S. (2018) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2873723 · Cited by 20 · see citing works
Vu, M. N., Tran, N. H., Wijeratne, D. G. S., Pham, K. D., Lee, K., & Nguyen, D. H. N. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2907952 · Cited by 20 · see citing works
Exploiting Gaussian Mixture Model Clustering for Full-Duplex Transceiver Design
Chen, J., Zhang, L., & Liang, Y. (2019) · IEEE Transactions on Communications · doi:10.1109/tcomm.2019.2915225 · Cited by 20 · see citing works
Stitching the Spectrum: Semantic Spectrum Segmentation with Wideband Signal Stitching
Uvaydov, D., Zhang, M., Robinson, C. P., D’Oro, S., Melodia, T., & Restuccia, F. (2024) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom52122.2024.10621332 · Cited by 19 · see citing works
Deep Learning for Cooperative Spectrum Sensing in Cognitive Radio
Chen, Z., Guo, D., & Zhang, J. (2020) · IEEE International Conference on Communication Technology (ICCT) · doi:10.1109/icct50939.2020.9295917 · Cited by 19 · see citing works
Zhai, Q., Bolić, M., Li, Y., Cheng, W., & Liu, C. (2021) · IEEE Access · doi:10.1109/access.2021.3080283 · Cited by 19 · see citing works
On the Outage Performance of Overlay Cognitive STBC-NOMA System With Imperfect SIC
Singh, S., & Bansal, M. (2021) · IEEE Wireless Communications Letters · doi:10.1109/lwc.2021.3109444 · Cited by 19 · see citing works
Dynamic and Collaborative Spectrum Sharing: The SCATTER Approach
Giannoulis, S., Mehari, M. T., Shahid, A., Stojadinovic, D., Claeys, M., Mahfoudhi, F., Liu, W., Seskar, I., Latré, S., Moerman, I., et al. (2019) · IEEE International Symposium on Dynamic Spectrum Access Networks · doi:10.1109/dyspan.2019.8935774 · Cited by 19 · see citing works
Distributed Resource Management in Downlink Cache-Enabled Multi-Cloud Radio Access Networks
Reifert, R.-J., Ahmad, A. A., Dahrouj, H., Chaaban, A., Sezgin, A., Al-Naffouri, T. Y., & Alouini, M. (2022) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2022.3195342 · Cited by 18 · see citing works
The 6G frequency switch that spares scientific services
McNair, J. Y. (2022) · Nature · doi:10.1038/d41586-022-01306-w · Cited by 18 · see citing works
- Authors
- Zhang, L., Xiao, M., Wu, G., Alam, M., Liang, Y.-C., & Li, S.
- Affiliations
- The University of Sydney (AU)
- KTH Royal Institute of Technology (SE)
- University of Electronic Science and Technology of China (CN)
- Instituto de Telecomunicações (PT)
- Venue
- IEEE Wireless Communications
- Published
- 2017-10
- Volume
- 24
- Issue
- 5
- Pages
- 44-51
- ISSN
- 1536-1284 (ISSN-L)
- OpenAlex
- W2766845249
- Cited by
- 321
- References
- 14
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 33 · 2023: 34 · 2022: 44 · 2021: 44 · 2020: 50 · 2019: 59 · 2018: 40
- FWCI
- 27.15
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Wireless Communications (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Cognitive Radio Networks and Spectrum Sensing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced MIMO Systems Optimization
- Physical Sciences › Engineering › Media Technology › Telecommunications and Broadcasting Technologies
- Keywords
- spectrum sharing, 5G, spectral efficiency, cognitive radio, device-to-device communication, in-band full-duplex, non-orthogonal multiple access
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
