Artificial intelligence, big data analytics, and deep learning for 6G communication networks: Challenges, applications, and future directions

Partha Sarathi Mohapatra (1)
(1) AT&T services Inc, Plano Texas, United States, United States

Abstract

The fast development of 6G communication systems has posed serious challenges with management of ultra-density connections, massive traffic, and extremely evolving wireless environments that demand new solutions with the help of Artificial Intelligence, Big Data Analytics, and Deep Learning. The conventional network management techniques cannot be used in supporting AI-native networks, terahertz communication, ultra-massive MIMO or integrated sensing and communication which are presumed to be key technologies of beyond-5G systems. The paper offers a detailed literature review concerning intelligent wireless systems, edge AI, federated learning, and data-driven networking. The review examines new applications, architecture, and technical issues towards integrating machine learning into wireless, digital twin networks, and self-organizing networks into future communication infrastructures. Findings suggest that low latency, high reliability, and energy-efficient communication in the next-generation networks can only be achieved through the use of AI-based optimization, autonomous control of networks, and real-time analytics made possible by the big data analytics. The results also indicate the growing research interest in network automation, smart connectivity and intelligent network management especially in the support of Internet of Everything, immersive services and large-scale cyber-physical systems. Nevertheless, other problems, such as computational complexity, security, privacy, interoperability, and scalability are no longer mere obstacles to implementation. The review believes that the deep learning, AI-driven optimization, and distributed analytics will be at the core of the future wireless systems and that intelligent, autonomous, and adaptive communication architectures will be a research focus of designing the 6G ecosystems.

Full text article

Generated from XML file

References

[1] Basharat S, Khan M, Iqbal M, Hashmi US, Zaidi SA, Robertson I. Exploring reconfigurable intelligent surfaces for 6G: State‐of‐the‐art and the road ahead. IET Communications. 2022 Aug;16(13):1458-74. https://doi.org/10.1049/cmu2.12364

[2] Bhide P, Shetty D, Mikkili S. Review on 6G communication and its architecture, technologies included, challenges, security challenges and requirements, applications, with respect to AI domain. IET Quantum Communication. 2025 Jan;6(1):e12114. https://doi.org/10.1049/qtc2.12114

[3] Du J, Lin T, Jiang C, Yang Q, Bader CF, Han Z. Distributed foundation models for multi-modal learning in 6G wireless networks. IEEE Wireless Communications. 2024 Jun 14;31(3):20-30. https://doi.org/10.1109/MWC.009.2300501

[4] Gururaj HL, Natarajan R, Almujally NA, Flammini F, Krishna S, Gupta SK. Collaborative energy-efficient routing protocol for sustainable communication in 5G/6G wireless sensor networks. IEEE Open Journal of the Communications Society. 2023 Sep 8;4:2050-61. https://doi.org/10.1109/OJCOMS.2023.3312155

[5] Du X, Wang T, Feng Q, Ye C, Tao T, Wang L, Shi Y, Chen M. Multi-agent reinforcement learning for dynamic resource management in 6G in-X subnetworks. IEEE transactions on wireless communications. 2022 Sep 27;22(3):1900-14. https://doi.org/10.1109/TWC.2022.3207918

[6] Hong EK, Lee I, Shim B, Ko YC, Kim SH, Pack S, Lee K, Kim S, Kim JH, Shin Y, Kim Y. 6G R&D vision: Requirements and candidate technologies. Journal of Communications and Networks. 2022 Apr;24(2):232-45. https://doi.org/10.23919/JCN.2022.000015

[7] Iqbal A, Tham ML, Wong YJ, Al-Habashna AA, Wainer G, Zhu YX, Dagiuklas T. Empowering non-terrestrial networks with artificial intelligence: A survey. IEEE Access. 2023 Sep 13;11:100986-1006. https://doi.org/10.1109/ACCESS.2023.3314732

[8] Jha AV, Appasani B, Khan MS, Zeadally S, Katib I. 6G for intelligent transportation systems: standards, technologies, and challenges. Telecommunication Systems. 2024 Jun;86(2):241-68. https://doi.org/10.1007/s11235-024-01126-5

[9] Kamruzzaman MM. Key technologies, applications and trends of internet of things for energy-efficient 6G wireless communication in smart cities. Energies. 2022 Aug 2;15(15):5608. https://doi.org/10.3390/en15155608

[10] Khan S, Khan S, Ali Y, Khalid M, Ullah Z, Mumtaz S. Highly accurate and reliable wireless network slicing in 5th generation networks: a hybrid deep learning approach. Journal of Network and Systems Management. 2022 Apr;30(2):29. https://doi.org/10.1007/s10922-021-09636-2

[11] Li H, Ota K, Dong M. Learning IoV in 6G: Intelligent edge computing for Internet of Vehicles in 6G wireless communications. IEEE Wireless Communications. 2023 Mar 7;30(6):96-101. https://doi.org/10.1109/MWC.017.2200089

[12] Meena P, Pal MB, Jain PK, Pamula R. 6G communication networks: introduction, vision, challenges, and future directions. Wireless Personal Communications. 2022 Jul;125(2):1097-123. https://doi.org/10.1007/s11277-022-09590-5

[13] Liu Y, Deng Y, Nallanathan A, Yuan J. Machine learning for 6G enhanced ultra-reliable and low-latency services. IEEE Wireless Communications. 2023 Apr 18;30(2):48-54. https://doi.org/10.1109/MWC.006.2200407

[14] Ohtsuki T. Machine learning in 6G wireless communications. IEICE Transactions on Communications. 2023 Feb 1;106(2):75-83. https://doi.org/10.1587/transcom.2022CEI0002

[15] Olugbade S, Ojo S, Imoize AL, Isabona J, Alaba MO. A review of artificial intelligence and machine learning for incident detectors in road transport systems. Mathematical and Computational Applications. 2022 Sep 13;27(5):77. https://doi.org/10.3390/mca27050077

[16] Puspitasari AA, An TT, Alsharif MH, Lee BM. Emerging technologies for 6G communication networks: Machine learning approaches. Sensors. 2023 Sep 6;23(18):7709. https://doi.org/10.3390/s23187709

[17] Saeed MM, Saeed RA, Abdelhaq M, Alsaqour R, Hasan MK, Mokhtar RA. Anomaly detection in 6G networks using machine learning methods. Electronics. 2023 Jul 31;12(15):3300. https://doi.org/10.3390/electronics12153300

[18] Kharche S, Kharche J. 6G intelligent healthcare framework: A review on role of technologies, challenges and future directions. Journal of Mobile Multimedia. 2023 May;19(3):603-44. https://doi.org/10.13052/jmm1550-4646.1931

[19] Shafi M, Jha RK, Jain S. 6G: Technology evolution in future wireless networks. IEEE Access. 2024 Apr 4;12:57548-73. https://doi.org/10.1109/ACCESS.2024.3385230

[20] Teimoori Z, Yassine A, Hossain MS. Smart vehicles recommendation system for artificial intelligence-enabled communication. IEEE Transactions on Consumer Electronics. 2024 Jan 30;70(1):3914-25. https://doi.org/10.1109/TCE.2024.3360320

[21] Tera SP, Chinthaginjala R, Pau G, Kim TH. Toward 6G: An overview of the next generation of intelligent network connectivity. IEEE Access. 2024 Dec 26;13:925-61. https://doi.org/10.1109/ACCESS.2024.3523327

[22] Sanjalawe Y, Fraihat S, Abualhaj M, Makhadmeh S, Alzubi E. A review of 6G and AI convergence: Enhancing communication networks with artificial intelligence. IEEE Open Journal of the Communications Society. 2025 Mar 20. https://doi.org/10.1109/OJCOMS.2025.3553302

[23] Shi Y, Lian L, Shi Y, Wang Z, Zhou Y, Fu L, Bai L, Zhang J, Zhang W. Machine learning for large-scale optimization in 6G wireless networks. IEEE Communications Surveys & Tutorials. 2023 Aug 1;25(4):2088-132. https://doi.org/10.1109/COMST.2023.3300664

[24] Shi Y, Zhou Y, Wen D, Wu Y, Jiang C, Letaief KB. Task-oriented communications for 6G: Vision, principles, and technologies. IEEE Wireless Communications. 2023 Jul 13;30(3):78-85. https://doi.org/10.1109/MWC.002.2200468

[25] Liu W, Fu Y, Shi Z, Wang H. When digital twin meets 6G: Concepts, obstacles, and research prospects. IEEE Communications Magazine. 2024 Nov 4;63(3):16-22. https://doi.org/10.1109/MCOM.001.2400202

[26] Sejan MA, Rahman MH, Shin BS, Oh JH, You YH, Song HK. Machine learning for intelligent-reflecting-surface-based wireless communication towards 6G: A review. Sensors. 2022 Jul 20;22(14):5405. https://doi.org/10.3390/s22145405

[27] Singh R, Kaushik A, Shin W, Di Renzo M, Sciancalepore V, Lee D, Sasaki H, Shojaeifard A, Dobre OA. Towards 6G evolution: Three enhancements, three innovations, and three major challenges. IEEE Network. 2025 May 29. https://doi.org/10.1109/MNET.2025.3574717

[28] Zhu X, Liu J, Lu L, Zhang T, Qiu T, Wang C, Liu Y. Enabling intelligent connectivity: A survey of secure ISAC in 6G networks. IEEE Communications Surveys & Tutorials. 2024 Jul 24;27(2):748-81. https://doi.org/10.1109/COMST.2024.3432871

[29] Zhu G, Lyu Z, Jiao X, Liu P, Chen M, Xu J, Cui S, Zhang P. Pushing AI to wireless network edge: An overview on integrated sensing, communication, and computation towards 6G. Science China Information Science++s. 2023 Mar;66(3):130301. https://doi.org/10.1007/s11432-022-3652-2

[30] Tera SP, Chinthaginjala R, Pau G, Kim TH. Toward 6G: An overview of the next generation of intelligent network connectivity. IEEE Access. 2024 Dec 26;13:925-61. https://doi.org/10.1109/ACCESS.2024.3523327

[31] Teimoori Z, Yassine A, Hossain MS. Smart vehicles recommendation system for artificial intelligence-enabled communication. IEEE Transactions on Consumer Electronics. 2024 Jan 30;70(1):3914-25. https://doi.org/10.1109/TCE.2024.3360320

[32] Tao Z, Xu W, Huang Y, Wang X, You X. Wireless network digital twin for 6G: Generative AI as a key enabler. IEEE Wireless Communications. 2024 Aug 7;31(4):24-31. https://doi.org/10.1109/MWC.002.2300564

[33] Sheraz M, Chuah TC, Lee YL, Alam MM, Al-Habashna AA, Han Z. A comprehensive survey on revolutionizing connectivity through artificial intelligence-enabled digital twin network in 6G. IEEE Access. 2024 Apr 3;12:49184-215. https://doi.org/10.1109/ACCESS.2024.3384272

[34] Shehzad MK, Rose L, Butt MM, Kovacs IZ, Assaad M, Guizani M. Artificial intelligence for 6G networks: Technology advancement and standardization. IEEE Vehicular Technology Magazine. 2022 May 4;17(3):16-25. https://doi.org/10.1109/MVT.2022.3164758

[35] Khan S, Khan S, Ali Y, Khalid M, Ullah Z, Mumtaz S. Highly accurate and reliable wireless network slicing in 5th generation networks: a hybrid deep learning approach. Journal of Network and Systems Management. 2022 Apr;30(2):29. https://doi.org/10.1007/s10922-021-09636-2

[36] Khan S, Hussain A, Nazir S, Khan F, Oad A, Alshehri MD. Efficient and reliable hybrid deep learning-enabled model for congestion control in 5G/6G networks. Computer Communications. 2022 Jan 15;182:31-40. https://doi.org/10.1016/j.comcom.2021.11.001

[37] Mahmood MR, Matin MA, Sarigiannidis P, Goudos SK. A comprehensive review on artificial intelligence/machine learning algorithms for empowering the future IoT toward 6G era. IEEE access. 2022 Aug 18;10:87535-62. https://doi.org/10.1109/ACCESS.2022.3199689

[38] Luo X, Chen HH, Guo Q. LEO/VLEO satellite communications in 6G and beyond networks-technologies, applications, and challenges. IEEE Network. 2024 Jan 15;38(5):273-85. https://doi.org/10.1109/MNET.2024.3353806

[39] Hashima S, Fadlullah ZM, Fouda MM, Mohamed EM, Hatano K, ElHalawany BM, Guizani M. On softwarization of intelligence in 6G networks for ultra-fast optimal policy selection: Challenges and opportunities. IEEE Network. 2022 Feb 18;37(2):190-7. https://doi.org/10.1109/MNET.103.2100587

[40] Gururaj HL, Natarajan R, Almujally NA, Flammini F, Krishna S, Gupta SK. Collaborative energy-efficient routing protocol for sustainable communication in 5G/6G wireless sensor networks. IEEE Open Journal of the Communications Society. 2023 Sep 8;4:2050-61. https://doi.org/10.1109/OJCOMS.2023.3312155

[41] Liu Q, Sun S, Rong B, Kadoch M. Intelligent reflective surface based 6G communications for sustainable energy infrastructure. IEEE Wireless Communications. 2022 Jan 21;28(6):49-55. https://doi.org/10.1109/MWC.016.2100179

[42] Lin Z, Feng Z, Guo K, Nauman A, Niyato D, Wang J. AI-driven seamless and massive access in space-air-ground integrated networks. IEEE Wireless Communications. 2025 May 27;32(3):72-9. https://doi.org/10.1109/MWC.001.2400371

[43] Kamruzzaman MM. Key technologies, applications and trends of internet of things for energy-efficient 6G wireless communication in smart cities. Energies. 2022 Aug 2;15(15):5608. https://doi.org/10.3390/en15155608

[44] Ismail L, Buyya R. Artificial intelligence applications and self-learning 6G networks for smart cities digital ecosystems: Taxonomy, challenges, and future directions. Sensors. 2022 Aug 1;22(15):5750. https://doi.org/10.3390/s22155750

[45] Irram F, Ali M, Naeem M, Mumtaz S. Physical layer security for beyond 5G/6G networks: Emerging technologies and future directions. Journal of Network and Computer Applications. 2022 Oct 1;206:103431. https://doi.org/10.1016/j.jnca.2022.103431

[46] Du J, Lin T, Jiang C, Yang Q, Bader CF, Han Z. Distributed foundation models for multi-modal learning in 6G wireless networks. IEEE Wireless Communications. 2024 Jun 14;31(3):20-30. https://doi.org/10.1109/MWC.009.2300501

[47] Cui H, Zhang J, Geng Y, Xiao Z, Sun T, Zhang N, Liu J, Wu Q, Cao X. Space-air-ground integrated network (SAGIN) for 6G: Requirements, architecture and challenges. China Communications. 2022 Feb 28;19(2):90-108. https://doi.org/10.23919/JCC.2022.02.008

[48] Ahmed Solyman A, Yahya HA. Evolution of wireless communication networks: from 1G to 6G and future perspective. International journal of electrical and computer engineering. 2022;12(4). https://doi.org/10.11591/ijece.v12i4.pp3943-3950

[49] Ahammed TB, Patgiri R, Nayak S. A vision on the artificial intelligence for 6G communication. Ict Express. 2023 Apr 1;9(2):197-210. https://doi.org/10.1016/j.icte.2022.05.005

[50] Abd Elaziz M, Al‐qaness MA, Dahou A, Alsamhi SH, Abualigah L, Ibrahim RA, Ewees AA. Evolution toward intelligent communications: Impact of deep learning applications on the future of 6G technology. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 2024 Jan;14(1):e1521. https://doi.org/10.1002/widm.1521

[51] Bhide P, Shetty D, Mikkili S. Review on 6G communication and its architecture, technologies included, challenges, security challenges and requirements, applications, with respect to AI domain. IET Quantum Communication. 2025 Jan;6(1):e12114. https://doi.org/10.1049/qtc2.12114

[52] Basharat S, Khan M, Iqbal M, Hashmi US, Zaidi SA, Robertson I. Exploring reconfigurable intelligent surfaces for 6G: State‐of‐the‐art and the road ahead. IET Communications. 2022 Aug;16(13):1458-74. https://doi.org/10.1049/cmu2.12364

[53] Barakabitze AA, Walshe R. SDN and NFV for QoE-driven multimedia services delivery: The road towards 6G and beyond networks. Computer Networks. 2022 Sep 4;214:109133. https://doi.org/10.1016/j.comnet.2022.109133

[54] Gera B, Raghuvanshi YS, Rawlley O, Gupta S, Dua A, Sharma P. Leveraging AI‐enabled 6G‐driven IoT for sustainable smart cities. International Journal of Communication Systems. 2023 Nov 10;36(16):e5588. https://doi.org/10.1002/dac.5588

[55] Fernando X, Lăzăroiu G. Energy-efficient industrial internet of things in green 6G networks. Applied Sciences. 2024 Sep 23;14(18):8558. https://doi.org/10.3390/app14188558

[56] Fan Z, Yan Z, Wen S. Deep learning and artificial intelligence in sustainability: a review of SDGs, renewable energy, and environmental health. Sustainability. 2023 Sep 8;15(18):13493. https://doi.org/10.3390/su151813493

[57] Peng H, Chen PC, Chen PH, Yang YS, Hsia CC, Wang LC. 6G toward metaverse: Technologies, applications, and challenges. In2022 IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS) 2022 Aug 24 (pp. 6-10). IEEE. https://doi.org/10.1109/APWCS55727.2022.9906483

[58] Pei J, Li S, Yu Z, Ho L, Liu W, Wang L. Federated learning encounters 6g wireless communication in the scenario of internet of things. IEEE Communications Standards Magazine. 2023 Mar 21;7(1):94-100. https://doi.org/10.1109/MCOMSTD.0005.2200044

[59] Padmapriya T, Salameh AA, Wildan MA, Kishore KH. AI Enabled-6G: Artificial intelligence (AI) for integration of 6G wireless communications. International Journal of Communication Networks and Information Security. 2022 Dec 1;14(3):372-9.

[60] Sanjalawe Y, Fraihat S, Abualhaj M, Makhadmeh S, Alzubi E. A review of 6G and AI convergence: Enhancing communication networks with artificial intelligence. IEEE Open Journal of the Communications Society. 2025 Mar 20. https://doi.org/10.1109/OJCOMS.2025.3553302

[61] Saeed MM, Saeed RA, Abdelhaq M, Alsaqour R, Hasan MK, Mokhtar RA. Anomaly detection in 6G networks using machine learning methods. Electronics. 2023 Jul 31;12(15):3300. https://doi.org/10.3390/electronics12153300

[62] Saafi S, Vikhrova O, Fodor G, Hosek J, Andreev S. AI-aided integrated terrestrial and non-terrestrial 6G solutions for sustainable maritime networking. IEEE Network. 2022 Jul 13;36(3):183-90. https://doi.org/10.1109/MNET.104.2100351

[63] Singh R, Kaushik A, Shin W, Di Renzo M, Sciancalepore V, Lee D, Sasaki H, Shojaeifard A, Dobre OA. Towards 6G evolution: Three enhancements, three innovations, and three major challenges. IEEE Network. 2025 May 29. https://doi.org/10.1109/MNET.2025.3574717

[64] Shi Y, Zhou Y, Wen D, Wu Y, Jiang C, Letaief KB. Task-oriented communications for 6G: Vision, principles, and technologies. IEEE Wireless Communications. 2023 Jul 13;30(3):78-85. https://doi.org/10.1109/MWC.002.2200468

[65] Shi Y, Lian L, Shi Y, Wang Z, Zhou Y, Fu L, Bai L, Zhang J, Zhang W. Machine learning for large-scale optimization in 6G wireless networks. IEEE Communications Surveys & Tutorials. 2023 Aug 1;25(4):2088-132. https://doi.org/10.1109/COMST.2023.3300664

[66] Zaman F, Farooq A, Ullah MA, Jung H, Shin H, Win MZ. Quantum machine intelligence for 6G URLLC. IEEE Wireless Communications. 2023 Apr 18;30(2):22-30. https://doi.org/10.1109/MWC.003.2200382

[67] Yeh C, Do Jo G, Ko YJ, Chung HK. Perspectives on 6G wireless communications. ICT Express. 2023 Feb 1;9(1):82-91. https://doi.org/10.1016/j.icte.2021.12.017

[68] Yang L, Li Y, Yang SX, Lu Y, Guo T, Yu K. Generative adversarial learning for intelligent trust management in 6G wireless networks. Ieee Network. 2022 Oct 14;36(4):134-40. https://doi.org/10.1109/MNET.003.2100672

[69] Xu M, Hoang DT, Kang J, Niyato D, Yan Q, Kim DI. Secure and reliable transfer learning framework for 6G-enabled Internet of Vehicles. IEEE Wireless Communications. 2022 May 9;29(4):132-9. https://doi.org/10.1109/MWC.004.2100542

[70] Na M, Lee J, Choi G, Yu T, Choi J, Lee J, Bahk S. Operator's perspective on 6G: 6G services, vision, and spectrum. IEEE Communications Magazine. 2024 Aug 12;62(8):178-84. https://doi.org/10.1109/MCOM.001.2400060

[71] Muscinelli E, Shinde SS, Tarchi D. Overview of distributed machine learning techniques for 6G networks. Algorithms. 2022 Jun 15;15(6):210. https://doi.org/10.3390/a15060210

[72] Merluzzi M, Borsos T, Rajatheva N, Benczur AA, Farhadi H, Yassine T, Müeck MD, Barmpounakis S, Strinati EC, Dampahalage D, Demestichas P. The Hexa-X project vision on artificial intelligence and machine learning-driven communication and computation co-design for 6G. IEEE Access. 2023 Jun 20;11:65620-48. https://doi.org/10.1109/ACCESS.2023.3287939

[73] Rasti M, Taskou SK, Tabassum H, Hossain E. Evolution toward 6G multi-band wireless networks: A resource management perspective. IEEE Wireless Communications. 2022 May 5;29(4):118-25. https://doi.org/10.1109/MWC.006.2100536

[74] Ramezanpour K, Jagannath J. Intelligent zero trust architecture for 5G/6G networks: Principles, challenges, and the role of machine learning in the context of O-RAN. Computer Networks. 2022 Nov 9;217:109358. https://doi.org/10.1016/j.comnet.2022.109358

[75] Jiang F, Peng Y, Dong L, Wang K, Yang K, Pan C, Niyato D, Dobre OA. Large language model enhanced multi-agent systems for 6G communications. IEEE Wireless Communications. 2024 Aug 16;31(6):48-55. https://doi.org/10.1109/MWC.016.2300600

[76] Jha AV, Appasani B, Khan MS, Zeadally S, Katib I. 6G for intelligent transportation systems: standards, technologies, and challenges. Telecommunication Systems. 2024 Jun;86(2):241-68. https://doi.org/10.1007/s11235-024-01126-5

[77] Lin X, Kundu L, Dick C, Obiodu E, Mostak T, Flaxman M. 6G digital twin networks: From theory to practice. IEEE Communications Magazine. 2023 Jun 12;61(11):72-8. https://doi.org/10.1109/MCOM.001.2200830

[78] Li H, Ota K, Dong M. Learning IoV in 6G: Intelligent edge computing for Internet of Vehicles in 6G wireless communications. IEEE Wireless Communications. 2023 Mar 7;30(6):96-101. https://doi.org/10.1109/MWC.017.2200089

[79] Alhammadi A, Shayea I, El-Saleh AA, Azmi MH, Ismail ZH, Kouhalvandi L, Saad SA. Artificial intelligence in 6G wireless networks: Opportunities, applications, and challenges. International Journal of Intelligent Systems. 2024;2024(1):8845070. https://doi.org/10.1155/2024/8845070

[80] Alhaj NA, Jamlos MF, Manap SA, Abdelsalam S, Bakhit AA, Mamat R, Jamlos MA, Gismalla MS, Hamdan M. Integration of hybrid networks, AI, ultra massive-MIMO, THz frequency, and FBMC modulation toward 6G requirements: A review. IEEE Access. 2023 Dec 21;12:483-513. https://doi.org/10.1109/ACCESS.2023.3345453

[81] Wang Y, Zhao J. Mobile edge computing, metaverse, 6G wireless communications, artificial intelligence, and blockchain: Survey and their convergence. In2022 IEEE 8th World Forum on Internet of Things (WF-IoT) 2022 Oct 26 (pp. 1-8). IEEE. https://doi.org/10.1109/WF-IoT54382.2022.10152245

[82] Wang Y, Gao Z, Zheng D, Chen S, Gündüz D, Poor HV. Transformer-empowered 6G intelligent networks: From massive MIMO processing to semantic communication. IEEE Wireless Communications. 2022 Nov 23;30(6):127-35. https://doi.org/10.1109/MWC.008.2200157

[83] Vilas Boas EC, e Silva JD, de Figueiredo FA, Mendes LL, de Souza RA. Artificial intelligence for channel estimation in multicarrier systems for B5G/6G communications: a survey. EURASIP Journal on Wireless Communications and Networking. 2022 Dec 2;2022(1):116. https://doi.org/10.1186/s13638-022-02195-3

[84] Tong W, Li GY. Nine challenges in artificial intelligence and wireless communications for 6G. IEEE Wireless Communications. 2022 May 5;29(4):140-5. https://doi.org/10.1109/MWC.006.2100543

[85] Ozpoyraz B, Dogukan AT, Gevez Y, Altun U, Basar E. Deep learning-aided 6G wireless networks: A comprehensive survey of revolutionary PHY architectures. IEEE Open Journal of the Communications Society. 2022 Sep 29;3:1749-809. https://doi.org/10.1109/OJCOMS.2022.3210648

[86] Olugbade S, Ojo S, Imoize AL, Isabona J, Alaba MO. A review of artificial intelligence and machine learning for incident detectors in road transport systems. Mathematical and Computational Applications. 2022 Sep 13;27(5):77. https://doi.org/10.3390/mca27050077

[87] Rahman MA, Hossain MS. A deep learning assisted software defined security architecture for 6G wireless networks: IIoT perspective. IEEE Wireless Communications. 2022 Jun 20;29(2):52-9. https://doi.org/10.1109/MWC.006.2100438

[88] Puspitasari AA, An TT, Alsharif MH, Lee BM. Emerging technologies for 6G communication networks: Machine learning approaches. Sensors. 2023 Sep 6;23(18):7709. https://doi.org/10.3390/s23187709

[89] Kim W, Ahn Y, Kim J, Shim B. Towards deep learning-aided wireless channel estimation and channel state information feedback for 6G. Journal of Communications and Networks. 2023 Jan 9;25(1):61-75. https://doi.org/10.23919/JCN.2022.000037

[90] Kharche S, Kharche J. 6G intelligent healthcare framework: A review on role of technologies, challenges and future directions. Journal of Mobile Multimedia. 2023 May;19(3):603-44. https://doi.org/10.13052/jmm1550-4646.1931

[91] Celik A, Eltawil AM. At the dawn of generative AI era: A tutorial-cum-survey on new frontiers in 6G wireless intelligence. IEEE Open Journal of the Communications Society. 2024 Feb 5;5:2433-89. https://doi.org/10.1109/OJCOMS.2024.3362271

[92] Catak FO, Kuzlu M, Catak E, Cali U, Unal D. Security concerns on machine learning solutions for 6G networks in mmWave beam prediction. Physical Communication. 2022 Jun 1;52:101626. https://doi.org/10.1016/j.phycom.2022.101626

[93] Sun R, Cheng N, Li C, Chen F, Chen W. Knowledge-driven deep learning paradigms for wireless network optimization in 6G. IEEE Network. 2024 Jan 10;38(2):70-8. https://doi.org/10.1109/MNET.2024.3352257

[94] Song W, Rajak S, Dang S, Liu R, Li J, Chinnadurai S. Deep learning enabled IRS for 6G intelligent transportation systems: A comprehensive study. IEEE Transactions on Intelligent Transportation Systems. 2022 Jun 24;24(11):12973-90. https://doi.org/10.1109/TITS.2022.3184314

[95] Tong W, Li GY. Nine challenges in artificial intelligence and wireless communications for 6G. IEEE Wireless Communications. 2022 May 5;29(4):140-5. https://doi.org/10.1109/MWC.006.2100543

Authors

Partha Sarathi Mohapatra
Mohapatra, P. S. . (2026). Artificial intelligence, big data analytics, and deep learning for 6G communication networks: Challenges, applications, and future directions. International Journal of Applied Resilience and Sustainability, 2(2), 817-841. https://doi.org/10.70593/deepsci.0202034

Article Details

How to Cite

Mohapatra, P. S. . (2026). Artificial intelligence, big data analytics, and deep learning for 6G communication networks: Challenges, applications, and future directions. International Journal of Applied Resilience and Sustainability, 2(2), 817-841. https://doi.org/10.70593/deepsci.0202034

Organizational culture for sustainable healthcare: An NLP-ML-SEM framework with the Sustainability Culture Alignment Index (SCAI)

Birupaksha Biswas, Suhena Sarkar, Joseph Ozigis Akomodi, Claudio Bellevicine (Author)
Abstract View : 275
Download :125

Sustainable supply chain management through a digital twin-enabled federated deep reinforcement learning framework

Santanu Acharyya, Suhena Sarkar, Bappaditya Biswas, Birupaksha Biswas, Prithwijit Banerjee...
Abstract View : 164
Download :251

Artificial intelligence-driven cybersecurity for resilient and sustainable business in Industry 5.0

Swapnil Malipatil, Jayesh Rane, Sibaram Prasad Panda, Nitin Liladhar Rane (Author)
Abstract View : 179
Download :191

Green artificial intelligence for sustainable and resilient development: A review

Dimple Ravindra Patil, Nitin Liladhar Rane, Obizue Mirian Ndidi, Jayesh Rane (Author)
Abstract View : 168
Download :81

Ethics, bias, and fairness challenges in artificial intelligence and machine learning

Ritesh Rastogi, Nitin Liladhar Rane, Ankur Chaudhary, Jayesh Rane (Author)
Abstract View : 194
Download :236

Qualitative research using artificial intelligence: Methods, techniques, challenges, and future directions

Dimple Ravindra Patil , Nitin Liladhar Rane , Obizue Mirian Ndidi, Jayesh Rane (Author)
Abstract View : 332
Download :252

Multi-agent cooperative control of a three-tank liquid system using reinforcement learning algorithms

Lincoln Nobert Munhenzwa, Adlen Kerboua, Godfrey Murairidzi Gotora (Author)
Abstract View : 104
Download :133