Open Access
Security and Safety
Volume 2, 2023
Article Number 2023003
Number of page(s) 15
Section Information Network
Published online 02 August 2023
  1. Yao FQ. Communication Anti-jamming Engineering and Practice (in Chinese). Beijing: Publishing House of Electronics Industry, 2012. [Google Scholar]
  2. Simon MK, Omura JK and Scholtz RA et al. Spread Spectrum Communications. New York: McGraw-Hill, Inc, 1985. [Google Scholar]
  3. Wang SF, Bao YF and Li Y. The architecture and technology of cognitive electronic warfare (in Chinese). Sci Sin Inf 2018; 48: 1603–13. [CrossRef] [Google Scholar]
  4. Wu JX. Development paradigms of cyberspace endogenous safety and security (in Chinese). Sci Sin Inform 2022; 52: 189–204. [CrossRef] [Google Scholar]
  5. Wu JX. Principles of Cyberspace mimic Defense: General Robust Control and Endogenous Safety & Security (in Chinese). Beijing: Science Press, 2018. [Google Scholar]
  6. Hu AQ, Fang LT and Li T. Research on bionic mechanism based endogenous security defense system (in Chinese). Chin J Network Inf Secur 2021; 7: 11–9. [Google Scholar]
  7. Jin L, Hu XY and Lou YM et al. Introduction to wireless endogenous security and safety: Problems, attributes, structures and functions. China Communications, 2021; 18: 88–99. [CrossRef] [Google Scholar]
  8. Jin L, Lou YM and Sun XL, et al. Concept and vision of 6G wireless endogenous safety and security (in Chinese). Sci Sin Inform, 2023; 53: 344–364. [CrossRef] [Google Scholar]
  9. Zhang XD. Matrix Analysis and Applications (in Chinese). Beijing: Tsinghua University Press, 2004. [Google Scholar]
  10. Erpek T, Sagduyu YE and Shi Y. Deep learning for launching and mitigating wireless jamming attacks. IEEE TransCognit Commun Networks 2019; 5: 2–14. [CrossRef] [Google Scholar]
  11. Liu X, Xu YH and Jia LL et al. Anti-jamming communications using spectrum waterfall: a deep reinforcement learning approach. IEEE Commun Lett 2018; 22: 998–1001. [CrossRef] [Google Scholar]
  12. Li YY, Xu YH and Xu YT et al. Dynamic spectrum anti-jamming in broadband communications: a hierarchical deep reinforcement learning approach. IEEE Wireless Commun Lett 2020; 9 1616–19. [CrossRef] [Google Scholar]
  13. Xiao L, Jiang DH and Xu DJ et al. Two-dimensional antijamming mobile communication based on reinforcement learning. IEEE Trans Vehicular Technol 2018; 67: 9499–512. [CrossRef] [Google Scholar]
  14. Pirayesh H and Zeng HC. Jamming attacks and anti-jamming strategies in wireless networks: a comprehensive survey. IEEE Commun Surv Tutorials 2022; 24: 767–809. [CrossRef] [Google Scholar]
  15. Peng QH, Cosman PC and Milstein LB. Spoofing or Jamming Performance Analysis of a Tactical Cognitive Radio Adversary. IEEE J Sel. Areas Commun 2011; 29: 903–11. [CrossRef] [Google Scholar]
  16. Sadeghi M and Larsson EG. Adversarial attacks on deep-learning based radio signal classification. IEEE Wireless Commun Lett 2019; 8: 213–16. [CrossRef] [Google Scholar]
  17. Sagduyu YE, Shi Y and Erpek T. Adversarial deep learning for over-the-air spectrum poisioning attacks. IEEE Trans Mobile Comput 2021; 20: 306–19. [CrossRef] [Google Scholar]
  18. Shannon CE. A mathematical theory of communication. Bell Syst Techn J 1948; 27: 379–423. [CrossRef] [Google Scholar]
  19. Luo XW, Chen HH and Guo Q. Semantic communication: overview, open issues, and future research directions. IEEE Wireless Commun 2022; 29: 210–19. [CrossRef] [Google Scholar]
  20. Zhang YC, Zhang P and Wei JB et al. Semantic communication for intelligent devices: architectures and a paradigm (in Chinese). Sci Sin Inf 2022; 53: 907–21. [CrossRef] [Google Scholar]
  21. Do TN, Kaddoum G and Nguyen TL et al. Multi-RIS-Aided wireless systems: statistical characterization and performance analysis. IEEE Trans Commun 2021; 69: 8641–58. [CrossRef] [Google Scholar]
  22. Molisch AF. Wireless Communications, second edition. UK: John Wiley & Sons Ltd, 2011. [Google Scholar]
  23. Venugopal A and Leib H. A tensor based framework for multi-domain communication systems. IEEE Open J Commun Soc 2020; 1: 606–35. [CrossRef] [Google Scholar]
  24. Jia LL, Xu YH and Sun YM et al. A multi-domain anti-jamming defense scheme in heterogeneous wireless networks. IEEE Access 2018; 6: 40177–188. [CrossRef] [Google Scholar]
  25. Li YC, Bai SZ and Gao ZZ. A multi-domain anti-jamming strategy using stackelberg game in wireless relay networks. IEEE Access 2020; 8: 173609–3617. [CrossRef] [Google Scholar]
  26. Xiao J, Yang CG and Anpalagan A et al. Joint interference management in ultra-dense small-cell networks a multi-domain coordination perspective. IEEE Trans Commun 2018; 66: 5470–81. [CrossRef] [Google Scholar]
  27. Yucek T and Arslan H. A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Commun Surv Tutorials 2009; 11: 116–30. [CrossRef] [Google Scholar]
  28. Somaraju R and Trumpf J. Degrees of freedom of a communication channel: using DOF singular values. IEEE Trans Inf Theory 2010; 56: 1560–73. [CrossRef] [Google Scholar]
  29. Shannon CE. Communication in the presence of noise. Proc I.R.E 1949; 37: 10–21. [CrossRef] [Google Scholar]
  30. Poon AS, Brodersen RW and Tse DN. Degrees of freedom in multiple-antenna channels: a signal space approach. IEEE Trans Inf Theory 2005; 51: 523–36. [CrossRef] [Google Scholar]
  31. Seddik KG. On the degrees of freedom of IRS-assisted non-coherent MIMO communications. IEEE Commun Lett 2022; 26: 1175–79. [CrossRef] [Google Scholar]
  32. Xu J. Degrees of freedom of OAM-based line-of-sight radio systems. IEEE Trans Antennas Propag 2017; 65: 1996–2008. [CrossRef] [Google Scholar]
  33. Lu L, Li GY and Maaref A et al. Opportunistic transmission exploiting frequency- and spatial-domain degrees of freedom. IEEE Wireless Commun 2014; 21: 91–7. [CrossRef] [Google Scholar]
  34. Bogucka H and Conti A. Degrees of freedom for energy savings in practical adaptive wireless systems. IEEE Commun Mag 2011; 49: 38–45. [CrossRef] [Google Scholar]
  35. Chung ST and Goldsmith AJ. Degrees of freedom in adaptive modulation: a unified view. IEEE Trans Commun 2001; 49: 1561–71. [CrossRef] [Google Scholar]
  36. Wang XH, Dong JS and Chi CY et al. Semantic space: an infrastructure for smart spaces. IEEE Pervasive Comput 2004; 3: 32–9. [CrossRef] [Google Scholar]
  37. Zhang SY, Yang ZL and Yang JS et al. Linguistic steganography: from symbolic space to semantic space. IEEE Signal Process Lett 2021; 28 11–5. [CrossRef] [Google Scholar]
  38. Chen YD and Chi YJ. Harnessing structures in big data via guaranteed low-rank matrix estimation. IEEE Signal Process Mag 2018; 35: 14–31. [CrossRef] [Google Scholar]
  39. Friedlander B. Communications through time-varying subspace channels. IEEE J Sel Areas Commun 2008; 26: 338–47. [CrossRef] [Google Scholar]
  40. Renzo MD, Debbah M and Phan-Huy D et al. Smart radio environments empowered by reconfigurable AI meta-surfaces: an idea whose time has come. EURASIP J Wireless Commun Networks 2019; 129: 1–20. [Google Scholar]
  41. Wu QQ and Zhang R. Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network. IEEE Commun Mag 2020; 58: 106–112. [CrossRef] [Google Scholar]
  42. Gacanin H and Renzo MD. Wireless 2.0 toward an intelligent radio environment empowered by reconfigurable meta-surfaces and artificial intelligence. IEEE Vehicular Technol Mag 2020; 15: 74–82. [CrossRef] [Google Scholar]
  43. Cui TJ, Jin S and Zhang JY et al. Research Report on Reconfigurable Intelligent Surface (RIS) (in Chinese). IMT-2030(6G) Promotion Group, 2021. [Google Scholar]
  44. Sun YF, An K and Zhu YG et al. Intelligent reflecting surface assisted anti-jamming approach for wireless communications (in Chinese). Chin J Radio Sci 2021; 36: 877–86. [Google Scholar]
  45. Yuan SA, He Z and Chen XM et al. Electromagnetic effective degree of freedom of an MIMO system in free space. IEEE Antennas Wireless Propag Lett 2022; 21: 446–50. [CrossRef] [Google Scholar]
  46. Luo ZQ, Li CJ and Zhu LD. A comprehensive survey on blind source separation for wireless adaptive processing: principles, perspectives, challenges and new research directions. IEEE Access 2018; 6: 66685–708. [CrossRef] [Google Scholar]
  47. Yan XL, Zou XH and Li PX et al. Covert wireless communication using massive optical comb channels for deep denoising. Photonics Res 2021; 9: 1124–33. [CrossRef] [Google Scholar]
  48. Zhang L, Chen MZ and Tang WK et al. A wireless communication scheme based on space- and frequency-division multiplexing using digital metasurfaces. Nat Electron 2021; 4: 218–27. [CrossRef] [Google Scholar]
  49. Sun YF, An K and Zhu YG et al. Intelligent reflecting surface enhanced secure transmission against both jamming and eavesdropping attacks. IEEE Trans Vehicular Technol 2021; 70: 11017–022. [CrossRef] [Google Scholar]
  50. Sun YF, An K and Zhu YG et al. RIS-assisted robust hybrid beamforming against simultaneous jamming and eavesdropping attacks. IEEE Trans Wireless Commun 2022; 21: 9212–231. [CrossRef] [Google Scholar]
  51. Glybovski SB, Tretyakovb SA and Belov PA et al. Metasurfaces: from microwaves to visible. Phys Rep 2016; 634: 1–72. [CrossRef] [Google Scholar]
  52. Dai JY, Tang WK and Chen MZ et al. Wireless communication based on information metasurfaces. IEEE Trans Microwave Theory Tech 2021; 69: 1493–510. [CrossRef] [Google Scholar]
  53. Yu NF, Genevet P and Kats MA et al. Light propagation with phase discontinuities generalized laws of reflection and refraction. Science 2011; 334: 333–7. [Google Scholar]
  54. Ozdogan O, Bjornson E and Larsson EG. Intelligent reflecting surfaces: physics, propagation, and pathloss modeling. IEEE Wireless Commun Lett 2020; 9: 581–85. [CrossRef] [Google Scholar]
  55. Cui TJ, Wu HT and Liu S. Research progress of information metamaterials (in Chinese). Acta Phys Sin 2020; 69: 158101. [CrossRef] [Google Scholar]
  56. Tang WK, Chen MZ and Chen X et al. Wireless communications with reconfigurable intelligent surface path loss modeling and experimental measurement. IEEE Trans Wireless Commun 2021; 20: 421–39. [CrossRef] [Google Scholar]
  57. Zheng BX, You CS and Mei WD et al. A survey on channel estimation and practical passive beamforming design for intelligent reflecting surface aided wireless communications. IEEE Commun Surv Tutorials 2020; 24: 1035–71. [Google Scholar]
  58. Basar E and Yildirim I, Reconfigurable intelligent surfaces for future wireless networks: a channel modeling perspective. IEEE Wireless Commun 2021; 28: 108–14. [CrossRef] [Google Scholar]

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