Skip to main content
Log in

A Comprehensive Survey on Security Issues in 5G Wireless Communication Network using Beamforming Approach

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Numerous devices are expected to upsurge profoundly in the proximate future with an estimated figure exceeding the 50 billion benchmark of connected devices by 2020. There are some rudimentary demands of the subscribers like system capacity, improved data rates with reduction in the latency and secure transmission of data in an unsecured media and to meet these demands, the cellular network has to go under suitable progression. As a building prospective for fulfilling these demands, to overcome the threats and challenges in the transmission of the data and to provide security to the information from the possible attacks, 5G is emerging as an optimal solution. For the demands of the tremendous count of subscribers, Device-to-Device Wireless Communication Network is an operative technology. The escalating content sharing amongst the users has been resulting in an exponential intensification in the wireless data traffic, coercing networks of cellular users to experience a suitable cataclysm. For allocating the resources to the Cellular Users under an attack scenario, numerous advances have been made till now. In this paper, an adaptive resource block allocation algorithm using HMM with beamforming approach has been projected to achieve high values of secrecy rate and low secrecy outage probability in 5G Wireless Communication Networks with the consideration of different applications demanded by Cellular Users and the priority of the applications (video, voice and data) in accord with enhanced Quality of Service of the channel. As the study of inherent secrecy rate for secure transmission of data in Wireless Communication Networks, random techniques are currently in great interest over the communication field. In this paper, it is to explore a multi-user scenario demanding different applications from BS under threat scenario of multi- eavesdropper. In this paper, different types of Beamforming are studied and different techniques involved for secure communication. An architecture has been provided for the security aspect in accordance with beamforming approach. As for better channel capacity, beamforming approach with diversity is an optimal solution for the secure transmission of information for Next Generation Networks.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27

Similar content being viewed by others

References

  1. Akhil, G., & Jha, R. K. (2015). A survey of 5G network: Architecture and emerging technologies. IEEE Access, 3, 1206–1232.

    Article  Google Scholar 

  2. Pimmy, G., & Jha, R. K. (2016). Device-to-device communication in cellular networks: A survey. Journal of Network and Computer Applications, 71, 99–117.

    Article  Google Scholar 

  3. Gartner (2018). Gartner says Worldwide PC, tablet and mobile phone combined shipments to reach 2.4 Billion Units in 2013. http://www.gartner.com/newsroom/id/2408515. Accessed 02 January 2018.

  4. Hasan, M., & Ekram H. (2014). Distributed resource allocation for relay-aided device-to-device communication: A message passing approach.

  5. Wilde, G. (2018). Worldwide device shipments to grow 1.9 Percent in 2016, while end-user spending to decline for the first time. http://www.gartner.com/newsroom/id/3187134. Accessed 02 January 2018.

  6. Cisco (2018). Visual networking index: Global mobile data traffic forecast update, 2015–2010. http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/mobile-white-paper-c11-520862.html. Accessed 02 January 2018.

  7. Asadi, A., Wang, Q., & Mancuso, V. (2014). A survey on device-to-device communication in cellular networks. IEEE Communication Surveys, 16(4), 1801–1819.

    Article  Google Scholar 

  8. Lin, Y.-D., & Hsu, Y.-C. (2000). Multihop cellular: A new architecture for wireless communications. In Proceedings of 19th annual joint conference of the IEEE computer and communication societies (INFOCOM) (pp. 1273–1282).

  9. Tehrani, M. N., Uysal, M., & Yanikomeroglu, H. (2014). Device-to-device communication in 5G cellular networks: Challenges solutions and future directions. IEEE Communication Magazine, 52(5), 86–92.

    Article  Google Scholar 

  10. Ma, D., & Tsudik, G. (2010). Security and Privacy in emerging wireless networks [invited paper]. IEEE Wireless Communication, 17(5), 12–21.

    Article  Google Scholar 

  11. Kumar, H., Sarma, D., & Kar, A. (2008). Security threats in wireless sensor networks. IEEE Aerospace Electronic System Magazine, 23(6), 39–45.

    Article  Google Scholar 

  12. Wu, B., Chen, J., Wu, J., & Cardei, M. (2007). A survey of attacks and countermeasures in mobile ad hoc networks. In Wireless network security (pp. 103–135), Springer.

  13. Wernke, M., Skvortsov, P., Dürr, F., & Rothermel, K. (2014). A classification of location privacy attacks and approaches. Personal Ubiquitous Computer, 18(1), 163–175.

    Article  Google Scholar 

  14. Gandotra, P., Jha, R. K., & Jain, S. (2017). A survey on device-to-device (D2D) communication: Architecture and security issues. Journal Network Computer Application, 78, 9–29.

    Article  Google Scholar 

  15. Blogh, J., & Hanzo, L. (2004). Third-generation systems and intelligent wireless networking: Smart antennas and adaptive modulation. In Wiley-IEEE Press. SciTech Publishing.

  16. Qinghua, L., Guangjie, L., Wookbong, L., Moon-il, L., Mazzarese, D., Clerckx, B., et al. (2010). MIMO techniques in WiMAX and LTE: A feature overview. Communications Magazine, IEEE., 48(5), 86–92.

    Article  Google Scholar 

  17. Godara, L. C. (1997). Application of antenna arrays to mobile communications. II. Beam-forming and direction-of-arrival considerations. Proceedings of the IEEE, 85, 1195–1245.

    Article  Google Scholar 

  18. Golbon-Haghighi, M. H. (2016). Beamforming in wireless networks (PDF). InTech Open (pp. 163–199).

  19. Van Veen, B. D., & Buckley, K. M. (1988). Beamforming: A versatile approach to spatial filtering (PDF). IEEE ASSP Magazine, 5(2), 4.

    Article  Google Scholar 

  20. Godara, L. C. (1997). Applications of antenna arrays to mobile communication, Part I: Performance improvement, feasibility, and system considerations. Proceedings of the IEEE, 85(7), 1031–1060.

    Article  Google Scholar 

  21. Rappaport, T. S., Sun, S., Mayzus, R., Zhao, H., Azar, Y., Wang, K., et al. (2013). Millimeter wave mobile communication for 5G cellular: It will work! IEEE Access., 1, 335–349.

    Article  Google Scholar 

  22. Pi, Z., & Khan, F. (2011). An introduction to Millimeter-wave mobile broadband systems. IEEE Communications Magazine, 49, 101–107.

    Article  Google Scholar 

  23. Balanis, C. A. (2005). Antenna theory: Analysis and design. New York: Wiley.

    Google Scholar 

  24. Diggavi, S. N., Al-Dhahir, N., Stamoulis, A., & Calderbank, A. R. (2004). Great expectations: The value of spatial diversity in wireless networks. Proceedings of the IEEE, 92(2), 219–270.

    Article  Google Scholar 

  25. Montebugnoli, S., Bianchi, G., Cattani, A., Ghelfi, F., Maccaferri, A., & Perini (xxxx). Some notes on beamforming’. IRA N, 353/04.

  26. GPP (2004). Beamforming enhancements. TR 25.887 V6.0.0 (200403), Release 6, 3GPP.

  27. Derryberry, R. T., Gray, S. D., Ionescu, D. M., Mandyam, G., & Raghothaman, B. (2002). Transmit diversity in 3G CDMA systems. IEEE Communications Magazine, 40(4), 68–75.

    Article  Google Scholar 

  28. Lee, D., & Ng, W. T. (2005). Beamforming system for 3G and 4G wireless LAN applications. IEEE Access, 3, 137–140.

    Google Scholar 

  29. Gotsis, K. A., & Sahalos, J. N. (2011). Beamforming in 3G and 4G mobile communication: The Switched-beam approach. Recent Developments in Mobile Communications-A multidisciplinary approach. Intechweb.

  30. Geier, E. (2015). All about beamforming, the faster Wi-Fi you didn’t know you needed. In PC World. IDG Consumer & SMB. Retrieved, from 19 October 2015.

  31. Van Trees, H. L. (2004). Part IV of estimation and modulation theory: Optimum array processing. Hoboken: Wiley.

    Google Scholar 

  32. Krim, H., & Viberg, M. (1996). Two decades of array signal processing research: The parametric approach. IEEE Signal Processing Magazine, 13(4), 67–94.

    Article  Google Scholar 

  33. Godara, L. C. (1997). Applications of antenna arrays to mobile communications—Part II: Beam-forming and direction-of-arrival considerations. Proceedings of the IEEE, 85(8), 1195–1245.

    Article  Google Scholar 

  34. Widrow, B. (1967). Adaptive antenna systems. Proceedings of the IEEE, 55(12), 2143–2159.

    Article  Google Scholar 

  35. Griffiths, L. J. (1969). A simple adaptive algorithm for real-time processing in antenna arrays. Proceedings of the IEEE, 57(10), 1696–1704.

    Article  Google Scholar 

  36. Frost, O. L., III. (1972). An algorithm for linearly constrained adaptive array processing. Proceedings of the IEEE, 60(8), 926–935.

    Article  Google Scholar 

  37. Godara, L. C. (2004). ‘Smart Antennas’. Boca Raton: CRC Press.

    Book  Google Scholar 

  38. Gross, F. (2005). Smart antennas for wireless communications with MATLAB. New York: McGraw-Hill.

    Google Scholar 

  39. Imtiaj, S., Misra, I. S., & Biswas, R. (2012). A comparative study of beamforming techniques using LMS and SMI algorithms in smart antennas. In International conference on communications, devices and intelligent systems (CODIS) (pp. 246–249), 2012 Kolkata.

  40. Nwalozie, G., Okorogu, V., Maduadichie, S., & Adenola, A. (2013). A simple comparative evaluation of adaptive beam forming algorithms. International Journal of Engineering and Innovative Technology (IJEIT), 2, 417–424.

    Google Scholar 

  41. Rao, A. P., & Sarma, N. (2014). Adaptive beamforming algorithms for smart antenna systems. WSEAS Transactions on Communications, 13, 44–50.

    Google Scholar 

  42. Saxena, P., & Kothari, A. (2014). Performance analysis of adaptive beamforming algorithms for smart antennas. IERI Procedia, 10, 131–137.

    Article  Google Scholar 

  43. Simon, H. (2002). Adaptive filter theory (4th ed.). New York: Springer.

    Google Scholar 

  44. Surendra, L., Shameem, S., & Khan, D. H. (2012). Performance comparison of LMS, SMI and RLS adaptive beamforming algorithms for smart antennas. In International journal of computer science and technology (IJCST) (vol. 3, pp. 973–977).

  45. Veerendra, & Bakhar, M. (2014). Design and performance analysis of adaptive beamforming algorithm for smart antenna systems. In International journal of advanced research in electronics and communication engineering (IJARECE) (vol. 3, pp. 704–707).

  46. Ali, W., & Hassan, A. H. (2014) A hybrid least mean square/sample matrix inversion algorithm using micro strip antenna array. In Science and information conference (SAI) (pp. 871–876), London, UK.

  47. Liu, W., & Weiss, S. (2010). Wideband beamforming: Concepts and techniques. Hoboken: Wiley.

    Book  Google Scholar 

  48. Johnson, D. H., & Dudgeon, D. E. (1993). Array signal processing: Concepts and techniques. Englewood Cliffs: Prentice-Hall.

    MATH  Google Scholar 

  49. IEEE 802.15 (xxxx). WPAN Millimeter Wave Alternative PHY Task Group 3c. http://www.ieee802.org/15/pub/TG3c.html.

  50. Aerts, W., Delmotte, P., & Vandenbosch, G. A. E. (2009). Conceptual study of analog baseband beam forming: Design and measurement of an eight- by-eight phased array. Transaction on Antenna Propagation, 57(5), 000–999.

    Google Scholar 

  51. Kashif, F. M., Qadeer, W., & Shah, S. I. (2001). Efficient implementation of quadrature amplitude modulation transmitters. In IEEE INMIC technology for the 21st century.

  52. Capon, J. (1969). High-resolution frequency-wave number spectrum analysis. In Proceedings of IEEE (vol. 57, No. 8, pp. 1408–1418).

  53. Gershman, A., Sidiropoulos, N., Shahbazpanahi, S., Bengtsson, M., & Ottersten, B. (2010). Convex optimization-based beamforming. IEEE Signal Processing Magazine, 27(3), 62–75.

    Article  Google Scholar 

  54. Clerckx, B., Kim, G., Choi, J., & Hong, Y.-J. (2010). Explicit versus implicit feedback for SU and MU-MIMO. In Proceedings of IEEE global communication conference (GLOBECOM) (pp. 1–5).

  55. Lou, H., Ghosh, M., Xia, P., & Olesen, R. (2013). A comparison of implicit and explicit channel feedback methods for MU-MIMO WLAN systems. In Proceedings of IEEE personal indoor mobile radio communication (PIMRC) (pp. 419–424).

  56. Compton, R. T. (1988). Adaptive antennas. Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  57. Zatman, M. (1998). How narrow is narrowband? IEE Proceedings - Radar, Sonar and Navigation, 145(2), 85–91.

    Article  Google Scholar 

  58. Madisetti, V., & Williams, D. (Eds.). (1997). The digital signal processing handbook. Boca Raton: CRC Press.

    Google Scholar 

  59. Benesty, J., Chen, J., & Huang, Y. (2008). Microphone array signal processing. Berlin: Springer-Verlag.

    Google Scholar 

  60. Dokmanic, I., Scheibler, R., & Vetterli, M. (2015). Raking the cocktail party. IEEE Journal of Selected Topics in Signal Processing, 9(5), 825–836.

    Article  Google Scholar 

  61. Kennedy, R. A., Abhayapala, T. D., & Ward, D. B. (1998). Broadband nearfield beamforming using a radial beampattern transformation. IEEE Transactions on Signal Processing, 46(8), 2147–2156.

    Article  Google Scholar 

  62. Doclo, S., & Moonen, M. (2003). Design of far-field and nearfield broadband beamformers using eigenfilters. Signal Processing, 83, 2641–2673.

    Article  MATH  Google Scholar 

  63. Madisetti, V., & Williams, D. B. (1998). The digital signal processing handbook (1st ed.). Salem: CRC Press LLC.

    Google Scholar 

  64. Van Trees, H. (2002). Detection, Estimation and Modulation theory, part IV, Optimum Array Processing. New York: Wiley.

    Google Scholar 

  65. Muirhead, R. J. (2005). Aspects of multivariate statistical theory. New York: Wiley.

    MATH  Google Scholar 

  66. Peel, et. al. (2005). A vector-perturbation technique for near-capacity multi antenna multiuser communication-part I: channel inversion and regularization. In IEEE Transactions on Communications.

  67. Van Trees, H. L. (2002). Optimum array processing–part IV, detection, estimation, and modulation theory (1st ed.). Hoboken: Wiley.

    Google Scholar 

  68. Cox, H., et al. (2011). Robust adaptive beamforming. In IEEE transactions on acoustics, speech and signal processing (vol. 35, No. 10).

  69. Peel, B. C. B., Hochwald, B. M., & Swindlehurst, A. L. (2005). A vector-perturbation technique for near-capacity multiantenna multiuser communication—Part I: channel inversion and regularization. IEEE Transactions on Communications, 53, 195–202.

    Article  Google Scholar 

  70. Tom, L. (2015). Game‐theoretic approach towards network security: a review. In 2015 international conference on circuit, power and computing technologies (ICCPCT) (pp. 1–4).

  71. Chen, B., Jun, Z., & Yuan, Z. (2015). A time division scheduling resource allocation algorithm for D2D communication in cellular networks. In Communications (ICC), 2015 IEEE International Conference on. IEEE.

  72. Wunder, G., et al. (2013). 5GNOW: Challenging the LTE design paradigms of orthogonality and synchronicity. In Vehicular Technology Conference (VTC Spring), 2013 IEEE 77th. IEEE.

  73. Zheng, J., Biwei, C., & Yuan, Z. (2015). An adaptive time division scheduling based resource allocation algorithm for D2D communication under laying cellular networks. In 2015 IEEE global communications conference (GLOBECOM). IEEE.

  74. 4G Americas’ summary of global 5G initiatives. White Paper, 4G Americas. http://www.4gamericas.org/documents/2014.4GA. Summary of Global 5G Initiatives Final.pdf

  75. Monserrat, J. F., et al. (2014). Rethinking the mobile and wireless network architecture: The METIS research into 5G. In: 2014 European conference on networks and communications (EuCNC), IEEE.

  76. Belfiore, J.-C. (2014). Codes for wireless wiretap channels. In Information theory workshop (ITW), IEEE.

  77. Baldemair, R., et al. (2013). Evolving wireless communications: Addressing the challenges and expectations of the future. In Vehicular technology magazine (pp. 24–30), IEEE 8.1.

  78. Rappaport, T. S. (1996). Wireless communications: Principles and practice (Vol. 2). New Jersey: Prentice Hall.

    MATH  Google Scholar 

  79. Halonen, T., Javier, R., & Juan, M. (2004). GSM, GPRS and EDGE performance: evolution towards 3G/UMTS. London: Wiley.

    Google Scholar 

  80. Furht, B., & Syed, A. A. (2009). Long Term Evolution: 3GPP LTE radio and cellular technology. New York: CRC Press.

    Google Scholar 

  81. Rusek, F., et al. (2013). Scaling up MIMO: Opportunities and challenges with very large arrays. IEEE Signal Processing Magazine, 30(1), 40–60.

    Article  Google Scholar 

  82. Studer, C., & Larsson, E. G. (2013). PAR-aware large-scale multi-user MIMO-OFDM downlink. IEEE Journal on Selected Areas in Communications, 31, 303–313.

    Article  Google Scholar 

  83. Larsson, E. G., et al. (2013). Massive MIMO for next generation wireless systems. arXiv preprint arXiv:1304.6690.

  84. Nam, J., Ahn, J.-Y., Adhikary, A., & Caire, G. (2012). Joint spatial division and multiplexing: Realizing massive MIMO gains with limited channel state information. In 46th Annual conference on information sciences and systems (CISS).

  85. Agyapong, P. K., et al. (2014). Design considerations for a 5G network architecture. Communications Magazine, 3, 65–75.

    Article  Google Scholar 

  86. (2013). Advanced 5G network infrastructure for the future internet-public private partnership in horizon 2020.

  87. Fallgren, Mikael, & Timus, Bogdan. (2013). Scenarios, requirements and KPIs for 5G mobile and wireless system. METIS deliverable D, 1, 1.

    Google Scholar 

  88. Mikael, F., & Bogdan, T. (Eds.) (2013). Scenarios, requirements and KPIs for 5G mobile and wireless system,” METIS deliverable D1.1.

  89. Yue, J., et al. (2013). Secrecy-based access control for device to- device communication underlaying cellular networks. IEEE Commun. Letters, 17(11), 2068–2071.

    Article  Google Scholar 

  90. Zhou, Y., Fang, Y., & Zhang, Y. (2008). Securing wireless sensor networks: A survey. IEEE Commun. Surveys Tutorials, 10(3), 6–28.

    Article  Google Scholar 

Download references

Acknowledgement

The authors appreciatively acknowledge the support delivered by 5G and IoT Lab, DoECE, and TBIC, Shri Mata Vaishno Devi University, Katra, Jammu.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rakesh Kumar Jha.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

A list of recent research projects based on security scenario in 5G WCN are given in Table 7. A list of abbreviations is given in Table 8.

Table 7 5G security scenario activities around the world [75, 76, 88, 89]
Table 8 LIST OF ABBREVIATIONS

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sharma, A., Jha, R.K. A Comprehensive Survey on Security Issues in 5G Wireless Communication Network using Beamforming Approach. Wireless Pers Commun 119, 3447–3501 (2021). https://doi.org/10.1007/s11277-021-08416-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08416-0

Keywords

Navigation