Performance Analysis of Blockage Detection in 6G Wireless Networks
محورهای موضوعی : Communication Systems & Devices
Nagaraja kumar Neravati
1
,
Anil Kumar R
2
,
Subba Raju MP
3
,
Kalyani K
4
,
Surya Kala Nagireddi
5
,
Yarrapragada Rao K. S. S.
6
1 - 1Dept of ECE, Rajeev Gandhi memorial college of engineering and technology, Nandyal, India
2 - Dept of ECE, Aditya University, Surampalem, India
3 - Dept of EEE, Aditya University, Surampalem, India
4 - Aditya University, Surampalem, India
5 - Dept of Technology, Aditya University, Surampalem, India
6 - 6Aditya University, Surampalem, India
کلید واژه: 6G, Blockage Detection, Detection Probability, STFT, sub-terahertz, ,
چکیده مقاله :
This paper presents a proactive blockage detection algorithm and performance for sub-terahertz (sub-THz) communication systems. It is a critical technology for next-generation wireless networks. Human body blockage remains a significant challenge for millimeter wave and sub-THz systems, it is often causing severe signal degradation and connectivity loss. Current solutions, predominantly time-domain approaches or machine learning models. These are suffering from high computational complexity, limited accuracy and the inability to detect blockages before they occur. The proposed algorithm overcomes these limitations by leveraging spectral-domain analysis using the short-time Fourier transform (STFT). It helps to detect the pre-blockage signatures with high precision. Blockage Detection algorithm adopts a simple and threshold-based detection mechanism. This operates in three stages: initialization, active monitoring and blockage recovery. The results demonstrate that the proposed algorithm achieves a detection probability PB exceeding 99%. It detects blockages at least 50 ms before their occurrence. Additionally, the algorithm provides superior mean time to blockage reaching 150ms for optimal parameters. This is significantly earlier than traditional methods. These findings highlight the algorithm's effectiveness in mitigating connectivity issues in dense indoor deployments and its adaptability to various network configurations. The proposed solution is well-suited for applications requiring ultra-reliable low-latency communication, augmented reality, autonomous vehicles, and industrial IoT. This offers a promising step towards seamless 6G wireless communication.
[1] R. Govindasamy, S. K. Nagarajan, J. R. Muthu, and P. Annadurai, “Deep optimized hybrid beamforming intelligent reflecting surface assisted UM-MIMO THz communication for 6G broadband connectivity,” Telecommunication Systems, vol. 86, no. 4, pp. 645–660, 2024.
[2] F. Zhinuk, A. Gaydamaka, D. Moltchanov, and Y. Koucheryavy, “Spectral-based proactive blockage detection for sub-THz communications,” IEEE Communications Letters, vol. 28, no. 7, pp. 1703–1707, 2024.
[3] H. Gui, Y. Xie, Q. Song, Y. Qian, and R. Zhang, “Improved SIC-SVD hybrid precoding algorithm for indoor sub-THz systems,” IEEE Access, vol. 11, pp. 93691–93700, 2023.
[4] Z. Wang, X. Mu, J. Xu, and Y. Liu, “Simultaneously transmitting and reflecting surface (STARS) for terahertz communications,” IEEE Journal on Selected Topics in Signal Processing, vol. 17, no. 4, pp. 861–877, 2023.
[5] J. Wang and M. Kaneko, “Exploiting beam split-based multi-user diversity in terahertz MIMO-OFDM systems,” IEEE Wireless Communications Letters, 2024.
[6] M. Giordani, A. Zanella, and M. Zorzi, “Millimeter wave communication in vehicular networks: Challenges and opportunities,” IEEE Vehicular Technology Magazine, vol. 14, no. 3, pp. 42–52, Sep. 2019.
[7] Fazal-E-Asim, B. Sokal, A. L. F. De Almeida, B. Makki, and G. Fodor, “Structured channel estimation for RIS-assisted THz communications,” IEEE Transactions on Vehicular Technology, 2024.
[8] F. Zhinuk, A. Gaydamaka, D. Moltchanov, and Y. Koucheryavy, “Spectral-based proactive blockage detection for sub-THz communications,” IEEE Communications Letters, vol. 28, no. 7, p. 1703 – 1707, 2024
[9] J. Liu, X. Hou, W. Liu, L. Chen, Y. Kishiyama, and T. Asai, “Unified 6G waveform design based on DFT-S-OFDM enhancements,” IEICE Transactions on Communications, vol. E106B, no. 6, p. 528 – 537, 2023.
[10] T. Dheerajlal, A. Madhusree, and A. K. Dutta, “An MB-OFDM based wideband Thz communication system with impairment aware precoder and squint effect mitigation,” IEEE Access, vol. 12, p. 18122 – 18146, 2024.
[11] Y. Yuan, T. Zhang, Z. Zhang, X. Zhao, X. Wu, S. Zheng, L. Liang, and C. Cao, “Robust charac- terization of terahertz metasurface sensor with ultra-high frequency selectivity and polarization sensitivity,” IEEE Sensors Journal, 2024.
[12] Y. Xie, Y. Ma, X. Liu, S. A. Khan, W. Chen, L. Zhu, J. Zhu, and Q. H. Liu, “Dual-degree-of-freedom multiplexed metasensor based on quasi-bics for boosting broadband trace isomer detection by Thz molecular fingerprint,” IEEE Journal of Selected Topics in Quantum Electron- ics, vol. 29, no. 5, 2023.
[13] R. Henri, K. Nallappan, D. S. Ponomarev, H. Guerboukha, D. V. Lavrukhin, A. E. Yachmenev, R. A. Khabibullin, and M. Skorobogatiy, “Fabrication and characterization of an 8 × 8 terahertz photoconductive antenna array for spatially resolved time domain spectroscopy and imaging applications,” IEEE Access, vol. 9, p. 117691 – 117702, 2021
[14] H. Zarini, N. Gholipoor, M. R. Mili, M. Rasti, H. Tabassum, and E. Hossain, “Resource man- agement for multiplexing eMBB and URLLC services over ris-aided THz communication,” IEEE Transactions on Communications, vol. 71, no. 2, p. 1207 – 1225, 2023.
[15] J. Wang and M. Kaneko, “Exploiting beam split-based multi-user diversity in terahertz MIMO-OFDM systems,” IEEE Wireless Communications Letters, 2024.
[16] Q. Jing and D. Liu, “Study of atmospheric attenuation characteristics of terahertz wave based on line-by-line integration,” International Journal of Communication Systems, vol. 31, no. 12, 2018
[17] M. R. Ahadiat, P. Azmi, and A. Haghbin, “BER performance analysis of MIMO-OFDM communication systems using iterative technique over indoor power line channels in an impulsive noise environment,” Journal of Information Systems and Telecommunication, vol. 4, no. 1, p. 34 – 41, 2016.
[18] M. J. Tanakian and M. Mehrjoo, “Balancing agility and stability of wireless link quality estimators,” Journal of Information Systems and Telecommunication, vol. 7, no. 3, p. 184 – 192, 2019.
[19] M. Haque and T. Shimamura, “Spectrum sensing of ofdm signals utilizing higher order statistics under noise uncertainty environments in cognitive radio systems,” Journal of Information Systems and Telecommunication, vol. 11, no. 3, p. 251 – 259, 2023.
[20] S. H. Mostafavi-Amjad, V. Solouk, and H. Kalbkhani, “Energy-efficient user pairing and power allocation for granted uplink-noma in uav communication systems,” Journal of Information Sys- tems and Telecommunication, vol. 10, no. 40, p. 312 – 323, 2022.