Filter Bank Multicarrier Modulation Techniques for 5G and Beyond Wireless Communication Systems



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Submitted Feb 24, 2022
Published Mar 21, 2022
10.24018/ejece.2022.6.2.423

Abstract viewed = 632 times

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Higher data rates, higher mobility, lower latency, and better quality of service are the prime requirements for future communication systems. It is expected to provide connectivity to the Internet of everything, time-sensitive/time-engineered application, and service to high-fidelity holographic society. Its performance in terms of data rate, latency, synchronization, security, and reliability will be much better compared to 4G and 5G mobile communication systems. This paper investigates the performance of the pulse shaping-based filter bank multicarrier (FBMC) modulation technique used in 5G mobile communication systems. Simulation results show that the FBMC system has a better performance compared to the conventional orthogonal frequency division multiplexing (OFDM) system in terms of many parameters such as achievable channel capacity, signal to noise ratio, time, and frequency response, out of band leakage, etc.

Keywords: Division Multiplexing, Filter Bank Multicarrier, Modulation Technique, Novel orthogonal Multiple Access Technique, orthogonal frequency, spectrum Efficiency

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References

  1. Lei Jiang, Bo Liu, et al. Flexible Filter Bank Multi-Carriers PON Based on Two-Dimensional Multiple Probabilistic Shaping Distribution. IEEE Access, 2019; 7:1793-1799.
     Google Scholar
  2. A.S Kang, R Vig. Simulation Analysis of Prototype Filter Bank Multicarrier Cognitive Radio Under Different Performance Parameters. Indonesian Journal of Electrical Engineering and Informatics, 2015; 3(3):157-166.
     Google Scholar
  3. V K Singh, M F. Flanagan and Barry Cardiff. Generalized Least Squares Based Channel Estimation for FBMC-OQAM. IEEE Access, 2019; 7:129411-129420.
     Google Scholar
  4. S Mahama, D K P Asiedu, et al. Multi-User Wireless Information and Power Transfer in FBMC-Based IoT Networks. IEEE Access, 2019; 2:545-563.
     Google Scholar
  5. J Dang, Z Zhang, L Wu, and Y Wu. A New Framework of Filter Bank Multi-Carrier: Getting Rid of Subband Orthogonality. IEEE Transactions on Communications, 2017; 65(9):3922-3932.
     Google Scholar
  6. F Li, K Zheng, H Zhao1 and W Xiang. QAM Signal Transmission Based on Matrix Model in Filter-Bank Multicarrier Systems. IEEE Access, 2018; 6:63987-63998.
     Google Scholar
  7. R Nissel, S Schwarz and M Rupp. Filter Bank Multicarrier Modulation Schemes for Future Mobile Communications. IEEE Journal on Selected Areas in Communications, 2017; 35(8):1768 ? 1782.
     Google Scholar
  8. Yadav Shatrughna Prasad, Bera Subhash Chandra. PAPR Reduction for Improved Efficiency of OFDM Modulation for Next Generation Communication Systems. International Journal of Electrical and Computer Engineering, 2016; 6(5):2310-2321.
     Google Scholar
  9. Yadav Shatrughna Prasad, Bera Subhash Chandra. Reduction of PAPR in SC-FDMA System using Pulse Shaping Technique. International Journal of Applied Engineering Research, 2015; 10(23): 43509-43513.
     Google Scholar
  10. B. F. Boroujeny. OFDM versus filter bank multicarrier. IEEE Signal Process. Mag, 2011; 28(3):92?112.
     Google Scholar
  11. F. Schaich and T. Wild. Waveform contenders for 5G?OFDM vs. FBMC vs. UFMC. Proc. Int. Symp. Commun, Control Signal Process, Athens, Greece, 2014; 457?460.
     Google Scholar
  12. T. Yunzheng, L. Long, L. Shang, and Z. Zhi. A survey: Several technologies of non-orthogonal transmission for 5G. China Commun., 2015; 12(10):1?15.
     Google Scholar
  13. F. Schaich, T. Wild, and Y. Chen. Waveform contenders for 5G?Suitability for short packet and low latency transmissions. Proc. IEEE 79th Veh. Technol. Conf. Seoul, South Korea, 2014; 1?5.
     Google Scholar
  14. A. Viholainen, T. H. Stitz, J. Alhava, T. Ihalainen, and M. Renfors. Complex modulated critically sampled filter banks based on cosine and sine modulation. Proc. IEEE Int. Symp. Circuits Syst., 1. Phoenix-Scottsdale, AZ, USA. 2002; 833?836.
     Google Scholar
  15. A. I. P?rez-Neira et al., ?MIMO signal processing in offset-QAM based filter bank multicarrier systems. IEEE Trans. Signal Process. 2016; 64(21):5733?5762.
     Google Scholar
  16. C. Sexton, Q. Bodinier, A. Farhang, N. Marchetti, F. Bader, and L. A. DaSilva. Enabling asynchronous machine-type D2D communication using multiple waveforms in 5G. IEEE Internet Things J., 2018; 5(2): 1307?1322.
     Google Scholar
  17. B. Lim and Y.-C. Ko. SIR analysis of OFDM and GFDM waveforms with timing offset, CFO, and phase noise. IEEE Trans. Wireless Commun., 2017; 16(10): 6979?6990.
     Google Scholar
  18. S. Mahama, Y. J. Harbi, A. G. Burr, and D. Grace. Design and convergence analysis of an IIC-Based BICM-ID receiver for FBMCQAM systems. IEEE Open J. Commun. Soc., 2020; 563?577.
     Google Scholar
  19. G. Wunder et al. 5GNOW: Non-orthogonal, asynchronous waveforms for future mobile applications. IEEE Commun. Mag., 2014; 52(2): 97?105.
     Google Scholar
  20. M. Pischella, R. Zakaria, and D. Le Ruyet. Resource block-level power allocation in asynchronous multi-carrier D2D communications. IEEE Commun. Lett., 2017; 21(4): 813?816.
     Google Scholar
  21. R. Zakaria and D. Le Ruyet. A novel filter-bank multicarrier scheme to mitigate the intrinsic interference: Application to MIMO systems. IEEE Trans. Wireless Commun., 2012; 11(3):1112?1123.
     Google Scholar