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Low-latency and High-Reliability FBMC Modulation scheme using Optimized Filter design for enabling NextG Real-time Smart Healthcare Applications

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Abstract

This paper presents a prototype filter design using the orthant optimization technique to assist a filter bank multicarrier (FBMC) modulation scheme of a NextG smart e-healthcare network framework. Low latency and very high reliability are one of the main requirements of a real-time e-healthcare system. In recent times, FBMC modulation has gotten more attention due to its spectral efficiency. The characteristics of a filter bank are determined by t’s, prototype filter. A prototype filter cannot be designed to achieve an arbitrary time localization (for low latency) and frequency localization (spectral efficiency), as time and frequency spreading are conflicting goals. Hence, an optimum design needed to be achieved. In this paper, a constraint for perfect or nearly perfect reconstruction is formulated for prototype filter design and an orthant-based enriched sparse ℓ1-optimization method is applied to achieve the optimum performance in terms of higher availability of subcarrier spacing for the given requirement of signal-to-interference ratio. Larger subcarrier spacing ensures lower latency and better performance in real-time applications. The proposed FBMC system, based on an optimum design of the prototype filter, also supports a higher data rate as compared to traditional FBMC and OFDM systems, which is another requirement of real-time communication. In this paper, the solution for the different technical issues of physical layer design is provided. The presented modulation scheme through the proposed prototype filter-based FBMC can suppress the side lobe energy of the constituted filters up to large extent without compromising the recovery of the signal at the receiver end. The proposed system provides very high spectral efficiency; it can sacrifice large guard band frequencies to increase the subcarrier spacing to provide low-latency communication to support the real-time e-healthcare network.

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Data availability statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

BER:

Bit error rate

eMBB:

Enhanced mobile broad band

FBMC:

Filter bank multicarrier

FFT:

Fast Fourier transform

IoHT:

Internet of healthcare thing

ISI:

Inter-channel interference

MIMO:

Multiple input multiple output

mmtc:

Massive machine type communication

NOMA:

Non-orthogonal multiple access

NPR:

Nearly perfect reconstruction

OESOM:

Orthant-based enriched sparse ℓ1-optimization method

OFDM:

Orthogonal frequency division multiplexing

OMA:

Orthogonal multiple division access

OoB:

Out of band

OQAM:

Offset quadrature amplitude modulation

SIR:

Signal-to-interference ratio

uRLLC:

Ultra-reliable low-latency communication

References

  1. McCue TJ (2015) 117 billion market for internet of things in healthcare by 2020. Forbes Tech

  2. Lloret J, Parra L, Taha M, Tomas J (2017) An architecture and protocol for smart continuous eHealth monitoring using 5G. Comput Netw 129:340–351

    Article  Google Scholar 

  3. Adarsh A, Kumar B et al (2021) Design of an efficient cooperative spectrum for the intra-hospital cognitive radio network. Comput Mater Continua 69(1):35–49

    Article  Google Scholar 

  4. Adarsh A, Kumar B (2020) Wireless medical sensor networks for smart e-healthcare. In: Intelligent data security solutions for e-health applications. Academic Press, pp 275–292

  5. Adarsh A, Tiwari A, Kumar B (2019) Performance analysis of data sensitive adaptive MAC protocol for intra-hospital scenario. In: 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT). IEEE, pp 1–6

  6. Vouyioukas D, Maglogiannis I, Komnakos D (2007) Emergency m-health services through high-speed 3G systems: Simulation and performance evaluation. SIMULATION 83(4):329–345

    Article  Google Scholar 

  7. Istepanaian RSH, Zhang Y-T (2012) Guest editorial introduction to the special section: 4G health—the long-term evolution of m-health. IEEE Trans Inf Technol Biomed 16(1):1–5

    Article  Google Scholar 

  8. Chaudhari K, Karule PT (2014) WiMAX network-based E health service and telemedicine applications for rural and remote populations in India. In: 2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom). IEEE, pp 398–406

  9. Dasgupta P (2013) The shameful frailty of the rural healthcare system in India, Published in in sickness and in health on Asia, India, 2013

  10. Adarsh A, Pathak S, Kumar B (2021) Design and analysis of a reliable, prioritized and cognitive radio-controlled telemedicine network architecture for internet of healthcare things. Int J Comput Netw Appl (IJCNA) 8(1):54–66

    Google Scholar 

  11. Brito JMC (2016) Trends in wireless communications towards 5G networksThe influence of e-health and IoT applications. In: 2016 International Multidisciplinary Conference on Computer and Energy Science Split

  12. 5G-PPP (2015) White Paper on E-Health Vertical Sector, white paper, 5GPPP. https://5g-ppp.eu/wp-content/uploads/2014/02/5G-PPPWhite-Paper-on e-Health-Vertical-Sector.pdf

  13. Chen M, Yang J, Zhou J, Hao Y, Zhang J, Youn CH (2018) 5G-smart diabetes: toward personalized diabetes diagnosis with healthcare big data clouds. IEEE Commun Mag 56(4):16–23

    Article  Google Scholar 

  14. Chiuchisan I, Dimian M, Street U (2015) Internet of things for E-health: an approach to medical applications Department of Computer Science, Automation and Electronics, Stefan cel Mare, University, Suceava, Integrated Center for Research, Development and Innovation in Advanced Material

  15. Chen M, Ma Y, Li Y, Wu D, Zhang Y, Youn CH (2017) Wearable 2.0: enabling human-cloud integration in next generation healthcare systems. IEEE Commun Mag 55(1):54–61

    Article  Google Scholar 

  16. Bishoyi PK, Misra S (2021) Enabling green mobile-edge computing for 5G-based healthcare applications. IEEE Trans Green Commun Netw 5(3):1623–1631

    Article  Google Scholar 

  17. Ahad A, Tahir M, Yau KLA (2019) 5G-based smart healthcare network: architecture, taxonomy, challenges and future research directions. IEEE Access 7:100747–100762

    Article  Google Scholar 

  18. Ahad A, Tahir M, Aman Sheikh M, Ahmed KI, Mughees A, Numani A (2020) Technologies trend towards 5G network for smart health-care using IoT: a review. Sensors 20(14):4047

    Article  Google Scholar 

  19. Popovski P, Trillingsgaard KF, Simeone O, Durisi G (2018) 5G wireless network slicing for eMBB, URLLC, and mMTC: a communication-theoretic view. IEEE Access 6:55765–55779

    Article  Google Scholar 

  20. Cai Y, Qin Z, Cui F, Li GY, McCann JA (2017) Modulation and multiple access for 5G networks. IEEE Commun Surv Tutor 20(1):629–646

    Article  Google Scholar 

  21. Haci H, Zhu H, Wang J (2017) Performance of non-orthogonal multiple access with a novel asynchronous interference cancellation technique. IEEE Trans Commun 65(3):1319–1335

    Article  Google Scholar 

  22. Wang H, Xu L, Yan Z, Gulliver TA (2020) Low complexity MIMO-FBMC sparse channel parameter estimation for industrial big data communications. IEEE Trans Ind Inf 17(5):3422–3430

    Article  Google Scholar 

  23. Lai X (2009) Optimal design of nonlinear-phase FIR filters with prescribed phase error. IEEE Trans Signal Process 57(9):3399–3410

    Article  MATH  Google Scholar 

  24. Davidson T (2010) Enriching the art of FIR filter design via convex optimization. IEEE Signal Process Mag 27(3):89–101

    Article  Google Scholar 

  25. Viholainen A, Bellanger M, Huchard M Prototype filter and structure optimization. http://www.ict-phydyas.org/delivrables/PHYDYAS-D5-1.pdf/view

  26. Chen D, Qu D, Jiang T (2010) Novel prototype filter design for FBMC based cognitive radio systems through direct optimization of filter coefficients. In: Presented at the International Conference on Wireless Communication Signal Processing, Suzhou, China

  27. De Los Reyes JC, Loayza E, Merino P (2017) Second-order orthant-based methods with enriched Hessian information for sparse ℓ1-optimization. Comput Optim Appl 67:225–258

    Article  MATH  Google Scholar 

  28. Patzold M, Laue F (1998) Statistical properties of Jakes' fading channel simulator. In: VTC'98. 48th IEEE Vehicular Technology Conference. Pathway to Global Wireless Revolution (Cat. No. 98CH36151), 2. IEEE, pp 712–718

  29. Li Ye (2000) Pilot-symbol-aided channel estimation for OFDM in wireless systems. IEEE Trans Veh Technol 49(4):1207–1215

    Article  Google Scholar 

  30. Nissel R, Rupp M (2016) On pilot-symbol aided channel estimation in FBMC-OQAM. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, pp 3681–3685

  31. Simon MK, Vilnrotter VA (2005) Alamouti-type space-time coding for free-space optical communication with direct detection. IEEE Trans Wirel Commun 4(1):35–39

    Article  Google Scholar 

  32. Zarrinkoub H (2014) Understanding LTE with MATLAB: from mathematical modeling to simulation and prototyping. Wiley, New York

    Book  Google Scholar 

  33. Siohan P, Siclet C, Lacaille N (2002) Analysis and design of OFDM/OQAM systems based on filterbank theory. IEEE Trans Signal Process 50(5):1170–1183

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of ECE, Madanapalle Institute of Technology and Science, Madanapalle, 517325, India

    Abhinav Adarsh

  2. Department of ECE, MIET, Meerut, 250005, India

    Shashwat Pathak

  3. ECED, FGIET, Raebareli, 211004, India

    Digvijay Singh Chauhan

  4. ECED, MNNIT Allahabad, Prayagraj, 211004, India

    Basant Kumar

Authors
  1. Abhinav Adarsh
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  2. Shashwat Pathak
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  3. Digvijay Singh Chauhan
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  4. Basant Kumar
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Correspondence to Shashwat Pathak.

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Conflict of interest

The authors Dr. Abhinav Adarsh and Dr. Basant Kumar declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper titled; “Low Latency and High Reliability FBMC Modulation Scheme using Optimized Filter Design for enabling NextG Real Time Smart Healthcare Applications”.

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Adarsh, A., Pathak, S., Chauhan, D.S. et al. Low-latency and High-Reliability FBMC Modulation scheme using Optimized Filter design for enabling NextG Real-time Smart Healthcare Applications. J Supercomput 79, 3643–3665 (2023). https://doi.org/10.1007/s11227-022-04799-4

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