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An improved fuzzy logic-based small cell deployment in NOMA-HetNet: a novel sun flower-based tunicate swarm optimization-oriented multi objective concept

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Abstract

NOMA can achieve greater spectrum effectiveness than OMA by utilizing power domain multiplexing. The performance of NOMA in a HetNet having non-uniform small cell deployment is investigated in this research, with crucial performance metrics such as distance, channel gain, reference signal power, energy efficiency, coverage probability, achievable rate, and QoS being examined. To begin, a NOMA-oriented HetNet model is created, with users paired according to the suggested user pairing strategy. Next, taking into account the channel quality from the NOMA users to the BSs, the distribution of order statistics for distances among distinct NOMA users and the serving BS is provided. An improved fuzzy logic system is utilized for cell dimensioning and a novel SF-TSO algorithm is used for automatic base station placement. Here, the trapezoidal fuzzy membership limits are optimized by the novel SF-TSO with the intention of attaining the multi objective or the fitness function. On this foundation, we show how different networking characteristics, like the SINR threshold and BS density, affect the considered parameters of NOMA users. In addition, an analysis is provided to offer insight into the EE of the system under consideration. Furthermore, detailed simulations as well as comparisons are carried out, demonstrating the benefits of NOMA over OMA in the HetNet system under consideration.

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Abbreviations

NOMA:

Non-orthogonal multiple access

FBSs:

Femto base stations

RBs:

Resource blocks

OMA:

Orthogonal multiple access

CS:

Compressive sensing

HetNet:

Heterogeneous network

R-WFISTA:

Restricted weighted fast iterative shrinkage-thresholding algorithm

J-SA-GEE-PA:

Joint subcarrier assignment and global energy-efficient power allocation

BS:

Base station

EH:

Energy-harvesting

SF-TSO:

Sun flower-based tunicate swarm optimization

JT-CoMP:

Joint transmission coordinated multi-point

SINR:

Signal-to-interference-plus-noise-ratio

WNV:

Wireless network virtualization

MIMO:

Multiple-input multiple output

UNC:

Unlimited NOMA clustering

SE:

Spectral efficiency

LNC:

Limited NOMA clustering

EE:

Energy-efficiency

RANs:

Radio access networks

SCs:

Small-cell

TS:

Time slotting

SBS:

Small base station

MU:

Macro users

MC:

Macro-cell

OMU:

Offloaded macro users

MBS:

Macro base station

PU:

Pairing user

QoS:

Quality of service

CCU:

Cell centre users

SIC:

Successive interference cancellation

CEU:

Cell edge users

MOP:

Multi-objective problem

PA:

Power allocation

SOP:

Single objective problem

PA-IA-CB:

Power allocation-based interference alignment and coordinated beamforming

NC:

Non-cooperative

AWGN:

Additive white Gaussian noise

References

  1. Shin W, Vaezi M, Lee B, Love D J, Lee J and Poor H V 2017 Coordinated beamforming for multi-cell MIMO-NOMA. IEEE Commun. Lett. 21(1): 84–87

    Article  Google Scholar 

  2. Wildemeersch M, Quek T Q S, Kountouris M, Rabbachin A and Slumpet C H 2014 Successive interference cancellation in heterogeneous networks. IEEE Trans. Commun. 62(12): 4440–4453

    Article  Google Scholar 

  3. Di B, Song L and Li Y 2016 Sub-channel assignment, power allocation, and user scheduling for non-orthogonal multiple access networks. IEEE Trans. Wireless Commun. 15(11): 7686–7698

    Article  Google Scholar 

  4. Zhang Z, Sun H and Hu R Q 2017 Downlink and uplink non-orthogonal multiple access in a dense wireless network. IEEE J. Sel. Areas Commun. 35(12): 2771–2784

    Article  Google Scholar 

  5. Khan W U, Li X, Ihsan A, Ali Z, Elhalawany B M and Sidhu G A S 2021 Energy efficiency maximization for beyond 5G NOMA-enabled heterogeneous networks. Peer Peer Netw. Appl. 14: 3250–3264

    Article  Google Scholar 

  6. Fu Y, Zhang M, Salaün L, Sung C W and Chen C S 2020 Zero-forcing oriented power minimization for multi-cell MISO-NOMA systems: A joint user grouping, beamforming, and power control perspective. IEEE J. Sel. Areas Commun. 38(8): 1925–1940

    Article  Google Scholar 

  7. Fu Y, Salaün L, Sung C W and Chen C S 2018 Subcarrier and power allocation for the downlink of multicarrier NOMA systems. IEEE Trans. Veh. Technol. 67(12): 11833–11847

    Article  Google Scholar 

  8. Ali S, Hossain E and Kim D I 2017 Non-orthogonal multiple access (NOMA) for downlink multiuser MIMO systems: User clustering, beamforming, and power allocation. IEEE Access. 5: 565–577

    Article  Google Scholar 

  9. Zhang S, Zhang N, Kang G and Liu Z 2018 Energy and spectrum efficient power allocation with NOMA in downlink HetNets. Phys. Commun. 31: 121–132

    Article  Google Scholar 

  10. Islam S M R, Avazov N, Dobre O A and Kwak K S 2017 Power-domain non-orthogonal multiple access (NOMA) in 5G systems: Potentials and challenges. IEEE Commun. Surveys Tuts. 19(2): 721–742

    Article  Google Scholar 

  11. Tang J, Luo J, Liu M, So D K C, Alsusa E, Chen G, Wong K K and Chambers J A 2019 Energy efficiency optimization for NOMA with SWIPT. IEEE J. Sel. Topics Signal Process. 13(3): 452–466

    Article  Google Scholar 

  12. Sobhi-Givi S, Shayesteh M G and Kalbkhani H 2020 Energy-efficient power allocation and user selection for mmWave-NOMA transmission in M2M communications underlaying cellular heterogeneous networks. IEEE Trans. Veh. Technol. 69(9): 9866–9881

    Article  Google Scholar 

  13. Nasser A, Muta O, Gacanin H and Elsabrouty M 2021 Joint user pairing and power allocation with compressive sensing in NOMA systems. IEEE Wireless Commun. Lett. 10(1): 151–155

    Article  Google Scholar 

  14. Ali M S, Tabassum H and Hossain E 2017 Dynamic user clustering and power allocation for uplink and downlink non-orthogonal multiple access (NOMA) systems. IEEE Access. 4(99): 6325–6343

    Google Scholar 

  15. Higuchi K and Benjebbour A 2015 Non-orthogonal multiple access (NO MA) with successive interference cancellation for future radio access. IEICE Trans. Commun. 98(3): 403–414

    Article  Google Scholar 

  16. Nasser A, Muta O, Gacanin H and Elsabrouty M 2021 Non-cooperative game based power allocation for energy and spectrum efficient downlink NOMA HetNets. IEEE Access. 9: 136334–136345

    Article  Google Scholar 

  17. Chen L, Ma L, Xu Y and Leung V C M 2019 Hypergraph spectral clustering based spectrum resource allocation for dense NOMA-HetNet. IEEE Wirel. Commun. Lett. 8(1): 305–308

    Article  Google Scholar 

  18. Nasser A, Muta O, Elsabrouty M and Gacanin H 2019 Compressive sensing based spectrum allocation and power control for NOMA HetNets. IEEE Access. 7: 98495–98506

    Article  Google Scholar 

  19. Baidas M W, Al-Mubarak M, Alsusa E and Awad M K 2019 Joint Subcarrier assignment and global energy-efficient power allocation for energy-harvesting two-tier downlink NOMA Hetnets. IEEE Access. 7: 163556–163577

    Article  Google Scholar 

  20. Xu B, Chen Y, Carrión J R and Zhang T 2017 Resource allocation in energy-cooperation enabled two-tier NOMA HetNets toward green 5G. IEEE J. Sel. Areas Commun. 35(12): 2758–2770

    Article  Google Scholar 

  21. Ni D, Hao L, Tran Q T and Qian X 2018 Power allocation for downlink NOMA heterogeneous networks. IEEE Access. 6: 26742–26752

    Article  Google Scholar 

  22. Rezvani S, Yamchi N M, Javan M R and Jorswieck E A 2021 Resource allocation in virtualized CoMP-NOMA HetNets: Multi-connectivity for joint transmission. IEEE Trans. Commun. 69(6): 4172–4185

    Article  Google Scholar 

  23. Swami P, Bhatia V, Vuppala S and Ratnarajah T 2021 User fairness in NOMA-HetNet using optimized power allocation and time slotting. IEEE Syst. J. 15(1): 1005–1014

    Article  Google Scholar 

  24. Swami P, Bhatia V, Vuppala S and Ratnarajah T 2019 On user offloading in NOMA-HetNet using repulsive point process. IEEE Syst. J. 13(2): 1409–1420

    Article  Google Scholar 

  25. Nasser A, Muta O, Elsabrouty M and Gacanin H 2019 Interference mitigation and power allocation scheme for downlink MIMO–NOMA HetNet. IEEE Trans. Veh. Technol. 68(7): 6805–6816

    Article  Google Scholar 

  26. Mirjalili S and Lewis A 2016 The whale optimization algorithm. Adv. Eng. Softw. 95: 51–67

    Article  Google Scholar 

  27. Samuel Manoharan J 2020 Population based metaheuristics algorithm for performance improvement of feed forward Neural Network. J. Soft Comput. Paradigm. 2: 36–46

    Article  Google Scholar 

  28. Gomes G F, da Cunha G S and Ancelotti A C 2019 A sunflower optimization (SFO) algorithm applied to damage identification on laminated composite plates. Eng. Comput. 35: 619–626

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Sethu Institute of Technology, Kariapatti, Virudhunagar, India

    D Anu Disney & A Merline

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  1. D Anu Disney
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  2. A Merline
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Correspondence to D Anu Disney.

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Disney, D.A., Merline, A. An improved fuzzy logic-based small cell deployment in NOMA-HetNet: a novel sun flower-based tunicate swarm optimization-oriented multi objective concept. Sādhanā 48, 67 (2023). https://doi.org/10.1007/s12046-023-02123-1

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  • DOI: https://doi.org/10.1007/s12046-023-02123-1

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