Skip to main content
Log in

Optimal channel estimation and interference cancellation in MIMO-OFDM system using MN-based improved AMO model

The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

In recent years, MIMO-OFDM plays a significant role due to its high-speed transmission rate. Various research studies have been carried out regarding the channel estimation to obtain optimal output without affecting the system performances. But due to increased bit error rate achieving optimal channel estimation is considered as a challenging task. Therefore, this paper proposes the modified Newton’s (MN)-based Improved Animal Migration Optimization (IAMO) algorithm in MIMO-OFDM system. The significant objective of this proposed approach involves the minimization of bit error rate and to enhance the system performance. In this paper, a modified Newton’s method is utilized to determine the discover capability and to speed up the convergence rate thereby obtaining the optimum search space positions. In addition to this, the proposed method is utilized to restrict the interference in the MIMO-OFDM systems. Finally, the performance of the proposed method is compared with other channel estimation methods to determine the effectiveness of the system. The experimental and comparative analyses are carried out, and the results demonstrate that the proposed approach provides better frequency-selective channels than other state-of-the-art methods .

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

References

  1. Ma X, Yang F, Liu S, Song J, Han Z (2018) Sparse channel estimation for MIMO-OFDM systems in high-mobility situations. IEEE Trans Veh Technol 67(7):6113–6124

    Article  Google Scholar 

  2. Nandi S, Pathak NN, Nandi A (2020) A novel adaptive optimized fast blind channel estimation for cyclic prefix assisted space–time block coded MIMO-OFDM systems. Wireless personal communications. pp. 1–7.

  3. Araújo DC, De Almeida AL, Da Costa JP, de Sousa RT (2019) Tensor-based channel estimation for massive MIMO-OFDM systems. IEEE Access 7:42133–42147

    Article  Google Scholar 

  4. Gaikwad RB, Shrivastava A (2019) Comparison of semi blind channel estimation techniques with old techniques for MIMO-OFDM systems. Int Res J Eng Tech (IRJET) 06(02):821–826

    Google Scholar 

  5. Qin Q, Gui L, Gong B, Luo S (2018) Sparse channel estimation for massive MIMO-OFDM systems over time-varying channels. IEEE Access 6:33740–33751

    Article  Google Scholar 

  6. Shafin R, Jiang M, Ma S, Piazzi L, Liu L (2018) Joint parametric channel estimation and performance characterization for 3D massive MIMO OFDM systems. In2018 IEEE International conference on communications (ICC) (pp. 1–6). IEEE.

  7. Kizawa M, Ikegami T (2020) Iterative cancellation for inter-block-interference on LDPC coded MIMO-OFDM Systems. In2020 IEEE 91st Vehicular technology conference (VTC2020-Spring) (pp. 1–5). IEEE.

  8. Zaib A, Masood M, Ali A, Xu W, Al-Naffouri TY (2016) Distributed channel estimation and pilot contamination analysis for massive MIMO-OFDM systems. IEEE Trans Commun 64(11):4607–4621

    Article  Google Scholar 

  9. Wu S, Kuang L, Ni Z, Huang D, Guo Q, Lu J (2016) Message-passing receiver for joint channel estimation and decoding in 3D massive MIMO-OFDM systems. IEEE Trans Wireless Commun 15(12):8122–8138

    Article  Google Scholar 

  10. Zhou Z, Fang J, Yang L, Li H, Chen Z, Blum RS (2017) Low-rank tensor decomposition-aided channel estimation for millimeter wave MIMO-OFDM systems. IEEE J Sel Areas Commun 35(7):1524–1538

    Article  Google Scholar 

  11. Gowthul Alam MM, Baulkani S (2017) Reformulated query-based document retrieval using optimised kernel fuzzy clustering algorithm. Int J Bus Intell Data Min 12(3):299

    Google Scholar 

  12. Sundararaj V (2016) An efficient threshold prediction scheme for wavelet based ECG signal noise reduction using variable step size firefly algorithm. Int J Intell Eng Syst 9(3):117–126

    Google Scholar 

  13. Gowthul Alam MM, Baulkani S (2019) Geometric structure information based multi-objective function to increase fuzzy clustering performance with artificial and real-life data. Soft Comput 23(4):1079–1098

    Article  Google Scholar 

  14. Sundararaj V (2019) Optimised denoising scheme via opposition-based self-adaptive learning PSO algorithm for wavelet-based ECG signal noise reduction. Int J Biomed Eng Technol 31(4):325

    Article  Google Scholar 

  15. Gowthul Alam MM, Baulkani S (2019) Local and global characteristics-based kernel hybridization to increase optimal support vector machine performance for stock market prediction. Knowl Inf Syst 60(2):971–1000

    Article  Google Scholar 

  16. Hassan BA, Rashid TA (2020) Datasets on statistical analysis and performance evaluation of backtracking search optimisation algorithm compared with its counterpart algorithms. Data in Brief 28:105046

    Article  Google Scholar 

  17. Hassan BA (2020) CSCF: a chaotic sine cosine firefly algorithm for practical application problems. Neural Comput Appl 33(12):7011–7030

    Article  Google Scholar 

  18. Rejeesh MR (2019) Interest point based face recognition using adaptive neuro fuzzy inference system. Multimed Tools Appl 78(16):22691–22710

    Article  Google Scholar 

  19. Sundararaj V, Muthukumar S, Kumar RS (2018) An optimal cluster formation based energy efficient dynamic scheduling hybrid MAC protocol for heavy traffic load in wireless sensor networks. Comput Secur 77:277–288

    Article  Google Scholar 

  20. Sundararaj V, Anoop V, Dixit P, Arjaria A, Chourasia U, Bhambri P, Rejeesh MR, Sundararaj R (2020) CCGPA-MPPT: cauchy preferential crossover-based global pollination algorithm for MPPT in photovoltaic system. Prog Photovolt Res Appl 28(11):1128–1145

    Article  Google Scholar 

  21. Vinu S (2019) Optimal task assignment in mobile cloud computing by queue based ant-bee algorithm. Wirel Pers Commun 104(1):173–197

    Article  Google Scholar 

  22. Rejeesh MR, Thejaswini P (2020) MOTF: multi-objective optimal trilateral filtering based partial moving frame algorithm for image denoising. Multimed Tools Appl 79(37):28411–28430

    Article  Google Scholar 

  23. Bhandari R, Jadhav S (2019) Novel spectral efficient technique for MIMO-OFDM channel estimation with reference to PAPR and BER analysis. Wireless Pers Commun 104(4):1227–1242

    Article  Google Scholar 

  24. Kaur H, Khosla M, Sarin RK (2019) Hybrid type-2 fuzzy based channel estimation for MIMO-OFDM system with doppler offset influences. Wireless Pers Commun 108(2):1131–1143

    Article  Google Scholar 

  25. Mashhadi MB, Gunduz D (2020) Pruning the pilots: deep learning-based pilot design and channel estimation for MIMO-OFDM systems. arXiv preprint arXiv:2006.11796.

  26. He M, Huang C (2019) Self-interference cancellation for full-duplex massive MIMO OFDM with single RF Chain. IEEE Wireless Communications Letters 9(1):26–29

    Article  Google Scholar 

  27. Huang Y, He Y, Luo Q, Shi L, Wu Y (2018) Channel estimation in MIMO–OFDM systems based on a new adaptive greedy algorithm. IEEE Wireless Communications Letters 8(1):29–32

    Article  Google Scholar 

  28. VenkateswaraRao N, Venkateswarlu C (2017) Hybrid ABC optimization based interference cancellation in MIMO-OFDM. In2017 2nd International conference on communication and electronics systems (ICCES) (pp. 21–25)

  29. Priyanjali KS, Nageswaramma O, Dikshit AK, Mrudula S. (2016 May 20) Threshold based soft partial parallel interference cancellation for MIMO-OFDM system. In2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) (pp. 861–865). IEEE.

  30. Tripta FA, Kumar SB, Saha TC (2019) Wavelet decomposition based channel estimation and digital domain self-interference cancellation in in-band full-duplex OFDM systems. In2019 URSI Asia-Pacific Radio Science Conference (AP-RASC) (pp. 1–4). IEEE.

  31. Chang YK, Ueng FB, Shen YS, Liao CY (2019) Joint kalman channel estimation and turbo equalization for MIMO OFDM systems over fast fading channels. KSII Trans Internet Info Sys (TIIS) 13(11):5394–409

    Google Scholar 

  32. Sundararaj V, Selvi M (2021) Opposition grasshopper optimizer based multimedia data distribution using user evaluation strategy. Multimed Tools Appl. https://doi.org/10.1007/s11042-021-11123-4

  33. Venkateswarlu C, Rao NV (2021) A robust and secure time-domain interference cancellation using optimization method in MIMO-OFDM system. Int J Electron Secur Digit Forensics 13(2):197–218

    Article  Google Scholar 

  34. Grabner MJ, Li X, Fu S (2019) An adaptive BLAST successive interference cancellation method for high data rate perfect space-time coded MIMO systems. IEEE Trans Veh Technol 69(2):1542–1553

    Article  Google Scholar 

  35. Nandi S, Pathak NN, Nandi A (2020) A Novel Adaptive Optimized Fast Blind Channel Estimation for Cyclic Prefix Assisted Space–Time Block Coded MIMO-OFDM Systems. Wireless Personal Communications. pp:1–7

  36. Srivastava S, Kumar MS, Mishra A, Chopra S, Jagannatham AK, Hanzo L (2020 ) Sparse Doubly-Selective Channel Estimation Techniques for OSTBC MIMO-OFDM Systems: A Hierarchical Bayesian Kalman Filter Based Approach. IEEE Transactions on Communications.

  37. Lai Z, Feng X, Yu H (2019) an improved animal migration optimization algorithm based on interactive learning behavior for high dimensional optimization problem. In2019 International conference on high performance big data and intelligent systems (HPBD&IS) (pp. 110–115). IEEE

  38. Lai Z, Hu X, Jiang C (2020) An intelligent algorithm with interactive learning mechanism for high‐dimensional optimization problem based on improved animal migration optimization. Concurrency and Computation: Practice and Experience.pp:e5774

  39. Mellor DJ, Beausoleil NJ, Littlewood KE, McLean AN, McGreevy PD, Jones B, Wilkins C (2020) The 2020 five domains model: including human-animal interactions in assessments of animal welfare. Animals 10(10):1870

    Article  Google Scholar 

  40. O’Bryan L, Beier M, Salas E (2020) How approaches to animal swarm intelligence can improve the study of collective intelligence in human teams. J Intelligence 8(1):9

    Article  Google Scholar 

  41. Tilles PFC, Petrovskii SV (2016) How animals move along? exactly solvable model of super diffusive spread resulting from animal’s decision making. J Math Biol 73(1):227–255

    Article  MathSciNet  Google Scholar 

  42. Nishani HP, Weerakoon S, Fernando TG, Liyanage M (2018) Weerakoon-Fernando method with accelerated third-order convergence for systems of nonlinear equations. Int J Math Model Numer Optimi 8(3):287–304

    Google Scholar 

  43. Rasheed M, Shihab S, Rashid T, Enneffati M (2021) Some step iterative method for finding roots of a nonlinear equation. J Al-Qadisiyah Comp Sci Math 13(1):Page-95

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chittetti Venkateswarlu.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Venkateswarlu, C., Rao, N.V. Optimal channel estimation and interference cancellation in MIMO-OFDM system using MN-based improved AMO model. J Supercomput 78, 3402–3424 (2022). https://doi.org/10.1007/s11227-021-03983-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-021-03983-2

Keywords

Navigation