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Wireless Networks
Erschienen in: Wireless Networks 7/2023

03.06.2023 | Original Paper

Effect of block size on BER performance of inverse filtering based MIMO FBMC

verfasst von: Mohit Kumar Srivastava, Manoj Kumar Shukla, Arun Kumar Singh

Erschienen in: Wireless Networks | Ausgabe 7/2023

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Abstract

Filter bank multicarrier (FBMC) is a novel next-generation data transfer technique. FBMC has a large number of benefits over conventional orthogonal frequency division multiplexing (OFDM) techniques. The FBMC scheme suffers from imaginary interference, which degrades the bit error rate (BER) performance at the receiver. In the recent past, inter carrier interference (ICI)-free Alamouti-coded FBMC frame and block repetition schemes for BER improvement were discussed. However, in the analysis, various interfering terms are neglected. In this work to reduce ICI and inter symbol interference (ISI), the concept of inverse filtering is applied while considering other interfering terms. Inverse filtering can be used to reduce the negative impacts of the ICI and ISI. This is determined by mathematical modelling that includes the ICI, ISI, and other interfering parameters. The simulation is performed in MATLABR software. The obtained BER at an SNR of 15 dB is 2.3 × 10−4.The simulation results are also compared with some of the recent methods, and it has been found that the proposed scheme is better in comparison to the considered recent methods.
Vorheriger Artikel Outage probability optimization of UAV relay system based on elliptical trajectory
Nächster Artikel Deep learning aided wireless interference identification for coexistence management in the ISM bands

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Literatur
1.
Cianca, E., De Sanctis, M., & Ruggieri, M. (2005). Convergence towards 4g: A novel view of integration. Wireless Personal Communications, 33, 327–336.CrossRef
2.
Wang, X. (2005). OFDM and its application to 4G. in 14th Annual International Conference on Wireless and Optical Communications, WOCC, p. 69.
3.
Chen, L., & Ze-yao, H. (2008). OFDM—main technology of 4G mobile communication system. Computer TechNology & Development, 3.
4.
Anastasi, G., Grillo, D., & Lenzini, LuciaNo. (1997). An access protocol for speech/data/video integration in TDMA-based advanced mobile systems. IEEE Journal on Selected Areas in Communications, 15(8), 1498–1510.CrossRef
5.
Masui, H., Ohgoshi, Y., YaNo, T., & Doi, N. (2001). U.S. patent no. 6,269,088. U.S. Patent and Trademark Office.
6.
Zaki, Y., Zhao, L., Goerg, C., & Timm-Giel, A. (2011). LTE mobile network virtualization. Mobile Networks & Applications, 16(4), 424–432.CrossRef
7.
Abd El-Samie, F. E., Al-kamali, F. S., Dessouky, M. I., Sallam, B. M., & Shawki, F. (2010). Performance enhancement of SC-FDMA systems using a companding technique. Annals of telecommunications-annales des télécommunications, 65, 293–300.CrossRef
8.
Ramakrishnan, B., Kumar, A., Chakravarty, S., Masud, M., & Baz, M. (2021). Analysis of FBMC waveform for 5G network based smart hospitals. Applied Sciences, 1(19), 8895.CrossRef
9.
Kim, J., Park, Y., Weon, S., Jeong, J., Choi, S., & Hong, D. (2018). A new filter-bank multicarrier system: The linearly processed FBMC system. IEEE Transactions on Wireless Communications, 17(7), 4888–4898.CrossRef
10.
Caus, M., Pérez-Neira, A. I., & García-Armada, A. (2021). A discrete bit loading algorithm for FBMC/OQAM. IEEE Signal Processing Letters, 19(6), 324–327.
11.
Varga, L. & Kollár, Z. (2013). Low complexity FBMC transceiver for FPGA implementation. in 2013 23rd International Conference Radioelektronika (RADIOELEKTRONIKA), IEEE, pp. 219–223.
12.
Xu, Mu., Zhang, J., Feng, Lu., Wang, J., Cheng, L., Cho, H. J., Khalil, M. I., Guidotti, D., & Chang, G.-K. (2016). FBMC in next-generation mobile fronthaul networks with centralized pre-equalization. IEEE Photonics Technology Letters, 28(18), 1912–1915.CrossRef
13.
Bellanger, M., Ruyet, D. L., Roviras, D. & Terre, M. (2010). FBMC physical layer: A primer. PHYDYAS.
14.
He, Z., Zhou, L., Chen, Y. & Ling, X.(2017). Filter optimization of out-of-band emission and BER analysis for FBMC-OQAM system in 5G. in 2017 IEEE 9th International Conference on Communication Software and Networks (ICCSN), IEEE, pp. 56–60.
15.
Xu, Y., Feng, Z., Zou, J., Kong, D., Xin, Y., & Jiang, T. (2021). An imaginary interference-free method for MIMO precoding in FBMC/OQAM systems. IEEE Transactions on Broadcasting, 67(3), 642–650.CrossRef
16.
Harbi, Y.J. & Burr, A.G. (2016). On ISI and ICI cancellation for FBMC/OQAM system using iterative decoding and ML detection. In 2016 IEEE wireless communications and networking conference, IEEE, pp. 1–6.
17.
Nam, H., Choi, M., Han, S., Kim, C., Choi, S., & Hong, D. (2016). A new filter-bank multicarrier system with two prototype filters for QAM symbols transmission and reception. IEEE Transactions on Wireless Communications, 15(9), 5998–6009.CrossRef
18.
Lélé, C., Siohan, P., & Legouable, R. (2010). The alamouti scheme with CDMA-OFDM/OQAM. EURASIP Journal on Advances in Signal Processing, 2010, 1–13.CrossRef
19.
Kong, D., Xia, X. G., & Jiang, T. (2015). An Alamouti coded CP-FBMC-MIMO system with two transmit antennas. Science China Information Sciences, 10(58), 1–6.
20.
Renfors, M., Ihalainen, T. & Stitz, T.H. (2010). A block-Alamouti scheme for filter bank based multicarrier transmission. in 2010 European Wireless Conference (EW), IEEE, pp. 1031–1037.
21.
Na, D., & Choi, K. (2017). Generalization of the phase shift condition in “intrinsic ICI-free alamouti coded FBMC.” IEEE Communications Letters, 21(8), 1747–1750.CrossRef
22.
Kong, D., Zheng, X., Zhang, Y., & Jiang, T. (2020). Frame repetition: A solution to imaginary interference cancellation in FBMC/OQAM systems. IEEE Transactions on Signal Processing, 68, 1259–1273.MathSciNetCrossRefMATH
23.
Kong, D., Zheng, X., Tian, Y., Jiang, T., & Zhang, Y. (2022). Alamouti code based on block repetition in FBMC/OQAM systems. Digital Communications and Networks, 8(1), 58–63.CrossRef
24.
Zafar, A. (2018). Filter bank based multicarrier systems for future wireless networks. University of Surrey.
25.
Palomar, D. P., Bengtsson, M., & Ottersten, B. (2005). Minimum BER linear transceivers for MIMO channels via primal decomposition. IEEE Transactions on Signal Processing, 53(8), 2866–2882.MathSciNetCrossRefMATH
26.
Vaigandla, K. K., & Benita, J. (2022). Study and analysis of multi carrier modulation techniques–FBMC and OFDM. Materials Today: Proceedings, 58, 52–56.
27.
Adarsh, A., Pathak, S., Chauhan, D. S., & Kumar, B. (2023). Low-latency and high-reliability FBMC modulation scheme using optimized filter design for enabling NextG real-time smart healthcare applications. The Journal of Supercomputing, 79(4), 3643–3665.CrossRef
28.
Wang, F., Qu, D., Jiang, T. & Farhang-Boroujeny, B. (2015). Tail shortening by virtual symbols in FBMC-OQAM signals. In 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE), IEEE, pp. 157–161.
29.
Alzubi, O. A., Chen, T. M., Alzubi, J. A. A., Rashaideh, H., & Al-Najdawi, N. (2016). Secure channel coding schemes based on algebraic-geometric codes over Hermitian curves. Journal of Universal Computer Science, 22(4), 552–566.MathSciNet
30.
Sholiyi, A., Alzubi, J.A., Alzubi, O.A., Almomani, O. & O’Farrell, T. (2016). Near capacity irregular turbo code. arXiv preprint arXiv:​1604.​01358.
31.
Alzubi, J. A., Alzubi, O. A., & Chen, T. M. (2014). Forward error correction based on algebraic-geometric theory. Springer International Publishing.CrossRefMATH
32.
33.
Varlamov, V. O., Lobov, E. M., & Lobova, E. O. (2023). Investigation of FBMC-OQAM equalization with real interference prediction algorithm properties for MIMO transmission scheme. Sensors, 23(4), 2111.CrossRef
34.
Zakaria, R., & Le Ruyet, D. (2016). Partial interference cancellation with maximum likelihood sequence detection in FBMC spatial multiplexing system. EURASIP Journal on Advances in Signal Processing, 1, 1–12.
35.
Bedoui, A., & Et-tolba, M. (2021). A deep neural network-based interference mitigation for MIMO-FBMC/OQAM systems. Frontiers in Communications and Networks, 2, 728982.CrossRef
Metadaten
Titel
Effect of block size on BER performance of inverse filtering based MIMO FBMC
verfasst von
Mohit Kumar Srivastava
Manoj Kumar Shukla
Arun Kumar Singh
Publikationsdatum
03.06.2023
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 7/2023
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-023-03388-4

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