TRANSMITTING DATA IN 3D WIMAX CHANNEL BASED ON SISO-OFDM AND MIMO-OFDM
Keywords:
Single Input Single Output (SISO), Multiple Input; Multiple Output (MIMO), Bit Error Rate (BER), Orthogonal Frequency Division Multiplexing (OFDM), WiMAX, multipath
Abstract
This paper considers infrastructure to wireless mobile communications using Advanced-WiMAX. In this paper, the productivity performance throughput experienced the mobile users is compared in the cases of 3D SISO and 3D MIMO-channel models within a large urban cell. Re-cently, there has been substantial work and interest to expand MIMO and SISO-processing by taking into consideration in the design the elevation plane in addition to the azimuth dimension, Since the evaluation of elevation MIMO and SISO performance in 3D-channel design is needed. Bit-level simulation is performed for the channel in WiMAX operating at 2.5 GHz. The results indicate the accuracy of the 3D channel model, and the correct estimation of the 3D channel is showed. The difference in higher predicted capacity for the 3D channel model has resulted in the small-scale parameters for the SISO-case and the lower spatial correlation parameters for the MIMO-case. Different mobility speeds, the effect of the Doppler shift, several paths and the signal attenuation at a distance and with increasing frequency has been carried out in this study. Simulation runtimes are measured concerning the multi-section modulation types for both systems SISO and MIMO. Noise immunity is adversely affected by an increase in the number of spatial streams. The noise immunity is also affected by the increase in the number of antennas at the transmitters and receivers.
References
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2. Mondal B., Thomas T.A., Visotsky E., Vook F.W., Ghosh A., Nam Y.-H., Li Y., Zhang J., Zhang M., and Luo Q. 3D channel model in 3GPP, IEEE Communications Magazine, 2015, Vol. 53 (3), pp. 16-23
3. Fedosov V., Legin A., Lomakina A. Adaptive algorithm based on antenna arrays for radio communication systems, Serbian Journal of Electrical Engineering, 2017, Vol. 14, No. 3, pp. 301-312.
4. Fernández-Caramés T.M., González-López M., Escudero C.J., and Castedo L. Performance evaluation of multiple-antenna IEEE 802.11 p transceivers using an FPGA-based MIMO ve-hicular channel emulator, EURASIP Journal on Wireless Communications and Networking, 2012, 2012 (1), pp. 215.
5. Fedosov V., Legin A., Lomakina A. Adaptive algorithm for data transmission in wireless chan-nels based on MIMO-OFDM technique, Conference Proceedings - 2017 Radiation and Scat-tering of Electromagnetic Waves, RSEMW 2017, 2017, pp. 218-221.
6. Thota J., Almesaeed R., Doufexi A., Armour S., and Nix A.R. Infrastructure to Vehicle Throughput Performance in LTE-A Using 2D and 3D 3GPP/ITU Channel Models, Book Infra-structure to Vehicle Throughput Performance in LTE-A Using 2D and 3D 3GPP/ITU Channel Models (IEEE, 2015, edn.), pp. 1-5.
7. Javadi M., Habib S., and Hannan M.: Survey on inter-vehicle communication applications, Cur-rent trends and challenges, Information Technology Journal, 2013, No. 12 (2), pp. 243-250.
8. Fedosov V.P., Kovtun D.G., Legin A.A., Lomakina A.V. Issledovanie modeli OFDM-signala s malym urovnem vnepolosnogo izlucheniya [Study of an OFDM signal model with a low level of out-of-band radiation], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2015, No. 11 (172), pp. 6-16.
9. Fedosov V., Lomakina A., Legin A., and Voronin V. Modeling of systems wireless data trans-mission based on antenna arrays in underwater acoustic channels, Book Modeling of systems wireless data transmission based on antenna arrays in underwater acoustic channels (Interna-tional Society for Optics and Photonics, 2016, edn.), pp. 98720G.
10. Fedosov V.P., Legin A.A., Lomakina A.V. Algoritmy, osnovannye na tekhnologii MIMO-OFDM, dlya realizatsii tsifrovogo gidroakusticheskogo kanala svyazi [Algorithms based on the MIMO-OFDM technology for the implementation of a digital hydroacoustic communica-tion channel], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2015, No. 7 (168), pp. 148-158.
11. Almesaeed R., Ameen A.S., Doufexi A., Dahnoun N., and Nix A.R. A comparison study of 2D and 3D ITU channel model, Book A comparison study of 2D and 3D ITU channel model (IEEE, 2013, edn.), pp. 1-7.
12. Thomas T.A., Vook F.W., Mellios E., Hilton G.S., Nix A.R., and Visotsky E. 3D extension of the 3GPP/ITU channel model, Book 3D extension of the 3GPP/ITU channel model (IEEE, 2013, edn.), pp. 1-5.
13. Series M.: Guidelines for evaluation of radio interface technologies for IMT-Advanced, Report ITU, 2009, Vol. 638, pp. 1-72.
14. Isa A.A.M., Othman M., Johal M., Isa M., Zin M., Haron N., Zakaria Z., and Ibrahim M. En-hanced location estimation with a single base station in WiMAX network, Book Enhanced lo-cation estimation with a single base station in WiMAX network (IEEE, 2014, edn.), pp. 1-6.
15. Cho Y.S., Kim J., Yang W.Y., and Kang C.G. MIMO-OFDM wireless communications with MATLAB, John Wiley & Sons, 2010.
16. Fedosov V., Lomakina A., Legin A., and Voronin V. Three-dimensional model of hydro acous-tic channel for research MIMO systems, Book Three-dimensional model of hydro acoustic channel for research MIMO systems (International Society for Optics and Photonics, 2017, edn.), pp. 101860W.
17. Ademaj F., Taranetz M., and Rupp M. 3GPP 3D MIMO channel model: A holistic implemen-tation guideline for open source simulation tools, EURASIP Journal on Wireless Communica-tions and Networking, 2016, 2016, (1), pp. 55.
18. Khan M.W., Zhou Y., and Xu G. Modeling of acoustic propagation channel in underwater wire-less sensor networks, Book Modeling of acoustic propagation channel in underwater wireless sensor networks (IEEE, 2014, edn.), pp. 586-590,
19. Zajic A.G. Statistical modeling of MIMO mobile-to-mobile underwater channels, IEEE Trans-actions on Vehicular Technology, 2011, Vol. 60 (4), pp. 1337-1351
20. Zhang L., Liu J., Liu K., and Zhou Y. On the 3D beamforming and proactive cell shaping with 3GPP 3D channel model, Book on the 3D beamforming and proactive cell shaping with 3GPP 3D channel model (IEEE, 2014, edn.), pp. 688-693.
21. Fedosov V.P., Muravitskiy N.S. Adaptivnaya priemnaya antennaya reshetka dlya obrabotki prostranstvenno-vremennykh signalov v MIMO-sisteme besprovodnoy peredachi dannykh [Adaptive receiving antenna array for processing space-time signals in a MIMO-system for wireless data transmission], Antenny [Antenna], 2011, No. 8 (171), pp. 35-43.
22. Fedosov V.P., Lomakina A.V., Legin A.A., Voronin V.V. Three-dimensional model of hydro acoustic channel for research MIMO systems, Proceedings of SPIE - The International Society for Optical Engineering. 9. Сер. "Ocean Sensing and Monitoring IX" 2017, pp. 101860W.
23. Kucheryavenko A., Fedosov V. Model of multicomponent micro-Doppler signal in environ-ment MATLAB, MATEC Web of Conferencesб 2017, pp. 05008.
24. Ryzhov V.P., Fedosov V.P. Mnogopol'zovatel'skoe prostranstvenno-vremennoe kodirovanie i dekodirovanie v sisteme svyazi na osnove antennykh reshetok [Multi-user space-time coding and decoding in a communication system based on antenna arrays], Izluchenie i rasseyanie elektromagnitnykh voln IREMV-2003: Tr. Mezhdunarodnoy nauchnoy konferentsii [Radiation and scattering of electromagnetic waves IREMV-2003: Proceedings of the International Scien-tific Conference], 2003, pp. 271-275.
Published
2021-02-13
Issue
Section
SECTION I. COMMUNICATIONS, NAVIGATION, AND RADAR
