Academic literature on the topic 'MIMO-OFDM System Model'
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Journal articles on the topic "MIMO-OFDM System Model"
Rathod, Anokchand, and Megha Gupta. "Review Paper on MIMO-OFDM System Using Wimax Model." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (June 30, 2018): 2259–63. http://dx.doi.org/10.31142/ijtsrd14604.
Full textYoussef, M. I., A. E. Emam, and M. Abd Khalifa. "ICI and PAPR enhancement in MIMO-OFDM system using RNS coding." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 2 (April 1, 2019): 1209. http://dx.doi.org/10.11591/ijece.v9i2.pp1209-1219.
Full textN. Jayanthi, P., and S. Ravishankar. "Model-based compressed sensing algorithms for MIMO- OFDM channel estimation." International Journal of Engineering & Technology 7, no. 2.4 (March 10, 2018): 5. http://dx.doi.org/10.14419/ijet.v7i2.4.10030.
Full textEl Ghzaoui, M., A. Hmamou, J. Foshi, and J. Mestoui. "Compensation of Non-linear Distortion Effects in MIMO-OFDM Systems Using Constant Envelope OFDM for 5G Applications." Journal of Circuits, Systems and Computers 29, no. 16 (June 18, 2020): 2050257. http://dx.doi.org/10.1142/s0218126620502576.
Full textShivhare, Amit, Ravi Kumar, and Manish K. Patidar. "Review of MIMO-OFDM System Using Simulink Model." International Journal of Computer Sciences and Engineering 7, no. 3 (March 31, 2019): 72–75. http://dx.doi.org/10.26438/ijcse/v7i3.7275.
Full textEt. al., Preesat Biswas,. "A Simulational Performance of 5G MIMO Systems applying UFMC( Universal Filtered Multicarrier) Study." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (April 10, 2021): 3176–83. http://dx.doi.org/10.17762/turcomat.v12i2.2365.
Full textSilpa, C., A. Vani, and K. Rama Naidu. "Deep Learning Based Channel Estimation for MIMO-OFDM System with Modified ResNet Model." Indian Journal Of Science And Technology 16, no. 2 (January 15, 2023): 97–108. http://dx.doi.org/10.17485/ijst/v16i2.2154.
Full textKavitha, G., B. Kirthiga, and N. Kirubanandasarathy. "Performance Analysis of an Area Efficient and Low Power MOD-R2MDC FFT for MIMO OFDM." Applied Mechanics and Materials 573 (June 2014): 176–80. http://dx.doi.org/10.4028/www.scientific.net/amm.573.176.
Full textZhao, Gaoli, Jianping Wang, Wei Chen, and Junping Song. "A Novel Signal Detection Algorithm for Underwater MIMO-OFDM Systems Based on Generalized MMSE." Journal of Sensors 2019 (November 12, 2019): 1–10. http://dx.doi.org/10.1155/2019/2603051.
Full textShobha, Y. K., and H. G. Rangaraju. "Experimental Evaluation of Machine learning based MIMO-OFDM System for Optimal PAPR and BER." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 16 (May 26, 2021): 315–27. http://dx.doi.org/10.37394/23203.2021.16.27.
Full textDissertations / Theses on the topic "MIMO-OFDM System Model"
Lu, X. (Xiaojia). "Resource allocation in uplink coordinated multicell MIMO-OFDM systems with 3D channel models." Doctoral thesis, Oulun yliopisto, 2013. http://urn.fi/urn:isbn:9789526202914.
Full textTiivistelmä Työssä tutkitaan ylälinkin resurssien kohdentamisstrategioita matkapuhelinverkoissa. Olettaen koordinointi useiden monikantoaaltotekniikoita käyttävien moniantennitukiasemien (BS) välillä, resurssien kohdentamisongelma muotoillaan uudelleen ja optimoidaan yli suuren joukon optimointimuuttujia. Erityisesti keskitytään yhteenlasketun tehon minimointiongelmaan käyttäjäkohtaisien siirtonopeusrajoitteiden kanssa. Työssä oletetaan keskitetty koordinointi useiden monikantoaaltotekniikoita käyttävien moniantennitukiasemien välillä, joten tukiasemat voidaan adaptiivisesti ryhmitellä yhden matkaviestimen signaalin havannointia varten. Lähetysteho, kantoaaltoallokaatio, keilanmuodostus ja tukiasemaklusterointi ovat ongelman muuttujia, jotka optimoidaan yhdessä siten, että käyttäjäkohtaiset siirtonopeusrajoitteet täyttyvät. Ensimmäinen käsitelty tapaus on yksinkertainen yhden operaattorin monisolujärjestelmä. Tehonsäätöongelma käyttäjäkohtaisten siirtonopeusrajoitusten kanssa voidaan optimaalisesti ratkaista ehdotetulla algoritmilla, jossa lähetysteho, keilanmuodostusvektorit ja tukiasemaklusterointi päivitetään erikseen, kunnes yhteenlaskettu teho suppenee. Tarkastelu laajennetaan monimutkaisempaan monikantoaaltojärjestelmään. Kun käyttäjäkohtainen siirtonopeustavoite kiinnitetään, ongelma voidaan vastaavasti hajottaa osittaisiksi alikantoaaltokohtaisiksi osaongelmiksi, jossa kukin osaongelma voidaan optimaalisesti ratkaista. Jos alikantoaaltokohtaista siirtonopeustavoitetta ei ole kiinnitetty, tehonsäätöongelmasta tulee ei-polynomisesti monimutkainen. Optimaalisia algoritmeja ehdotetaan ongelman ratkaisemiseksi. Jotta voitaisiin saada tietoa todellisesta suorituskykyerosta ehdotettujen algoritmien ja kapasiteettioptimaalisen rajan välillä, vertailu tehdään yhden solun simulointimallissa epälineaarisen vastaanottimen kanssa siten, että kapasiteettioptimaalisen alarajan laskeminen on mahdollista. Tätä varten kehitetään tehokas geometria-avusteinen ja nopeasti konvergoituva algoritmi tehon minimointia varten käyttäjäkohtaisten siirtonopeusrajoitusten kanssa. Vertaamalla kapasiteettioptimaalista alarajaa ehdotettujen algoritmien suorituskykyyn huomataan, että ehdotettu BSW algoritmi on hyvä kompromissi konvergoitumisnopeuden ja tehonkulutuksen välillä. Matkapuhelinverkkojen resurssienkohdentamisalgoritmien lisäksi työssä huomioidaan myös verkon fyysinen mallintaminen ja vastaava suunnittelu. Työssä mallinnetaan radiokanavan ominaisuudet myös korkeustasossa, joka mahdollistaa diversiteetin hyödyntämisen korkeustason keilanmuodostuksessa. Antenniryhmä voi olla joko yhtenäinen lineaarinen ryhmä tai yhtenäinen tasoryhmä, jossa antennielementit on sijoitettu tasoon. Ehdotettuja tehonsäätöalgoritmeja simuloidaan kolmiulotteisessa verkkoskenaarioissa, jossa verrataan antenniryhmäsuunnittelun vaikutuksia eri radiokanavaskenaarioissa
Saglam, Halil Derya. "Simulation performance of multiple-input multiple-output systems employing single-carrier modulation and orthogonal frequency division multiplexing." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Dec%5FSaglam.pdf.
Full textThesis advisor(s): Murali Tummala, Roberto Cristi. Includes bibliographical references (p. 69-71). Also available online.
Costa, Michele Nazareth da. "Codage spatio-temporel tensoriel pour les systèmes de communication sans fil MIMO." Thesis, Nice, 2014. http://www.theses.fr/2014NICE4014/document.
Full textSince the growing success of mobile systems in the 1990s, new wireless technologies have been developed in order to support a growing demand for high-quality multimedia services with low error rates. An interesting way to improve the error performance and to achieve better transmission rates is to combine the use of various diversities and multiplexing access techniques in the MIMO system context. The incorporation of oversampling, spreading and multiplexing operations and additional diversities on wireless systems lead to multidimensional received signals which naturally satisfy tensor models. This thesis proposes a new tensorial approach based on a tensor space-time (TST) coding for MIMO wireless communication systems. The signals received by multiple antennas form a fourth-order tensor that satisfies a new tensor model, referred to as PARATUCK-(2,4) (PT-(2,4)) model. A performance analysis is carried out for the proposed TST system and a recent space-time-frequency (STF) system, which allows to derive expressions for the maximum diversity gain over a at fading channel. An uplink processing based on the TST coding with allocation resources is proposed. A new tensor decomposition is introduced, the so-called PT-(N1,N), which generalizes the standard PT-2 and our PT-(2,4) model. This thesis establishes uniqueness conditions for the PARATUCK-(N1,N) model. From these results, joint symbol and channel estimation is ensured for the TST and STF systems. Semi-blind receivers are proposed based on the well-known Alternating Least Squares algorithm and the Levenberg-Marquardt method, and also a new receiver based on the Kronecker Least Squares (KLS) for both systems
Jose, Renu. "Joint Estimation of Impairments in MIMO-OFDM Systems." Thesis, 2014. http://etd.iisc.ac.in/handle/2005/2769.
Full textJose, Renu. "Joint Estimation of Impairments in MIMO-OFDM Systems." Thesis, 2014. http://hdl.handle.net/2005/2769.
Full textShiu, Wen-Jun, and 徐文俊. "Utilizing Hidden Markov Channel Model for Adaptive Transmission Scheme in MIMO-OFDM Systems." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/j5qzx2.
Full text國立臺北科技大學
電腦與通訊研究所
97
Modern people request transmission rate and transmission quality very much. But, as a result of wireless communication environment is very complicated. So, different environment need to hold transmission rate and transmission quality is very important issue for future wireless communication development. This paper consider different multiple input multiple output(MIMO) structure in different channel environment, we present one method which according to Rician Channel -factor to represent channel quality indicator(CQI) and utilizing this Rician Channel -factor size for modulation、channel coding and MIMO structure to execute adaptive switch. We can accept error range to achieve maximum throughput by using we present method. However, user moment channel environment maybe already change result in adaptive switch become inaccurate when base station receiver user switch request and to proceed adaptive transmission in general time variant channel environment. Base Station receiver user switch request may forecast after channel variant proceed forecast adaptive switch and to increase adaptive switch accurate when we utilizing hidden Markov model(HMM) characteristic , according to high speed rail train measurement channel environment data match to similar channel environment. By the above describe, the spectrum efficiency has 3 bps/Hz difference when use different MIMO structure to collocate orthogonal frequency division multiplexing (OFDM) system in different channel -factor. Maximum throughput may achieve 75 Mbps when utilizing channel -factor proceed adaptive switch. Using HMM proceed channel forecast adaptive transmission average more 5 Mbps than no forecast adaptive transmission when we simulate in high speed rail train channel environment.
Bhavani, Shankar M. R. "Design Of Linear Precoded MIMO Communication Systems." Thesis, 2007. https://etd.iisc.ac.in/handle/2005/558.
Full textBhavani, Shankar M. R. "Design Of Linear Precoded MIMO Communication Systems." Thesis, 2007. http://hdl.handle.net/2005/558.
Full textBooks on the topic "MIMO-OFDM System Model"
Bianchi, Roberto. Interference cancellation in DSL systems: Interferenzunterdrückung in DSL-Systemen. 2011.
Find full textBook chapters on the topic "MIMO-OFDM System Model"
Shaik, Nilofer, and Praveen Kumar Malik. "5G Massive MIMO-OFDM System Model: Existing Channel Estimation Algorithms and Its Review." In Smart Antennas, 193–209. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-76636-8_15.
Full textShivaji, R., K. R. Nataraj, S. Mallikarjunaswamy, and K. R. Rekha. "Implementation of an Effective Hybrid Partial Transmit Sequence Model for Peak to Average Power Ratio in MIMO OFDM System." In Lecture Notes in Electrical Engineering, 1343–53. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3690-5_129.
Full textKomeylian, Somayeh, Christopher Paolini, and Mahasweta Sarkar. "Overcoming an Evasion Attack on a CNN Model in the MIMO-OFDM Wireless Communication Channel." In Lecture Notes in Networks and Systems, 71–88. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1203-2_7.
Full textPallavi, CH, and G. Sreenivasulu. "Performance of a MIMO-OFDM-Based Opto-Acoustic Modem for High Data Rate Underwater Wireless Communication (UWC) System." In Lecture Notes in Electrical Engineering, 51–65. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8865-3_5.
Full textConference papers on the topic "MIMO-OFDM System Model"
Magnitskiy, Viktor. "SIMULATION OF MIMO CHANNEL OF FIFTH GENERATION NETWORKS IN MATLAB SIMULINK SYSTEM." In CAD/EDA/SIMULATION IN MODERN ELECTRONICS 2019. Bryansk State Technical University, 2019. http://dx.doi.org/10.30987/conferencearticle_5e028213bdb4b4.10169741.
Full textKowal, Michal, Slawomir Kubal, Piotr Piotrowski, and Ryszard J. Zielinski. "Simulation model of the MIMO-OFDM system compliant with IEEE 802.11n." In 2010 Fifth International Conference on Broadband and Biomedical Communications (IB2Com). IEEE, 2010. http://dx.doi.org/10.1109/ib2com.2010.5723609.
Full textChan, Peter W. C., Z. G. Pan, Xueyuan Zhao, C. M. Lo, Kai Zhang, and Derek C. K. Lee. "Methodology for Mode Selection in MIMO-OFDM System." In 2008 IEEE Wireless Communications and Networking Conference. IEEE, 2008. http://dx.doi.org/10.1109/wcnc.2008.210.
Full textHuo, Wenjun, Zhigang Wang, and Shentang Li. "Low Complexity Polynomial-Model-Based Channel Estimation for MIMO-OFDM Systems." In 2007 2nd IEEE Conference on Industrial Electronics and Applications. IEEE, 2007. http://dx.doi.org/10.1109/iciea.2007.4318832.
Full textTang, Linjun, Xiaorong Jing, and Zufan Zhang. "Adaptive switching based on Markov model for multiuser MIMO-OFDM systems." In 2013 22nd Wireless and Optical Communication Conference (WOCC 2013). IEEE, 2013. http://dx.doi.org/10.1109/wocc.2013.6676349.
Full text"MODULATION-MODE ASSIGNMENT IN SVD-ASSISTED MULTIUSER MIMO-OFDM SYSTEMS." In International Conference on Wireless Information Networks and Systems. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003443900770086.
Full textMa, Yuanyuan, and Matthias Patzold. "Performance Comparison of Space-Time Coded MIMO-OFDM Systems Using Different Wideband MIMO Channel Models." In 2007 4th International Symposium on Wireless Communication Systems. IEEE, 2007. http://dx.doi.org/10.1109/iswcs.2007.4392443.
Full textThuong Nguyen Canh, Van Duc Nguyen, Phuong Dang, Luong Pham Van, Thu Nga Nguyen, and Matthias Patzold. "A performance study of LTE MIMO-OFDM systems using the extended one-ring MIMO channel model." In 2012 International Conference on Advanced Technologies for Communications (ATC 2012). IEEE, 2012. http://dx.doi.org/10.1109/atc.2012.6404273.
Full textHanzaz, Zakaria, and Hans Dieter Schotten. "Analysis of effective SINR mapping models for MIMO OFDM in LTE system." In 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/iwcmc.2013.6583780.
Full textZhou, Xingyu, Jing Zhang, Chao-Kai Wen, Jun Zhang, and Shi Jin. "Model-Driven Deep Learning-Based Signal Detector for CP-Free MIMO-OFDM Systems." In 2021 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2021. http://dx.doi.org/10.1109/iccworkshops50388.2021.9473616.
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