BER Performance Comparison of Various Modulation Schemes using MMSE on MIMO System over Various Fading Channel
DOI:
https://doi.org/10.26438/ijcse/v8i3.4148Keywords:
MIMO-OFDM, MMSE, ML, ZF, BERAbstract
In MIMO-OFDMA (multiple input multiple output-orthogonal frequency division multiplexing access) when signals are transmitted from the transmitter to receiver different types of error detection techniques are used for calculating the BER (bit error rate), which is an important factor in characterizing the data channel. Among various modulation schemes techniques, MMSE (minimum mean square error) is a versatile technique in which it is not necessary to calculate, explicit the posterior probability density function. In MMSE, we calculate the BER on previously known parameters and no need to assume random variables as a result among all estimators and the accuracy rate is higher. MMSE to reduce BER uses “MINIMUM MEAN SQUARE ALGORITHM” that is MMSE algorithm which is pre-owned to minimize the error and achieved the optimal performance at a cost of high computational complexities.
References
[1] Purnima k Sharma, T. Vijaysai, “Bit error rate analysis of precoding techniques in different MIMO systems”, proceedings of the 2nd international conference on electronics, communication and aerospace technology (ICECA 2018) IEEE Explore ISBN: 978-1-5386-0965-1, pp. 1144-1147.
[2] Madalina –Georgiana Berceanu, Carmen Voicu, Simona Halunga, “the performance of an uplink large scale MIMO – SIC detector”, International conference on military communications and information systems (ICMCIS), 2019, pp. 1-4.
[3] Shubangi R. Chaudhary, Madhavi Pardeep Thombre, “BER performance analysis of MIMO –OFDM system using different equalization techniques”, IEEE International conference on advanced communication control and computing technologies (ICACCCT), 2014, pp. 637-677.
[4] Zenitha Rehman and H.M.Savitha, “BER performance comparison of MIMO systems using OSTBC with ZF and ML decoding”, ICTACT Journal on communication technology, December 2014, volume:5, ISSUE:04, pp.1030-1034
[5] Brijesh Kumar Yadav, Rabinder Kumar Singh , and Sovan Mohanty, “performance analysis of efficient and low complexity MIMO-OFDM using STBC and V-BLAST”,International conference on emerging trends in electrical, electronics and sustainable energy systems (ICETEESES-16), IEEE 2016, PP. 204-207.
[6] Superaja Eduru, Nakkeran Rangaswamy, “BER analysis of massive MIMO system under correlated Rayleigh fading channel”, IEEE-43488, 9th ICCNT 2018 IISC Benguluru, India.
[7] Mr.Kanchan Sharma, Ambika Verma, Jasneet kaur, and Trishla, “performance evaluation of fountain codes for MIMO-OFDM system over Rican faded channel”,2014 international conference on medical imagining, m-health and emerging communication systems (Medcom), pp. 319-324.
[8] Kamaljit Kaur gill and Kiranpreet Kaur, “comparative analysis of ZF and MMSE detections for Nakagami –m faded MIMO channels”, IEEE INDICON 2015, pp.1-5.
[9] Himankashi Grover, Reetu Pathania, “performance analysis of MMSE equalizer and time-frequency block code for MIMOOFDM under single-RF system”, proceeding of 2nd international conference on inventive communication and computational technologies (ICICCCT) 2018, pp. 1277-1280.
[10] Lusekelo Kibona, liujain & liuying Zhaung, “BER analysis using Zero –forcing linear pre-coding scheme for massive MIMO under imperfect channel state information”, international journal of electronics, 2019.
[11] M.D. Renzo. And H.Hass. H, “Bit error probability of SMMIMO over generalized fading channel”, IEEE Transactions on vehicular Technology, vol. 61, no.3, pp.1124-1144, March 2012.
[12] Oktavia Kartika Sari, I Gede Puja Asthwa, “performance analysis of MIMO-OFDM systems with SIC detection based on Single –RF with convolution code”, international electronics Symposium (IES) 2016, PP. 289-294, 2016.
[13] Jabbar, s.; li, y., “Analysis and Evaluation of performance gains and the trade-off for massive MIMO Systems” (appl. Sci.), pp. 1-30, September 2016.
[14] J. Choi and H.Naguyen, “SIC-Based detection with list and lattice reduction for MIMO channels, “In IEEE Transactions on vehicular technology, vol.58, no. 7, pp.3786-3790, Sept. 2009.
[15] M.Berceanu, C.voice and S.Hangula, “performance analysis of an uplink massive MU-MIMO OFDM based system”, 2018 international conference on communications (COMM), Bucharest, 2018, pp.335-339.
[16] M.Brceanu, C. Voicu and S. Hangula, “uplink massive MUMIMO OFDM based system with LDPC coding-simulation and performances”, 9th edition of International conference Advanced topics in optoelectronics, microcontrollers, and nanotechnologies, 2018, Constanta.
[17] W.Li, C.Zhang, X.Duan, S.Jia, et al., "Performance evaluation and analysis on group mobility of group mobility of mobileready for LTE-Advanced systems”, in proc. IEEE VTC 2012fall.
[18] Purnima k. Sharma and Dinesh Sharma, “mobile wireless technology is boon or curse”, Indian journal of science and technology, vol. 9 (40), DOI:10.17485/ijst/2016/v9i40/84293, October 2016.
[19] Md. Hashemali Khan, KM Cho, Moon Ho Lee*, and JinGyunchun I g, “A Simple bock diagonal pre-coding for multiuser MIMO broadcast channels”, EURASIP Journal on wireless communication and networking: 95, 2014.
[20] Suresh Kumar Jindal, “MIMO system for military communication /applications”, International journal of engineering research and applications”, ISSN/; 2248-9622, VOL. 6, issue 3, (part -4) March 2016, pp. 22-33.
[21] Eman al-Khadar, Shereen, “pre-coding and post coding for capacity enhancement in MIMO systems” in Procedia computer science, volume-52, pp. 326-333, 2015.
[22] Er.Navjot Singh, Er. Vinod Kumar linear and non-linear decoding techniques in multi-user MIMO systems” A review vol. 4, issue-5, May 2015.
[23] Parul Wadhwa, Gaurav Gupta, “BER Analysis & Comparison of different decoding techniques for MIMO-OFDM system” International Journal of Advanced Research in computer science and software engineering volume 3, ISSUE 6, ISSN:2277 128X, June 2013.
[24] L.T.Berger, Andreas Scwager, Daniel Schneider and Pascal Pagani, “MIMO Power line communications: Narrow and Broadband Standards, EMC, and Advanced Processing”, Devices, circuits, and systems 2014.
[25] Bhasker Gupta and Davinder S. Saini, “BER performance improvement in MIMO systems”, 2nd IEEE International Conference on Parallel, Distributed and grid computing, 2012.
[26] K. Punia, E.M. George, K.V. Babu, and G.R. Reddy, “Signal Detection for spatially multiplexed multi-input multioutput(MIMO) systems”, in Proe. International conference on communication and signal processing, April 2014, pp.612-616.
[27] A.H. Mehana, and A. Noratinia, “Diversity of MMSE MIMO Receivers”, IEEE Transactions on information theory, vol. 58, no. 11, pp. 6788-6805, November 2012.
[28] Zhou, y., Shen, B., Wang, Q., & Choi, D.(2017), “ A New joint zero-forcing beam forming algorithm for massive MIMO systems”, IEEE Transactions on wireless communications,15(3),2245-2261.
[29] Silva, S., Baduge, G. A. A., Ardakani, M.,& STellambura, c.(2018), “Performance analysis of massive MIMO two- way relay network with pilot contamination, imperfect CSI and antenna correlation”, IEEE Transactions on vehicular technology, 67(6), 4831-4842.
[30] Shehab W. A., & Al-qudah, Z. (2017), “singular value decomposition: principles and applications in multiple input multiple output communication system”, Intl. J. Computer Network Communication, 9(1), pp. 13-21
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
