PERFORMANCE ANALYSIS AND EVALUATION OF MASSIVE MIMO SYSTEM
Muaayed F. AL-RAWI
muaayed@uomustansiriyah.edu.iqAl-Mustansiriyh University, Faculty of Engineering, Computer Engineering Department, Palestine Street, 14022, Baghdad (Iraq)
Izz K. ABBOUD
* Al-Mustansiriyh University, Faculty of Engineering, Computer Engineering Department, Palestine Street, 14022, Baghdad (Iraq)
Nasir A. AL-AWAD
Al-Mustansiriyh University, Faculty of Engineering, Computer Engineering Department, Palestine Street, 14022, Baghdad (Iraq)
Abstract
This article examines the performance of massive MIMO uplink system over Rician fading channel. The performance is estimated regarding spectral efficiency versus number of base station antennas utilizing three plans of linear detection, maximum-ratio-combining (MRC), zero forcing receiver (ZF), and minimum mean-square error receiver (MMSE). The simulation results reveal that the spectral efficiency increments altogether with expanding the quantity of base station antennas. Additionally, the spectral efficiency with MMSE is superior to that with ZF, and the last is superior to that with MRC. Furthermore, the spectral efficiency diminishes with expanding the fading parameter.
Keywords:
Performance Analysis, MIMO, Rician Fading ChannelReferences
Chopra, R., Murthy, C.R., Suraweera, H.A., & Larsson, E.G. (2018). Performance analysis of FDD massive MIMO systems under channel aging. IEEE Transactions on Wireless Communications, 17(2), 1094–1108. http://doi.org/10.1109/TWC.2017.2775629
DOI: https://doi.org/10.1109/TWC.2017.2775629
Google Scholar
Ciuonzo, D., Rossi, P.S., & Dey, S. (2015). Massive MIMO channel aware decision fusion. IEEE Transactions on Signal Processing, 63(3), 604–619. http://doi.org/10.1109/TSP.2014.2376886
DOI: https://doi.org/10.1109/TSP.2014.2376886
Google Scholar
Fatema, N., Hua, G., Xiang, Y., Peng, D., & Natgunanathan, I. (2018). Massive MIMO linear precoding: A survey. IEEE systems journal, 12(4), 3920–3931. http://doi.org/10.1109/JSYST.2017.2776401
DOI: https://doi.org/10.1109/JSYST.2017.2776401
Google Scholar
Lu, L., Li, G., Swindlehurst, A.L., Ashikhmin, A., & Zhang, R. (2014). An overview of massive MIMO: benefits and challenges. IEEE Journal of Selected Topics in Signal Processing, 8(5), 742–758. http://doi.org/10.1109/JSTSP.2014.2317671
DOI: https://doi.org/10.1109/JSTSP.2014.2317671
Google Scholar
Marzetta, T. L. (2010). Noncooperative cellular wireless with unlimited number of base station antennas. IEEE Transactions on Communications, 9(11), 3590–3600. http://doi.org/10.1109/TWC.2010.092810.091092
DOI: https://doi.org/10.1109/TWC.2010.092810.091092
Google Scholar
Ngo, H.Q. (2012). Performance Bounds for Very Large Multiuser MIMO Systems (M.Sc. Thesis). Linköping University, Sweden.
Google Scholar
Ngo, H.Q., Larsson, E.G., & Marzetta, T.L. (2013). Energy and spectral efficiency of very large multiuser MIMO systems. IEEE Transactions on Communications, 61(4), 1436–1449. http://doi.org/10.1109/TCOMM.2013.020413.110848
DOI: https://doi.org/10.1109/TCOMM.2013.020413.110848
Google Scholar
Pakdeejit, E. (2013). Linear Precoding Performance of Massive MU-MOMO Downlink System (M.Sc. Thesis). Linköping University, Sweden.
Google Scholar
Yang, H., & Marzetta, T.L. (2013). Performance of conjugate and zero-forcing beam forming in large-scale antenna systems. IEEE Journal on Selected Areas in Communications, 31(2), 172–179. http://doi.org/10.1109/JSAC.2013.130206
DOI: https://doi.org/10.1109/JSAC.2013.130206
Google Scholar
Authors
Muaayed F. AL-RAWImuaayed@uomustansiriyah.edu.iq
Al-Mustansiriyh University, Faculty of Engineering, Computer Engineering Department, Palestine Street, 14022, Baghdad Iraq
Authors
Izz K. ABBOUD* Al-Mustansiriyh University, Faculty of Engineering, Computer Engineering Department, Palestine Street, 14022, Baghdad Iraq
Authors
Nasir A. AL-AWADAl-Mustansiriyh University, Faculty of Engineering, Computer Engineering Department, Palestine Street, 14022, Baghdad Iraq
Statistics
Abstract views: 217PDF downloads: 26
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.
Most read articles by the same author(s)
- Nasir A. Al-Awad, Izz K. Abboud, Muaayed F. Al-Rawi, GENETIC ALGORITHM-PID CONTROLLER FOR MODEL ORDER REDUCTION PANTOGRAPHCATENARY SYSTEM , Applied Computer Science: Vol. 17 No. 2 (2021)
- Muaayed F. AL-RAWI, Muhanned F. AL-RAWI, NOVEL SIMPLE DESIGN AND ANALYSIS OF WI-MAX TRANSCEIVER USING MATLAB-SIMULINK , Applied Computer Science: Vol. 17 No. 1 (2021)
- Muaayed F. AL-RAWI, CONVENTIONAL ENERGY EFFICIENT ROUTING PROTOCOLS IN WIRELESS SENSOR NETWORKS , Applied Computer Science: Vol. 16 No. 3 (2020)
Similar Articles
- Marcin Badurowicz, Sebastian Łagowski, USAGE OF IOT EDGE APPROACH FOR ROAD QUALITY ANALYSIS , Applied Computer Science: Vol. 19 No. 1 (2023)
- Rumesh Edirimanne, W Madushan Fernando, Peter Nielsen, H. Niles Perera, Amila Thibbotuwawa, OPTIMIZING UNMANNED AERIAL VEHICLE BASED FOOD DELIVERY THROUGH VEHICLE ROUTING PROBLEM: A COMPARATIVE ANALYSIS OF THREE DELIVERY SYSTEMS. , Applied Computer Science: Vol. 20 No. 1 (2024)
- Damian KOLNY, Dawid KURCZYK, Józef MATUSZEK, COMPUTER SUPPORT OF ERGONOMIC ANALYSIS OF WORKING CONDITIONS AT WORKSTATIONS , Applied Computer Science: Vol. 15 No. 1 (2019)
- Archana Gunakala, Afzal Hussain Shahid, A COMPARATIVE STUDY ON PERFORMANCE OF BASIC AND ENSEMBLE CLASSIFIERS WITH VARIOUS DATASETS , Applied Computer Science: Vol. 19 No. 1 (2023)
- Roman GALAGAN, Serhiy ANDREIEV, Nataliia STELMAKH, Yaroslava RAFALSKA, Andrii MOMOT, AUTOMATION OF POLYCYSTIC OVARY SYNDROME DIAGNOSTICS THROUGH MACHINE LEARNING ALGORITHMS IN ULTRASOUND IMAGING , Applied Computer Science: Vol. 20 No. 2 (2024)
- Tilla IZSÁK, László MARÁK, Mihály ORMOS, EVALUATION OF SUPPORT VECTOR MACHINE BASED STOCK PRICE PREDICTION , Applied Computer Science: Vol. 19 No. 3 (2023)
- Katarzyna ORZECHOWSKA, Tymon RUBEL, Robert KURJATA, Krzysztof ZAREMBA, A DISTRIBUTED ALGORITHM FOR PROTEIN IDENTIFICATION FROM TANDEM MASS SPECTROMETRY DATA , Applied Computer Science: Vol. 18 No. 2 (2022)
- Alexandru Marius OBRETIN, Andreea Alina CORNEA, FILTERING STRATEGIES FOR SMARTPHONE EMITTED DIGITAL SIGNALS , Applied Computer Science: Vol. 20 No. 1 (2024)
- Sara SALEHI, FUZZY MULTIPLE CRITERIA GROUP DECISION-MAKING IN PERFORMANCE EVALUATION OF MANUFACTURING COMPANIES , Applied Computer Science: Vol. 19 No. 3 (2023)
- Erizal ERIZAL, Mohammad DIQI, PERFORMANCE EVALUATION OF STOCK PREDICTION MODELS USING EMAGRU , Applied Computer Science: Vol. 19 No. 3 (2023)
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.