Research Article
BibTex RIS Cite

5G iletişim sistemlerinde ÇGÇÇ sistemlerin dizin kazanç analizleri

Year 2022, Volume: 11 Issue: 4, 888 - 897, 14.10.2022
https://doi.org/10.28948/ngumuh.1088264

Abstract

Son on yılda, mobil iletişim ağlarında spektrum verimliliğini artırmak ve kullanılan iletim gücünü azaltmak için Çoklu Giriş Çoklu Çıkış (ÇGÇÇ) algoritmaları geliştirilmiştir. Spektrum verimliliğini artırmak ve kullanılan iletim gücünü azaltmak Beşinci Nesil Yeni Radyonun (5G YR) da Temel Performans Göstergelerinden olduğundan MIMO algoritmalarının 5G YR spesifikasyonlarına uygunluğu araştırılmaktadır. Bu çalışmanın amacı, 5G YR Fiziksel Aşağı Yönlü Bağlantı Paylaşımlı Kanalında (FAYBPK) çoklu verici antenler ve çoklu alıcı antenler kullanılarak elde edilen dizin kazançlarını incelemektir. Çalışma, Tekli Giriş Çoklu Çıkış (TGÇÇ) ve Çoklu Giriş Tekli Çıkış (ÇGTÇ) dizin kazanımlarını inceler, ardından 5G YR FAYBPK ÇGÇÇ sisteminde verici ve alıcı çeşitliliklerini birleştirir. Dizin kazanımları, Tekil Değer Ayrıştırma (TDA) ile elde edilen ön kodlama ve birleştirme vektörlerini kullanılarak elde edilir. Çalışma sonuçlara göre teorik dizi kazanımları baştan-uca 5G YR aşağı bağlantı kanallarında elde edilebilmektedir.

References

  • H. Kim, Design and Optimization for 5G Wireless Communications. Wiley-IEEE Press, 2020.
  • A. Goldsmith, Wireless Communications. Cambridge: Cambridge University Press, 2005.
  • D. Tse and P. Viswanath, Fundamentals of Wireless Communication. Cambridge University Press, 2005.
  • IEEE SA, “IEEE 802.11n-2009.” https://standards.ie ee.org/ieee/802.11n/3952/. Accessed March 2022
  • IEEE SA, “IEEE 802.11ac-2013.” https://standards.ie ee.org/ieee/802.11ac/4473. Accessed March 2022
  • IEEE, “IEEE 802.16-2017.” https://standards.ieee .org/ ieee/802.16/6996/. Accessed March 2022
  • 3GPP, “Release 14.” https://www.3gpp.org/release-14. Accessed March 2022
  • 3GPP, “Release 15.” https://www.3gpp.org/release-15. Accessed March 2022
  • 3GPP, “Release 7.” https://www.3gpp.org/specificatio ns/releases/73-release-7. Accessed March 2022
  • Y. Kabalci, 5G Mobile Communication Systems: Fundamentals, Challenges, and Key Technologies, Smart Grids and Their Communication Systems, Springer (2019), pp. 329-359
  • A. Zaidi, F. Athley, J. Medbo, X. Chen, and G. Durisi, 5G physical layer: Principles, models and technology components, Academic Press, 2018.
  • U. Mutlu, Y. Kabalci, Effects of Antenna Array on Throughput in 5G NR PDSCH, III. International Turkic World Congress on Science and Engineering (TURK-COSE), pp. 98-108, 2021
  • E. Telatar, Capacity of multi-antenna Gaussian channels, Eur. Trans. Telecommun., vol. 10, no. 6, pp. 585–595, 1999, doi: 10.1002/ett.4460100604.
  • M. A. Albreem, A. H. Al Habbash, A. M. Abu-Hudrouss, and S. S. Ikki, Overview of Precoding Techniques for Massive MIMO, IEEE Access, vol. 9, pp. 60764–60801, 2021, doi: 10.1109/ACCESS 2021. 3073325.
  • T. Kebede, Y. Wondie, J. Steinbrunn, H. B. Kassa, and K. T. Kornegay, Precoding and Beamforming Techniques in mmWave-Massive MIMO : Performance Assessment, IEEE Access, vol. 10, pp. 16365–16387, 2022, doi: 10.1109/ACCESS 2022.314 9301.
  • R. M. Asif, J. Arshad, M. Shakir, S. M. Noman, and A. U. Rehman, Energy Efficiency Augmentation in Massive MIMO Systems through Linear Precoding Schemes and Power Consumption Modeling, Wirel. Commun. Mob. Comput., vol. 2020, pp. 1–13, Sep. 2020, doi: 10.1155/2020/8839088.
  • D. Kadhim, Promising Gains of 5G Networks with Enhancing Energy Efficiency Using Improved Linear Precoding Schemes, Int. J. Intell. Eng. Syst., vol. 14, no. 3, pp. 139–149, Jun. 2021, doi: 10.22266/ijies2021 .0630.13.
  • J. Kaur, O. R. Popoola, M. Ali Imran, Q. H. Abbasi, and H. T. Abbas, Improving Throughput For Mobile Receivers Using Adaptive Beamforming, in 2021 1st International Conference on Microwave, Antennas & Circuits (ICMAC), Dec. 2021, pp. 1–4, doi: 10.1109 /ICMAC54080.2021.9678216.
  • N. Fatema, G. Hua, Y. Xiang, D. Peng, and I. Natgunanathan, Massive MIMO Linear Precoding: A Survey, IEEE Syst. J., vol. 12, no. 4, pp. 3920–3931, 2018, doi: 10.1109/JSYST.2017.2776401.
  • X. Qiao, Y. Zhang, and L. Yang, Conjugate Gradient Method Based Linear Precoding with Low-Complexity for Massive MIMO Systems, in 2018 IEEE 4th International Conference on Computer and Communications (ICCC), Dec. 2018, pp. 420–424, doi: 10.1109/CompComm.2018.8780818.
  • B. Lee, Simplified Antenna Group Determination of RS Overhead Reduced Massive MIMO for Wireless Sensor Networks, Sensors, vol. 18, no. 2, p. 84, Dec. 2017, doi: 10.3390/s18010084.
  • V. Ivanov, A. Medvedev, I. Bondareva and V. Grigoriev, Performance of 5G SU-MIMO Employing OFDM Bandwidth and Per-Subcarrier Precoding, Editors: O. Galinina, S. Andreev, S. Balandin, Y. Koucheryavy, Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN 2020, ruSMART 2020. https://doi.org/10.1007/978-3-030-65729-1
  • ETSI TS 138 211 - V16.2.0, 5G NR; Physical channels and modulation (3GPP TS 38.211 version 16.2.0 Release 16), ETSI 2020
  • M. Vu and A. Paulraj, MIMO wireless linear precoding, IEEE Signal Process. Mag., vol. 24, no. 5, pp. 86–105, 2007, doi: 10.1109/MSP.2007.904811.
  • B. Clerckx and C. Oestges, MIMO Wireless Networks, Academic Press, 2013.
  • A. Paulraj, R. Nabar, and D. Gore, Introduction to space-time wireless communications, Cambridge University Press, 2003.
  • J. B. Andersen, Array gain and capacity for known random channels with multiple element arrays at both ends, IEEE J. Sel. Areas Commun., vol. 18, no. 11, pp. 2172–2178, 2000, doi: 10.1109/49.895022.
  • ETSI TS 138 212 - V16.2.0, “5G NR; Multiplexing and channel coding (3GPP TS 38.212 version 16.2.0 Release 16), ETSI 2020
  • ETSI TS 138 300 - V16.2.0, 5G; NR; NR and NG-RAN Overall description; Stage-2 (3GPP TS 38.300 version 16.2.0 Release 16), 2020.
  • U. Mutlu, Y. Kabalci, Deep Learning Aided Channel Estimation Approach for 5G Communication Systems, 2022 4th Global Power, Energy and Communication Conference (GPECOM), pp. 655-660, 2022, doi: 10.1109/GPECOM55404.2022.9815811
  • T. Dubois, M. Hélard, M. Crussière, and C. Germond, Performance of time reversal precoding technique for MISO-OFDM systems, Eurasip J. Wirel. Commun. Netw., vol. 2013, no. 1, pp. 1–16, 2013, doi: 10.1186/1687-1499-2013-260.
  • G. Barb and M. Otesteanu, On the Influence of Delay Spread in TDL and CDL Channel Models for Downlink 5G MIMO Systems, 2019 IEEE 10th Annu. Ubiquitous Comput. Electron. Mob. Commun. Conf. UEMCON 2019, pp. 0958–0962, 2019, doi: 10.1109/UEMCON4 7517.2019.8992982.
  • ETSI TR 138 900, LTE; 5G; Study on channel model for frequency spectrum above 6 GHz (3GPP TR 38.900 version 15.0.0 Release 15), 2018
  • X. Chen, “Throughput Modeling and Measurement in an Isotropic-Scattering Reverberation Chamber,” IEEE Trans. Antennas Propag., vol. 62, no. 4, pp. 2130–2139, Apr. 2014, doi: 10.1109/TAP.2014.2301850.
  • D. Borges, P. Montezuma, R. Dinis, and M. Beko, “Massive MIMO Techniques for 5G and Beyond—Opportunities and Challenges,” Electronics, vol. 10, no. 14, p. 1667, Jul. 2021, doi: 10.3390/electronics 10141667.

Array gain analyses of MIMO systems in 5G communication systems

Year 2022, Volume: 11 Issue: 4, 888 - 897, 14.10.2022
https://doi.org/10.28948/ngumuh.1088264

Abstract

In the last decade, Multiple-Input Multiple-Output (MIMO) algorithms have been developed for mobile communication networks in order to increase spectrum efficiency and reduce transmitted power, which are also two of the main Key Performance Indicators of Fifth Generation New Radio (5G NR). Therefore, various MIMO algorithms are being researched for their adaptability to 5G NR specifications. The objective of this study is to examine the array gains achieved with the deployment of multiple transmit antennas and multiple receive antennas in 5G NR Physical Downlink Shared Channel (PDSCH). The study first examines the array gains of Single-Input Multiple-Output (SIMO) and Multiple-Input Single-Output (MISO), then combines the transmitter and the receiver diversities in a MIMO system for 5G PDSCH. The array gains are achieved through precoding and combining vectors obtained by Singular Value Decomposition (SVD) of the channel coefficients matrix. The results show that theoretical array gains can be achieved in end-to-end 5G NR downlink channels.

References

  • H. Kim, Design and Optimization for 5G Wireless Communications. Wiley-IEEE Press, 2020.
  • A. Goldsmith, Wireless Communications. Cambridge: Cambridge University Press, 2005.
  • D. Tse and P. Viswanath, Fundamentals of Wireless Communication. Cambridge University Press, 2005.
  • IEEE SA, “IEEE 802.11n-2009.” https://standards.ie ee.org/ieee/802.11n/3952/. Accessed March 2022
  • IEEE SA, “IEEE 802.11ac-2013.” https://standards.ie ee.org/ieee/802.11ac/4473. Accessed March 2022
  • IEEE, “IEEE 802.16-2017.” https://standards.ieee .org/ ieee/802.16/6996/. Accessed March 2022
  • 3GPP, “Release 14.” https://www.3gpp.org/release-14. Accessed March 2022
  • 3GPP, “Release 15.” https://www.3gpp.org/release-15. Accessed March 2022
  • 3GPP, “Release 7.” https://www.3gpp.org/specificatio ns/releases/73-release-7. Accessed March 2022
  • Y. Kabalci, 5G Mobile Communication Systems: Fundamentals, Challenges, and Key Technologies, Smart Grids and Their Communication Systems, Springer (2019), pp. 329-359
  • A. Zaidi, F. Athley, J. Medbo, X. Chen, and G. Durisi, 5G physical layer: Principles, models and technology components, Academic Press, 2018.
  • U. Mutlu, Y. Kabalci, Effects of Antenna Array on Throughput in 5G NR PDSCH, III. International Turkic World Congress on Science and Engineering (TURK-COSE), pp. 98-108, 2021
  • E. Telatar, Capacity of multi-antenna Gaussian channels, Eur. Trans. Telecommun., vol. 10, no. 6, pp. 585–595, 1999, doi: 10.1002/ett.4460100604.
  • M. A. Albreem, A. H. Al Habbash, A. M. Abu-Hudrouss, and S. S. Ikki, Overview of Precoding Techniques for Massive MIMO, IEEE Access, vol. 9, pp. 60764–60801, 2021, doi: 10.1109/ACCESS 2021. 3073325.
  • T. Kebede, Y. Wondie, J. Steinbrunn, H. B. Kassa, and K. T. Kornegay, Precoding and Beamforming Techniques in mmWave-Massive MIMO : Performance Assessment, IEEE Access, vol. 10, pp. 16365–16387, 2022, doi: 10.1109/ACCESS 2022.314 9301.
  • R. M. Asif, J. Arshad, M. Shakir, S. M. Noman, and A. U. Rehman, Energy Efficiency Augmentation in Massive MIMO Systems through Linear Precoding Schemes and Power Consumption Modeling, Wirel. Commun. Mob. Comput., vol. 2020, pp. 1–13, Sep. 2020, doi: 10.1155/2020/8839088.
  • D. Kadhim, Promising Gains of 5G Networks with Enhancing Energy Efficiency Using Improved Linear Precoding Schemes, Int. J. Intell. Eng. Syst., vol. 14, no. 3, pp. 139–149, Jun. 2021, doi: 10.22266/ijies2021 .0630.13.
  • J. Kaur, O. R. Popoola, M. Ali Imran, Q. H. Abbasi, and H. T. Abbas, Improving Throughput For Mobile Receivers Using Adaptive Beamforming, in 2021 1st International Conference on Microwave, Antennas & Circuits (ICMAC), Dec. 2021, pp. 1–4, doi: 10.1109 /ICMAC54080.2021.9678216.
  • N. Fatema, G. Hua, Y. Xiang, D. Peng, and I. Natgunanathan, Massive MIMO Linear Precoding: A Survey, IEEE Syst. J., vol. 12, no. 4, pp. 3920–3931, 2018, doi: 10.1109/JSYST.2017.2776401.
  • X. Qiao, Y. Zhang, and L. Yang, Conjugate Gradient Method Based Linear Precoding with Low-Complexity for Massive MIMO Systems, in 2018 IEEE 4th International Conference on Computer and Communications (ICCC), Dec. 2018, pp. 420–424, doi: 10.1109/CompComm.2018.8780818.
  • B. Lee, Simplified Antenna Group Determination of RS Overhead Reduced Massive MIMO for Wireless Sensor Networks, Sensors, vol. 18, no. 2, p. 84, Dec. 2017, doi: 10.3390/s18010084.
  • V. Ivanov, A. Medvedev, I. Bondareva and V. Grigoriev, Performance of 5G SU-MIMO Employing OFDM Bandwidth and Per-Subcarrier Precoding, Editors: O. Galinina, S. Andreev, S. Balandin, Y. Koucheryavy, Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN 2020, ruSMART 2020. https://doi.org/10.1007/978-3-030-65729-1
  • ETSI TS 138 211 - V16.2.0, 5G NR; Physical channels and modulation (3GPP TS 38.211 version 16.2.0 Release 16), ETSI 2020
  • M. Vu and A. Paulraj, MIMO wireless linear precoding, IEEE Signal Process. Mag., vol. 24, no. 5, pp. 86–105, 2007, doi: 10.1109/MSP.2007.904811.
  • B. Clerckx and C. Oestges, MIMO Wireless Networks, Academic Press, 2013.
  • A. Paulraj, R. Nabar, and D. Gore, Introduction to space-time wireless communications, Cambridge University Press, 2003.
  • J. B. Andersen, Array gain and capacity for known random channels with multiple element arrays at both ends, IEEE J. Sel. Areas Commun., vol. 18, no. 11, pp. 2172–2178, 2000, doi: 10.1109/49.895022.
  • ETSI TS 138 212 - V16.2.0, “5G NR; Multiplexing and channel coding (3GPP TS 38.212 version 16.2.0 Release 16), ETSI 2020
  • ETSI TS 138 300 - V16.2.0, 5G; NR; NR and NG-RAN Overall description; Stage-2 (3GPP TS 38.300 version 16.2.0 Release 16), 2020.
  • U. Mutlu, Y. Kabalci, Deep Learning Aided Channel Estimation Approach for 5G Communication Systems, 2022 4th Global Power, Energy and Communication Conference (GPECOM), pp. 655-660, 2022, doi: 10.1109/GPECOM55404.2022.9815811
  • T. Dubois, M. Hélard, M. Crussière, and C. Germond, Performance of time reversal precoding technique for MISO-OFDM systems, Eurasip J. Wirel. Commun. Netw., vol. 2013, no. 1, pp. 1–16, 2013, doi: 10.1186/1687-1499-2013-260.
  • G. Barb and M. Otesteanu, On the Influence of Delay Spread in TDL and CDL Channel Models for Downlink 5G MIMO Systems, 2019 IEEE 10th Annu. Ubiquitous Comput. Electron. Mob. Commun. Conf. UEMCON 2019, pp. 0958–0962, 2019, doi: 10.1109/UEMCON4 7517.2019.8992982.
  • ETSI TR 138 900, LTE; 5G; Study on channel model for frequency spectrum above 6 GHz (3GPP TR 38.900 version 15.0.0 Release 15), 2018
  • X. Chen, “Throughput Modeling and Measurement in an Isotropic-Scattering Reverberation Chamber,” IEEE Trans. Antennas Propag., vol. 62, no. 4, pp. 2130–2139, Apr. 2014, doi: 10.1109/TAP.2014.2301850.
  • D. Borges, P. Montezuma, R. Dinis, and M. Beko, “Massive MIMO Techniques for 5G and Beyond—Opportunities and Challenges,” Electronics, vol. 10, no. 14, p. 1667, Jul. 2021, doi: 10.3390/electronics 10141667.
There are 35 citations in total.

Details

Primary Language English
Subjects Electrical Engineering
Journal Section Electrical and Electronics Engineering
Authors

Ural Mutlu 0000-0003-2595-0531

Yasin Kabalcı 0000-0003-1240-817X

Publication Date October 14, 2022
Submission Date March 15, 2022
Acceptance Date July 6, 2022
Published in Issue Year 2022 Volume: 11 Issue: 4

Cite

APA Mutlu, U., & Kabalcı, Y. (2022). Array gain analyses of MIMO systems in 5G communication systems. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 11(4), 888-897. https://doi.org/10.28948/ngumuh.1088264
AMA Mutlu U, Kabalcı Y. Array gain analyses of MIMO systems in 5G communication systems. NOHU J. Eng. Sci. October 2022;11(4):888-897. doi:10.28948/ngumuh.1088264
Chicago Mutlu, Ural, and Yasin Kabalcı. “Array Gain Analyses of MIMO Systems in 5G Communication Systems”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 11, no. 4 (October 2022): 888-97. https://doi.org/10.28948/ngumuh.1088264.
EndNote Mutlu U, Kabalcı Y (October 1, 2022) Array gain analyses of MIMO systems in 5G communication systems. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 11 4 888–897.
IEEE U. Mutlu and Y. Kabalcı, “Array gain analyses of MIMO systems in 5G communication systems”, NOHU J. Eng. Sci., vol. 11, no. 4, pp. 888–897, 2022, doi: 10.28948/ngumuh.1088264.
ISNAD Mutlu, Ural - Kabalcı, Yasin. “Array Gain Analyses of MIMO Systems in 5G Communication Systems”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 11/4 (October 2022), 888-897. https://doi.org/10.28948/ngumuh.1088264.
JAMA Mutlu U, Kabalcı Y. Array gain analyses of MIMO systems in 5G communication systems. NOHU J. Eng. Sci. 2022;11:888–897.
MLA Mutlu, Ural and Yasin Kabalcı. “Array Gain Analyses of MIMO Systems in 5G Communication Systems”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, vol. 11, no. 4, 2022, pp. 888-97, doi:10.28948/ngumuh.1088264.
Vancouver Mutlu U, Kabalcı Y. Array gain analyses of MIMO systems in 5G communication systems. NOHU J. Eng. Sci. 2022;11(4):888-97.

download