tuzsutТруды учебных заведений связиProceedings of Telecommunication Universities1813-324X2712-8830СПбГУТ10.31854/1813-324X-2023-9-2-65-71tuzsut-463Research ArticleЭЛЕКТРОНИКА, ФОТОНИКА, ПРИБОРОСТРОЕНИЕ И СВЯЗЬELECTRONICS, PHOTONICS, INSTRUMENTATION AND COMMUNICATIONSАнализ характеристик алгоритмов прекодирования сигналов в системе MU-MIMO с группированием абонентовNumerical Evaluation of the MU-MIMO Beamforming Performance with User Selection Algorithmhttps://orcid.org/0000-0003-1235-6314КалачиковА. А.KalachikovA.

кандидат технических наук, доцент кафедры радиотехнических систем

Новосибирск, 630102, Российская Федерация

Novosibirsk, 630102, Russian Federation

330rts@gmail.comСибирский государственный университет телекоммуникаций и информатикиРоссияSiberian State University of Telecommunications and Information ScienceRussian Federation202330052023926571Copyright © Калачиков А.А., 20232023Калачиков А.А.Kalachikov A.This work is licensed under a Creative Commons Attribution 4.0 License.https://tuzs.sut.ru/jour/article/view/463

В статье представлены результаты имитационного моделирования алгоритма прекодирования ZF с использованием алгоритма ортогонального выбора абонентов и алгоритма максимизации взаимной информации в нисходящей системе MU-MIMO. При количестве пользователей бо́льшем, чем количество антенн на базовой станции, возникает взаимная корреляция между каналами пользователей, что снижает суммарную спектральную эффективность системы MU-MIMO. Для снижения эффекта взаимной корреляции применяется подбор пользователей на основе максимальной ортогональности между ними. Суммарная спектральная эффективность в системе MU-MIMO зависит от условий реального распространения сигналов и для каналов с пространственной корреляцией необходимо использовать выбор подмножества абонентов с низкой корреляцией между их векторами каналов. Для исследования эффективности выбора подмножества абонентов используется модель канала с открытым исходным кодом, позволяющая получать реалистичные реализации канала.

This paper presents the numerical evaluation of the ZF beamforming algorithm using the user selection in the multiuser multiantenna (MU-MIMO) downlink system. Two user selection algorithm – semiorthogonal user selection and greedy user selection are numerically evaluated based on the open source MIMO channel model. The sum rate performance depending on number of users are presented. The arising inter user correlation degrades the sum rate (spectral efficiency) performance of multiuser MIMO system especially in scenarios where the number of users is larger than the number of antennas at the BS. The selection of users is based on the orthogonality of the channels among selected users. For MIMO channel simulation the QUADRIGA channel model reflecting the real propagation conditions is used. The obtained performance of MU-MIMO ZF precoding in spatially correlated channel are compared based on the empirical cumulative density function of the sum rate of multiple users. Numerical results show that the ZF precoder using user selection (G ZF) outperforms the ZF precoder with random user selection in spectral efficiency. The greedy user selection in spatially correlated channel has advantage to semi-orthogonal user selection. It isobserved that as the increasing the number of served users used for selection the greedy user selection gives better performance than semi-orthogonal algorithm.

5G new radioQuaDRIGa3GPPмодель каналапрекодирование ZFсистема MU-MIMOгруппирование абонентов5G new radioQuaDRIGa3GPP channel modelZF precodingmultiuser MIMO systemuser selectionReferencesBjornson E., Hoydis J., Sanguinetti L. Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency // Foundations and Trends in Signal Processing. 2017. Vol. 11. Iss. 3‒4. PP. 154‒655. DOI:10.1561/2000000093Bjornson E., Hoydis J., Sanguinetti L. Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency. Foundations and Trends in Signal Processing. 2017;11(3‒4):154‒655. DOI:10.1561/2000000093Castaneda E., Silva A., Gameiro A., Kountouris M. An Overview on Resource Allocation Techniques for Multi-User MIMO Systems // IEEE Communications Surveys and Tutorials. 2017. Vol. 19. Iss. 1. PP. 239‒284. DOI:10.1109/COMST.2016.2618870Castaneda E., Silva A., Gameiro A., Kountouris M. An Overview on Resource Allocation Techniques for Multi-User MIMO Systems. IEEE Communications Surveys and Tutorials. 2017;19(1):239‒284. DOI:10.1109/COMST.2016.26188703. ETSI TS 38.211 V15.8.0 (2020-01). 5G; NR; Physical channels and modulation.ETSI TS 38.211 V15.8.0 (2020-01). 5G; NR; Physical channels and modulation.Yoo T., Goldsmith A. On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming. IEEE Journal on Selected Areas in Communications. 2006;24(3):528‒541. DOI:10.1109/JSAC.2005.862421Bayesteh A., Khandani A.K. On the User Selection for MIMO Broadcast Channels // IEEE Transactions on Information Theory. 2008. Vol. 54. Iss. 3. PP. 1086‒1107.Dimic G., Sidiropoulos N.D. On downlink beamforming with greedy userselection: Performance analysis and a simple new algorithm. IEEE Transactions on Signal Processing. 2005;53(10):3857‒3868. DOI:10.1109/TSP.2005.855401Yoo T., Goldsmith A. On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming // IEEE Journal on Selected Areas in Communications. 2006. Vol. 24. Iss. 3. PP. 528‒541. DOI:10.1109/JSAC.2005.862421Dimic G., Sidiropoulos N.D. On downlink beamforming with greedy userselection: Performance analysis and a simple new algorithm. IEEE Transactions on Signal Processing. 2005;53(10):3857‒3868. DOI:10.1109/TSP.2005.855401Dimic G., Sidiropoulos N.D. On downlink beamforming with greedy userselection: Performance analysis and a simple new algorithm // IEEE Transactions on Signal Processing. 2005. Vol. 53. Iss. 10. PP. 3857‒3868. DOI:10.1109/TSP.2005.855401Kaltenberger F., Gespert D., Knopp R., Kountouris M. Performance of Multi-User MIMO Precoding with Limited Feedback over Measured Channels. Proceedings of the IEEE Global Telecommunications Conference, IEEE GLOBECOM 2008, 30 November‒04 December 2008, New Orleans, USA. IEEE; 2008. DOI:10.1109/GLOCOM.2008.ECP.738Kaltenberger F., Gespert D., Knopp R., Kountouris M. Performance of Multi-User MIMO Precoding with Limited Feedback over Measured Channels // Proceedings of the IEEE Global Telecommunications Conference (IEEE GLOBECOM 2008, New Orleans, USA, 30 November‒04 December 2008). IEEE, 2008. DOI:10.1109/GLOCOM.2008.ECP.738Cho Y.S., Kim J., Yang W.Y., Kang C.G. MIMO-OFDM Wireless Communications with MATLAB. John Wiley and Sons; 2010. 544 p.Cho Y.S., Kim J., Yang W.Y., Kang C.G. MIMO-OFDM Wireless Communications with MATLAB. John Wiley and Sons, 2010. 544 p.ETSI TR 138.901 V16.1.0 (2020-11). 5G; Study on channel model for frequencies from 0,5 to 100 GHz.ETSI TR 138.901 V16.1.0 (2020-11). 5G; Study on channel model for frequencies from 0,5 to 100 GHz.Clerckx B., Kim G., Sung J. Correlated Fading in Broadcast MIMO Channels: Curse or Blessing? Proceedings of the IEEE Global Telecommunications Conference, IEEE GLOBECOM 2008, 30 November‒04 December 2008, New Orleans, USA. IEEE; 2008. DOI:10.1109/GLOCOM.2008.ECP.735Clerckx B., Kim G., Sung J. Correlated Fading in Broadcast MIMO Channels: Curse or Blessing? // Proceedings of the IEEE Global Telecommunications Conference (IEEE GLOBECOM 2008, New Orleans, USA, 30 November‒04 December 2008). IEEE, 2008. DOI:10.1109/GLOCOM.2008.ECP.735Jaeckel S., Raschkowski L., Börner K., Thiele L., Burkhardt F., Eberlein E. Quasi Deterministic Radio Channel Generator. User Manual and Documentation. QuaDRiGa. Document Revision: v2.2.0. Berlin: Fraunhofer Heinrich Hertz Institute; 2019.Jaeckel S., Raschkowski L., Börner K., Thiele L., Burkhardt F., Eberlein E. Quasi Deterministic Radio Channel Generator. User Manual and Documentation. QuaDRiGa. Document Revision: v2.2.0. Berlin: Fraunhofer Heinrich Hertz Institute, 2019.Jaeckel S., Raschkowski L., Börner K., Thiele L. QuaDRiGa: A 3-D Multicell Channel Model with Time Evolution for Enabling Virtual Field Trials. IEEE Transactions on Antennas Propagation. 2014;62(6):3242‒3256. DOI:10.1109/TAP.2014.2310220Jaeckel S., Raschkowski L., Börner K., Thiele L. QuaDRiGa: A 3-D Multicell Channel Model with Time Evolution for Enabling Virtual Field Trials // IEEE Transactions on Antennas Propagation. 2014. Vol. 62. Iss. 6. PP. 3242‒3256. DOI:10.1109/TAP.2014.2310220Jaeckel S., Raschkowski L., Börner K., Thiele L. QuaDRiGa: A 3-D Multicell Channel Model with Time Evolution for Enabling Virtual Field Trials // IEEE Transactions on Antennas Propagation. 2014. Vol. 62. Iss. 6. PP. 3242‒3256. DOI:10.1109/TAP.2014.2310220

The authors declare that there are no conflicts of interest present.