Massive MIMO Downlink Transmission for LEO Satellite Communications

Li, Ke-Xin; You, Li; Wang, Jiaheng; Gao, Xiqi; Tsinos, Christos G.; Chatzinotas, Symeon; Ottersten, Björn

doi:10.1109/VTC2021-Fall52928.2021.9625530

Reference : Massive MIMO Downlink Transmission for LEO Satellite Communications


	Document type :	Scientific congresses, symposiums and conference proceedings : Poster
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/49217

Title :	Massive MIMO Downlink Transmission for LEO Satellite Communications
Language :	English
Author, co-author :	Li, Ke-Xin [> >]
	You, Li [> >]
	Wang, Jiaheng [> >]
	Gao, Xiqi [> >]
	Tsinos, Christos G. [> >]
	Chatzinotas, Symeon [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	Sep-2021
Peer reviewed :	Yes
Event name :	2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)
Event date :	From 27-09-2021 to 30-09-2021
Abstract :	[en] We investigate the downlink (DL) transmit strategy for massive multiple-input multiple-output (MIMO) low-earthorbit (LEO) satellite communication (SATCOM) systems, in which only the slow-varying statistical channel state information is known at the transmitter side. First, we establish the massive MIMO LEO satellite channel model, in which the uniform planar arrays are deployed at both the satellite and user terminals (UTs). Building on the rank-one property of satellite channel matrices, we show that transmitting a single data stream to each UT is optimal for the ergodic sum rate maximization. This result is of great importance for massive MIMO LEO SATCOM systems, since the sophisticated design of transmit covariance matrices is turned into that of precoding vectors, with no loss of optimality at all. Furthermore, we conceive an algorithm to compute the precoding vectors. Simulation results show the significant performance gains of the proposed approaches over the previous schemes.
Funders :	National Natural Science Foundation of China (Grant Number: 61801114,61631018,61761136016,61971130,61720106003) - 10.13039/501100012226-Fundamental Research Funds for the Central Universities - 10.13039/100007869-FNR
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/49217
DOI :	10.1109/VTC2021-Fall52928.2021.9625530
Other URL :	https://ieeexplore.ieee.org/document/9625530

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