Position-aided channel estimation for large-scale MIMO in high-speed railway scenarios

Tao Li, Xiaodong Wang, Pingyi Fan, Taneli Riihonen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)


Channel estimation is a major overhead factor in large-scale multiple-input multiple-output \mbox{(MIMO)} systems, especially under the high- speed railway scenarios. This paper proposes a position-aided channel estimation scheme for high- speed railway communication systems, where both the transmitter and the receiver are equipped with large-scale antenna linear arrays. By joint spatio- temporal correlation, the pilot overhead can be significantly reduced. Furthermore, the optimal design of transmit power and time interval partition between the training and data phases as well as the antenna size are presented accordingly. Both analytical and simulation results show that the system throughput with position-aided channel estimation does not deteriorate significantly as the mobility increases, which is sharply in contrast with the conventional one that intends to re- estimate the entire channel matrix each block.

Original languageEnglish
Title of host publication2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings
Number of pages6
ISBN (Electronic)9781509013289
Publication statusPublished - 2 Feb 2017
MoE publication typeA4 Article in a conference publication
EventIEEE Global Communications Conference - Washington, United States
Duration: 4 Dec 20168 Dec 2016
Conference number: 59


ConferenceIEEE Global Communications Conference
Abbreviated titleGLOBECOM
CountryUnited States

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