| DC Field | Value | Language |
| dc.contributor.author | Shuo Wang | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2026-05-19T08:05:50Z | - |
| dc.date.available | 2026-05-19T08:05:50Z | - |
| dc.date.issued | 2026 | - |
| dc.identifier.citation | Shuo Wang. Performance analysis of LS and LMMSE channel estimation for 5G NR OFDM systems over time-varying fading channels / Shuo Wang // Информационная безопасность : сборник материалов 62-й научной конференции аспирантов, магистрантов и студентов БГУИР, Минск, 13–17 апреля 2026 г. / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: С. В. Дробот (гл. ред.) [и др.]. – Минск, 2026. – С. 214–215. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/63736 | - |
| dc.description.abstract | Accurate and efficient acquisition of Channel State Information (CSI) is crucial for reliable data transmission using Orthogonal
Frequency Division Multiplexing (OFDM) in 5G NR (New Radio) systems. Focusing on the 5G NR physical layer standards, this paper
constructs a complete OFDM baseband transmission link and conducts an in-depth performance comparison and theoretical analysis of
block pilot-based Least Squares (LS) and Linear Minimum Mean Square Error (LMMSE) channel estimation algorithms. A first-order
autoregressive (AR1) model is employed to simulate slow and fast fading environments at different mobility speeds. A strictly discrete
frequency-domain autocorrelation matrix is derived to address the errors of continuous integral approximation in traditional LMMS. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | БГУИР | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | сhannel еstimation | en_US |
| dc.subject | time-varying fading | en_US |
| dc.title | Performance analysis of LS and LMMSE channel estimation for 5G NR OFDM systems over time-varying fading channels | en_US |
| Appears in Collections: | Информационная безопасность : материалы 62-й научной конференции аспирантов, магистрантов и студентов (2026)
|