Abstract—With the development of high-speed trains (HSTs) in many countries, providing broadband wireless services in HSTs is crucial. Orthogonal frequency-division multiplexing (OFDM) has been widely adopted for broadband wireless communications due to its high spectral efficiency. However, OFDM is sensitive to the time selectivity caused by high-mobility channels, which costs much spectrum or time resources to obtain the accurate channel state information (CSI). Therefore, the channel estima-tion in high-mobility OFDM systems has been a long-standing challenge. In this paper, we first propose a new position-based high-mobility channel model, in which the HST’s position infor-mation and Doppler shift are utilized to determine the positions...
Nowadays, multicarrier transmission is very popular because of the high data rate requirement of wir...
Copyright © 2013 Boudali Ouarzazi et al. This is an open access article distributed under the Creati...
Several contributions have been made on using Compressed Sensing (CS) for sparse channel estimation ...
In this paper, channel overhead is reduced by exploiting channel sparsity for multiple input multipl...
© 2017 IEEE. Obtaining channel state information is very crucial for realizing high-performance high...
Abstract--- Orthogonal frequency division multiplexing (OFDM) is widely recognized as the key techno...
Abstract—In this paper, we investigate channel estimation for orthogonal frequency division multiple...
Orthogonal frequency division multiplexing (OFDM) is well-known to be effective against multipath di...
International audienceHigh speed data transmission for wireless communication in orthogonal frequenc...
Orthogonal frequency division multiplexing (OFDM) is a technique which are used in the next-generati...
In this paper, we propose a new compressive sensing (CS) based channel estimation method for high mo...
Orthogonal Frequency Division Multiplexing (OFDM) is a well-known technique used in modern wide band...
This paper presents a new algorithm for the channel estimation of the OFDM system based on a pilot s...
Abstract The future wireless mobile communication systems are aim to provide high-quality and high-r...
In this paper, generalized spatial modulation-orthogonal frequency-division multiplexing is introduc...
Nowadays, multicarrier transmission is very popular because of the high data rate requirement of wir...
Copyright © 2013 Boudali Ouarzazi et al. This is an open access article distributed under the Creati...
Several contributions have been made on using Compressed Sensing (CS) for sparse channel estimation ...
In this paper, channel overhead is reduced by exploiting channel sparsity for multiple input multipl...
© 2017 IEEE. Obtaining channel state information is very crucial for realizing high-performance high...
Abstract--- Orthogonal frequency division multiplexing (OFDM) is widely recognized as the key techno...
Abstract—In this paper, we investigate channel estimation for orthogonal frequency division multiple...
Orthogonal frequency division multiplexing (OFDM) is well-known to be effective against multipath di...
International audienceHigh speed data transmission for wireless communication in orthogonal frequenc...
Orthogonal frequency division multiplexing (OFDM) is a technique which are used in the next-generati...
In this paper, we propose a new compressive sensing (CS) based channel estimation method for high mo...
Orthogonal Frequency Division Multiplexing (OFDM) is a well-known technique used in modern wide band...
This paper presents a new algorithm for the channel estimation of the OFDM system based on a pilot s...
Abstract The future wireless mobile communication systems are aim to provide high-quality and high-r...
In this paper, generalized spatial modulation-orthogonal frequency-division multiplexing is introduc...
Nowadays, multicarrier transmission is very popular because of the high data rate requirement of wir...
Copyright © 2013 Boudali Ouarzazi et al. This is an open access article distributed under the Creati...
Several contributions have been made on using Compressed Sensing (CS) for sparse channel estimation ...