TY - CHAP
T1 - Channel estimation for PLNC under frequency selective fading scenario
AU - Gao, Feifei
AU - Xing, Chengwen
AU - Wang, Gongpu
N1 - Publisher Copyright:
© 2014, The Author(s).
PY - 2014
Y1 - 2014
N2 - In this chapter, we consider the channel estimation for PLNC under the more general frequency selective scenario, where orthogonal-frequency-division multiplexing (OFDM) is adopted for data transmission. We propose a two-phase training protocol, which is compatible with the two-phase data transmission, and thus the training block can be embedded into the data frame. Specifically, we design two different types of training methods: (i) block based training, for which we first estimate the cascaded source-relay-source channels, and then recover the individual channels between sources and relay; (ii) pilot-tone (PT) based training, for which we directly estimate the individual channels between sources and relay. Importantly, the identifiability of the channel estimation in both types of the training schemes are fully addressed. Finally, various numerical examples are presented to corroborate our analytical results.
AB - In this chapter, we consider the channel estimation for PLNC under the more general frequency selective scenario, where orthogonal-frequency-division multiplexing (OFDM) is adopted for data transmission. We propose a two-phase training protocol, which is compatible with the two-phase data transmission, and thus the training block can be embedded into the data frame. Specifically, we design two different types of training methods: (i) block based training, for which we first estimate the cascaded source-relay-source channels, and then recover the individual channels between sources and relay; (ii) pilot-tone (PT) based training, for which we directly estimate the individual channels between sources and relay. Importantly, the identifiability of the channel estimation in both types of the training schemes are fully addressed. Finally, various numerical examples are presented to corroborate our analytical results.
UR - http://www.scopus.com/inward/record.url?scp=85044928571&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-11668-6_4
DO - 10.1007/978-3-319-11668-6_4
M3 - Chapter
AN - SCOPUS:85044928571
T3 - SpringerBriefs in Computer Science
SP - 35
EP - 57
BT - SpringerBriefs in Computer Science
PB - Springer
ER -