scholarly journals DVB-S2 Channel Estimation and Decoding in The Presence of Phase Noise for Non-Linear Channels

2015 ◽  
Vol 1 (1) ◽  
pp. 112-127 ◽  
Author(s):  
Urvashi Pal ◽  
Horace L KING
Keyword(s):  
Channel Estimation ◽  
Phase Noise ◽  
Impulse Response ◽  
Radio Channel ◽  
Multipath Fading ◽  
Noise Signal ◽  
Signal Recovery ◽  
Multipath Fading Channel ◽  
Proper Estimation ◽  
Joint Channel

In a multipath fading channel of DVB-S2, smallscalevariations occur due to unwanted noise signal, which isdirectly related to the impulse response of a radio channel. Thevarying channel has to be estimated before decoding the signal atthe receiver for proper signal recovery. However, In the presenceof a time varying and correlated phase noise, proper estimation ofthe Channel Impulse Response (CIR) becomes difficult. Toovercome this problem, a pilot-aided joint channel estimation anddecoding method is proposed to obtain the initial estimate of thechannel. This technique is reliable and important for satellitecommunication as the Ku-band capacity is almost over crowdedand more satellite resources are needed. The results show thatIterative Channel Estimation technique results in a lower BER andimproved signal quality for DVB-S2, which fine-tunes the systemfor an efficient use of power and bandwidth of satellite resources.

scholarly journals Channel Estimation in DCT-Based OFDM

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Yulin Wang ◽  
Gengxin Zhang ◽  
Zhidong Xie ◽  
Jing Hu
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multipath Fading ◽  
Wireless Channel ◽  
Least Square ◽  
System Throughput ◽  
Multipath Fading Channel ◽  
Channel Response ◽  
Coherent Demodulation ◽  
And Performance

This paper derives the channel estimation of a discrete cosine transform- (DCT-) based orthogonal frequency-division multiplexing (OFDM) system over a frequency-selective multipath fading channel. Channel estimation has been proved to improve system throughput and performance by allowing for coherent demodulation. Pilot-aided methods are traditionally used to learn the channel response. Least square (LS) and mean square error estimators (MMSE) are investigated. We also study a compressed sensing (CS) based channel estimation, which takes the sparse property of wireless channel into account. Simulation results have shown that the CS based channel estimation is expected to have better performance than LS. However MMSE can achieve optimal performance because of prior knowledge of the channel statistic.

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