Orthogonal superimposed training design for doubly selective channel estimation using basis expansion models

2017 ◽  
Vol 28 (8) ◽  
pp. e3157 ◽  
Author(s):  
Gaoqi Dou ◽  
Xianwen He ◽  
Ren Deng ◽  
Lihua Li ◽  
Jun Gao
Keyword(s):  
Channel Estimation ◽  
Training Design ◽  
Superimposed Training ◽  
Basis Expansion ◽  
Doubly Selective Channel ◽  
Selective Channel

Semi-Blind Channel Estimation with Orthogonal Superimposed Training for SISO over Doubly Selective Channel

2014 ◽  
Vol 701-702 ◽  
pp. 1029-1032
Author(s):  
Cong Ying Li ◽  
Gao Ming Huang ◽  
Jun Gao ◽  
Gao Qi Dou ◽  
Chun Quan He ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Fading Channel ◽  
Blind Channel Estimation ◽  
Superimposed Training ◽  
Performance Simulation ◽  
Doubly Selective Channel ◽  
Estimation Performance ◽  
Blind Channel ◽  
Selective Channel ◽  
Simulation Results

In this paper, a semi-blind estimator based on orthogonal superimposed training (OST) for the case of doubly selecting fading channel is proposed. With the aid of OST, the interference to channel estimation form data symbols can be eliminated completely. Moreover, data symbols can serve as pseudo-pilots to enhance the estimation performance. Simulation results illustrate the benefits of pseudo-pilots method.

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