A Modified Superimposed Training Scheme for Individual Channel Estimation for Amplify-and-Forward Relay Network

2018 ◽  
Author(s):  
Xianwen He ◽  
Gaoqi Dou ◽  
Jun Gao
Keyword(s):  
Channel Estimation ◽  
Relay Network ◽  
Amplify And Forward ◽  
Superimposed Training ◽  
Training Scheme

scholarly journals Superimposed Training-Based Channel Estimation for MIMO Relay Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaoyan Xu ◽  
Jianjun Wu ◽  
Shubo Ren ◽  
Lingyang Song ◽  
Haige Xiang
Keyword(s):  
Channel Estimation ◽  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Relay Network ◽  
Mimo Channel ◽  
Amplify And Forward ◽  
Error Performance ◽  
Superimposed Training ◽  
Training Strategy ◽  
The Individual

We introduce the superimposed training strategy into the multiple-input multiple-output (MIMO) amplify-and-forward (AF) one-way relay network (OWRN) to perform the individual channel estimation at the destination. Through the superposition of a group of additional training vectors at the relay subject to power allocation, the separated estimates of the source-relay and relay-destination channels can be obtained directly at the destination, and the accordance with the two-hop AF strategy can be guaranteed at the same time. The closed-form Bayesian Cramér-Rao lower bound (CRLB) is derived for the estimation of two sets of flat-fading MIMO channel under random channel parameters and further exploited to design the optimal training vectors. A specific suboptimal channel estimation algorithm is applied in the MIMO AF OWRN using the optimal training sequences, and the normalized mean square error performance for the estimation is provided to verify the Bayesian CRLB results.

scholarly journals Individual Channel Estimation in a Diamond Relay Network Using Relay-Assisted Training

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Xianwen He ◽  
Gaoqi Dou ◽  
Jun Gao
Keyword(s):  
Channel Estimation ◽  
Relay Node ◽  
Spatial Diversity ◽  
Relay Network ◽  
Destination Node ◽  
Training Design ◽  
Amplify And Forward ◽  
Relay Nodes ◽  
Training Scheme ◽  
Data Signal

We consider the training design and channel estimation in the amplify-and-forward (AF) diamond relay network. Our strategy is to transmit the source training in time-multiplexing (TM) mode while each relay node superimposes its own relay training over the amplified received data signal without bandwidth expansion. The principal challenge is to obtain accurate channel state information (CSI) of second-hop link due to the multiaccess interference (MAI) and cooperative data interference (CDI). To maintain the orthogonality between data and training, a modified relay-assisted training scheme is proposed to migrate the CDI, where some of the cooperative data at the relay are discarded to accommodate relay training. Meanwhile, a couple of optimal zero-correlation zone (ZCZ) relay-assisted sequences are designed to avoid MAI. At the destination node, the received signals from the two relay nodes are combined to achieve spatial diversity and enhanced data reliability. The simulation results are presented to validate the performance of the proposed schemes.

scholarly journals Individual channel estimation for amplify-and-forward relay networks using in-band superimposed training

2018 ◽  
Vol 12 (9) ◽  
pp. 1141-1147
Author(s):  
Gaoqi Dou ◽  
Xianwen He ◽  
Ran Deng ◽  
Jun Gao ◽  
Qingbo Wang
Keyword(s):  
Channel Estimation ◽  
Relay Networks ◽  
Amplify And Forward ◽  
Superimposed Training
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