KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Individual Channel Estimation Based on Blind Interference Cancellation for Two-Way MIMO Relay Networks

  • He, Xianwen (Department of Communication Engineering, Naval University of Engineering) ;
  • Dou, Gaoqi (Department of Communication Engineering, Naval University of Engineering) ;
  • Gao, Jun (Department of Communication Engineering, Naval University of Engineering)
  • Received : 2017.11.19
  • Accepted : 2018.04.10
  • Published : 2018.08.31
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Abstract

In this paper, we investigate an individual channel estimation problem for multiple-input multiple-output (MIMO) two-way amplify-and-forward (AF) relay networks. To avoid self-interference during the estimation of the individual MIMO channels, a novel blind interference cancellation (BIC) approach is proposed based on an orthogonal preceding framework, where a pair of orthogonal precoding matrices is utilized at the source nodes. By designing an optimal decoding scheme, we propose to decompose the bidirectional transmission into a pair of unidirectional transmissions. Unlike most existing approaches, we make the practical assumption that the nonreciprocal MIMO channel and the mutual interference of multiple antennas are both taken into consideration. Under the precoding framework, we employ an orthogonal superimposed training strategy to obtain the individual MIMO channels. However, the AF strategy causes the noise at the terminal to be the sum of the local noise and the relay-propagated noise. To remove the relay-propagated noise during the estimation of the second-hop channel, a partial noise-nulling method is designed. We also derive a closed-form expression for the total mean square error (MSE) of the MIMO channel from which we compute the optimal power allocation. The simulation results demonstrate that the analytical and simulated curves match fully.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China, China Postdoctoral Science Foundation

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