Capacity Analysis of Bidirectional AF Relay Selection with Imperfect Channel State Information

TL;DR

This paper analyzes the impact of imperfect channel state information on the ergodic capacity of bidirectional amplify-and-forward relay selection, proposing two suboptimal schemes and deriving a tight lower bound.

Contribution

It introduces two practical relay selection schemes under imperfect CSI and derives a closed-form lower bound for ergodic capacity, showing the benefits of channel prediction.

Findings

Imperfect CSI significantly degrades ergodic capacity.

The predicted channel-based scheme outperforms the scheme based on imperfect channel coefficients.

Capacity approaches optimal performance with sufficiently large prediction length.

Abstract

In this letter, we analyze the ergodic capacity of bidirectional amplify-and-forward relay selection (RS) with imperfect channel state information (CSI), i.e., outdated CSI and imperfect channel estimation. Practically, the optimal RS scheme in maximizing the ergodic capacity cannot be achieved, due to the imperfect CSI. Therefore, two suboptimal RS schemes are discussed and analyzed, in which the first RS scheme is based on the imperfect channel coefficients, and the second RS scheme is based on the predicted channel coefficients. The lower bound of the ergodic capacity with imperfect CSI is derived in a closed-form, which matches tightly with the simulation results. The results reveal that once CSI is imperfect, the ergodic capacity of bidirectional RS degrades greatly, whereas the RS scheme based on the predicted channel has better performance, and it approaches infinitely to the optimal performance, when the prediction length is sufficiently large.