Relay Precoder Optimization in MIMO-Relay Networks With Imperfect CSI


Autoria(s): Ubaidulla, P; Chockalingam, A
Data(s)

01/11/2011

Resumo

In this paper, we consider robust joint designs of relay precoder and destination receive filters in a nonregenerative multiple-input multiple-output (MIMO) relay network. The network consists of multiple source-destination node pairs assisted by a MIMO-relay node. The channel state information (CSI) available at the relay node is assumed to be imperfect. We consider robust designs for two models of CSI error. The first model is a stochastic error (SE) model, where the probability distribution of the CSI error is Gaussian. This model is applicable when the imperfect CSI is mainly due to errors in channel estimation. For this model, we propose robust minimum sum mean square error (SMSE), MSE-balancing, and relay transmit power minimizing precoder designs. The next model for the CSI error is a norm-bounded error (NBE) model, where the CSI error can be specified by an uncertainty set. This model is applicable when the CSI error is dominated by quantization errors. In this case, we adopt a worst-case design approach. For this model, we propose a robust precoder design that minimizes total relay transmit power under constraints on MSEs at the destination nodes. We show that the proposed robust design problems can be reformulated as convex optimization problems that can be solved efficiently using interior-point methods. We demonstrate the robust performance of the proposed design through simulations.

Formato

application/pdf

Identificador

http://eprints.iisc.ernet.in/42613/1/Relay_Precoder.pdf

Ubaidulla, P and Chockalingam, A (2011) Relay Precoder Optimization in MIMO-Relay Networks With Imperfect CSI. In: IEEE Transactions on Signal Processing, 59 (11). pp. 5473-5484.

Publicador

IEEE

Relação

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5982443&tag=1

http://eprints.iisc.ernet.in/42613/

Palavras-Chave #Electrical Communication Engineering
Tipo

Journal Article

PeerReviewed