Channel training signal design for reciprocal multiple antenna systems with beamforming


Autoria(s): Bharath, BN; Murthy, Chandra R
Data(s)

01/01/2013

Resumo

Fast and efficient channel estimation is key to achieving high data rate performance in mobile and vehicular communication systems, where the channel is fast time-varying. To this end, this work proposes and optimizes channel-dependent training schemes for reciprocal Multiple-Input Multiple-Output (MIMO) channels with beamforming (BF) at the transmitter and receiver. First, assuming that Channel State Information (CSI) is available at the receiver, a channel-dependent Reverse Channel Training (RCT) signal is proposed that enables efficient estimation of the BF vector at the transmitter with a minimum training duration of only one symbol. In contrast, conventional orthogonal training requires a minimum training duration equal to the number of receive antennas. A tight approximation to the capacity lower bound on the system is derived, which is used as a performance metric to optimize the parameters of the RCT. Next, assuming that CSI is available at the transmitter, a channel-dependent forward-link training signal is proposed and its power and duration are optimized with respect to an approximate capacity lower bound. Monte Carlo simulations illustrate the significant performance improvement offered by the proposed channel-dependent training schemes over the existing channel-agnostic orthogonal training schemes.

Formato

application/pdf

Identificador

http://eprints.iisc.ernet.in/46671/1/IEEE_Tra_Veh_Tech_62-1_140_2012.pdf

Bharath, BN and Murthy, Chandra R (2013) Channel training signal design for reciprocal multiple antenna systems with beamforming. In: IEEE Transactions on Vehicular Technology, 62 (1). pp. 140-151.

Publicador

IEEE-Inst Electrical Electronics Engineers Inc

Relação

http://dx.doi.org/10.1109/TVT.2012.2219631

http://eprints.iisc.ernet.in/46671/

Palavras-Chave #Computer Science & Automation (Formerly, School of Automation)
Tipo

Journal Article

PeerReviewed