Achievable rate analysis and feedback design for multiuser relay with imperfect CSI

This paper investigates a multiuser MIMO relay downlink system with imperfect channel estimation and limited feedback. Compared with the system using perfect channel state information (CSI), we analyze the achievable rate loss due to CSI mismatch arising from both channel estimation and CSI quantization feedback. An upper bound to the rate loss is firstly derived to characterize the effect of imperfect CSI. Given the rate loss bound, we then present a limited feedback strategy for both two-hop channels in the relay system to guarantee a bounded rate loss for growing SNRs. This newly presented strategy reveals the relationship between CSI quantization level and other system parameters, including the transmit power and the pilots for channel estimation, on the entire two-hop system. Finally, computer simulations are carried out for verifying the correctness of our derived results.

[1]  Robert W. Heath,et al.  An overview of limited feedback in wireless communication systems , 2008, IEEE Journal on Selected Areas in Communications.

[2]  Ronghong Mo,et al.  Precoder design for non-regenerative MIMO relay systems , 2009, IEEE Transactions on Wireless Communications.

[3]  Shlomo Shamai,et al.  Fading channels: How perfect need "Perfect side information" be? , 2002, IEEE Trans. Inf. Theory.

[4]  Andrea J. Goldsmith,et al.  Capacity limits of MIMO channels , 2003, IEEE J. Sel. Areas Commun..

[5]  Geoffrey Ye Li,et al.  Pilot Matrix Design for Estimating Cascaded Channels in Two-Hop MIMO Amplify-and-Forward Relay Systems , 2011, IEEE Transactions on Wireless Communications.

[6]  Hossam S. Hassanein,et al.  Multi-hop capacity of MIMO-multiplexing relaying systems , 2009, IEEE Transactions on Wireless Communications.

[7]  Andrea J. Goldsmith,et al.  Capacity and power allocation for fading MIMO channels with channel estimation error , 2006, IEEE Trans. Inf. Theory.

[8]  Shu Wang,et al.  On MIMO Relay with Finite-Rate Feedback and Imperfect Channel Estimation , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[9]  Matthew R. McKay,et al.  Opportunistic Relaying for MIMO Wireless Communication: Relay Selection and Capacity Scaling Laws , 2011, IEEE Transactions on Wireless Communications.

[10]  Nihar Jindal MIMO broadcast channels with finite rate feedback , 2005, GLOBECOM.

[11]  Ali H. Sayed,et al.  Multiuser Two-Way Amplify-and-Forward Relay Processing and Power Control Methods for Beamforming Systems , 2010, IEEE Transactions on Signal Processing.

[12]  Yue Rong,et al.  Robust Design for Linear Non-Regenerative MIMO Relays With Imperfect Channel State Information , 2011, IEEE Transactions on Signal Processing.

[13]  Xiangyun Zhou,et al.  On Lower Bounding the Information Capacity of Amplify and Forward Wireless Relay Channels with Channel Estimation Errors , 2011, IEEE Transactions on Wireless Communications.

[14]  Yongming Huang,et al.  Asymptotic Achievable Rate Analysis for Selection Strategies in Amplify-and-Forward MIMO Two-Hop Networks With Feedback , 2010, IEEE Transactions on Vehicular Technology.

[15]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[16]  T. W. Anderson The integral of a symmetric unimodal function over a symmetric convex set and some probability inequalities , 1955 .

[17]  Bo Wang,et al.  On the capacity of MIMO relay channels , 2005, IEEE Transactions on Information Theory.

[18]  Xiaodai Dong,et al.  MIMO Relaying Broadcast Channels With Linear Precoding and Quantized Channel State Information Feedback , 2010, IEEE Transactions on Signal Processing.

[19]  Xiqi Gao,et al.  Superimposed Training Based Channel Estimation for OFDM Modulated Amplify-and-Forward Relay Networks , 2011, IEEE Transactions on Communications.

[20]  Yong Huat Chew,et al.  MMSE-based joint source and relay precoding design for amplify-and-forward MIMO relay networks , 2009, IEEE Transactions on Wireless Communications.

[21]  Xiaodai Dong,et al.  Joint Precoding Optimization for Multiuser Multi-Antenna Relaying Downlinks Using Quadratic Programming , 2011, IEEE Transactions on Communications.

[22]  Feifei Gao,et al.  On channel estimation and optimal training design for amplify and forward relay networks , 2008, IEEE Transactions on Wireless Communications.

[23]  Chau Yuen,et al.  Information Rate and Relay Precoder Design for Amplify-and-Forward MIMO Relay Networks With Imperfect Channel State Information , 2012, IEEE Transactions on Vehicular Technology.

[24]  Giuseppe Caire,et al.  Training and Feedback Optimization for Multiuser MIMO Downlink , 2009, IEEE Transactions on Communications.

[25]  Michael L. Honig,et al.  Signature optimization for CDMA with limited feedback , 2005, IEEE Transactions on Information Theory.

[26]  Murat Uysal,et al.  Impact of imperfect channel estimation on the performance of amplify-and-forward relaying , 2009, IEEE Transactions on Wireless Communications.

[27]  Robert W. Heath,et al.  MIMO Relaying With Linear Processing for Multiuser Transmission in Fixed Relay Networks , 2008, IEEE Transactions on Signal Processing.

[28]  Giuseppe Caire,et al.  Multiuser MIMO Achievable Rates With Downlink Training and Channel State Feedback , 2007, IEEE Transactions on Information Theory.

[29]  Andrea J. Goldsmith,et al.  Multi-Antenna Downlink Channels with Limited Feedback and User Selection , 2007, IEEE Journal on Selected Areas in Communications.

[30]  Helmut Bölcskei,et al.  Capacity scaling laws in MIMO relay networks , 2006, IEEE Transactions on Wireless Communications.

[31]  Thomas L. Marzetta,et al.  Fast transfer of channel state information in wireless systems , 2006, IEEE Transactions on Signal Processing.

[32]  Luc Vandendorpe,et al.  MIMO Relay Design for Multipoint-to-Multipoint Communications With Imperfect Channel State Information , 2009, IEEE Transactions on Signal Processing.

[33]  Panganamala Ramana Kumar,et al.  An achievable rate for the multiple-level relay channel , 2005, IEEE Transactions on Information Theory.