arXiv:0811.0935v4 [cs.IT] 17 Feb 2010 1 A New Training Protocol for Channel State Estimation in Wireless Relay Networks Cenk M. Yetis ∗ , Member, IEEE, and Ahmet H. Kayran, Senior Member, IEEE Abstract The accuracy of channel state information (CSI) is critical for improving the capacity of wireless networks. In this paper, we introduce a training protocol for wireless relay networks that uses channel estimation and feedforwarding methods. The feedforwarding method is the distinctive feature of the proposed protocol. As we show, each relay feedforwards the imperfect CSI to the destination in a way that provides a higher network capacity and a faster transfer of the CSI than the existing protocols. In addition, we show the importance of the effective CSI accuracy on the wireless relay network capacity by comparing networks with the perfect effective CSI, imperfect effective CSI, and noisy imperfect effective CSI available at the destination. Index Terms Relay networks, imperfect channel state information (CSI), channel estimation, effective SNR, ca- pacity, training. I. INTRODUCTION Using training signals is a widely used channel estimation method for obtaining the imperfect channel state information (CSI) in a wireless network that uses time division duplexing [1]. The information theoretic analysis of training based methods was initiated in [2], where the authors address the question of how much of the system resources should be spent for training. In [2], the system resources including C. M. Yetis is with Informatics Institute, Satellite Remote Sensing and Communication, Istanbul Technical University, Maslak, Istanbul, 34469, TURKEY. Email: cenkmyetis@yahoo.com. The author is supported in part by The Scientific and Technological Research Council of Turkey (TUBITAK). The author is on leave at University of California, Irvine. A. H. Kayran is with Department of Electronics and Communications Engineering, Istanbul Technical University, Maslak, Istanbul, 34469, TURKEY. Email: kayran@itu.edu.tr. February 17, 2010 DRAFT