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In this paper, we collect and discuss some of the recent theoretical results on channel identification using a random probe sequence. These results are part of the body of work known as compressive sampling, a rapidly developing field whose central message is that sparse vectors can be recovered from a set of “random” underdetermined measurements. In the context of channel estimation, if the channel's impulse response is sparse, then it can be estimated by exciting the channel with a random probing sequence and then taking a relatively small number of samples of the output. We also overview recent results in multiple channel estimation that show the channel responses in a multiple-input multiple-output (MIMO) system can be efficiently estimated by exciting all of the inputs with independent random probing signals simultaneously.
Decision and Control (CDC), 2010 49th IEEE Conference on
Date of Conference: 15-17 Dec. 2010