A deterministic algorithm was recently proposed for channel identification in block communication systems. The method assumed that the channel is finite impulse response (FIR) and that null guard intervals of length greater than the channel order are inserted between successive blocks to prevent interblock interference and allow block synchronization. In the absence of noise, the algorithm provides error-free channel estimates, using a finite number of received data, without requiring training sequences and without imposing a restriction neither on the channel, except for finite order and time invariance, nor on the symbol constellation. Using small perturbation analysis, in this paper, we derive approximate expressions of the estimated channel covariance matrix, which are used to quantify the resilience of the estimation algorithm to additive noise and channel fluctuations. Specifically, we consider channel fluctuations induced by transmitter/receiver relative motion, asynchronism, and oscillators' phase noise. We also compare the channel estimation accuracy with the Cramér-Rao bound (CRB) and prove that our estimation method is statistically efficient at practical SNR values for any data block length. Finally, we validate our theoretical analysis with simulations and compare our transmission scheme with an alternative system using training sequences for channel estimation.
|Original language||English (US)|
|Number of pages||12|
|Journal||IEEE Transactions on Signal Processing|
|State||Published - Mar 2002|
Bibliographical noteFunding Information:
Manuscript received August 19, 1999; revised October 9, 2001. This work was supported in part by the National Science Foundation Wireless Initiative Grant 9979443. The associate editor coordinating the review of this paper and approving it for publication was Prof. Michail K. Tsatsanis. S. Barbarossa is with the INFOCOM Department, University of Rome “La Sapienza,” Rome, Italy (e-mail: email@example.com). A. Scaglione is with the School of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853 USA. G. B. Giannakis is with the Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455 USA. Publisher Item Identifier S 1053-587X(02)01346-6.
- Channel estimation
- Theoretical bounds