Under the assumption of a frequency-flat slow Rayleigh fading channel with multiple transmit and receive antennas, we examine the effects of imperfect estimation of the channel parameters on error probability when known pilot symbols are transmitted among information data. Three different receivers are considered. The first one derives an estimate of the channel [by using either a maximum-likelihood (ML) or a minimum mean square error (MMSE) criterion], and then uses this estimate in the same metric that would be applied if the channel were perfectly known. The second receiver derives again an estimate of the channel, but uses the ML metric conditioned on the channel estimate. Our last receiver simultaneously processes the pilot and data symbols received. Simulation results are exhibited, showing that only a relatively small percentage of the transmitted frame need be allocated to pilot symbols in order to experience an acceptable degradation of error probability due to imperfect channel knowledge. Algorithms for the recursive calculation of the decision metric of the last two receivers are also developed for application to sequential decoding of trellis space–time codes.

Space-time decoding with imperfect channel estimation / Taricco, Giorgio; Biglieri, E.. - In: IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS. - ISSN 1536-1276. - STAMPA. - 4:4(2005), pp. 1874-1888. [10.1109/TWC.2005.850324]

Space-time decoding with imperfect channel estimation

TARICCO, GIORGIO;
2005

Abstract

Under the assumption of a frequency-flat slow Rayleigh fading channel with multiple transmit and receive antennas, we examine the effects of imperfect estimation of the channel parameters on error probability when known pilot symbols are transmitted among information data. Three different receivers are considered. The first one derives an estimate of the channel [by using either a maximum-likelihood (ML) or a minimum mean square error (MMSE) criterion], and then uses this estimate in the same metric that would be applied if the channel were perfectly known. The second receiver derives again an estimate of the channel, but uses the ML metric conditioned on the channel estimate. Our last receiver simultaneously processes the pilot and data symbols received. Simulation results are exhibited, showing that only a relatively small percentage of the transmitted frame need be allocated to pilot symbols in order to experience an acceptable degradation of error probability due to imperfect channel knowledge. Algorithms for the recursive calculation of the decision metric of the last two receivers are also developed for application to sequential decoding of trellis space–time codes.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/1406578
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