Bit-error probability for an adaptive diversity receiver in a Rayleigh-fading channel

Veli-Pekka Kaasila; Aarne Mämmelä

doi:10.1109/26.718549

Bit-error probability for an adaptive diversity receiver in a Rayleigh-fading channel

Veli-Pekka Kaasila, Aarne Mämmelä

Research output: Contribution to journal › Article › Scientific › peer-review

6 Citations (Scopus)

Abstract

The bit-error probability is determined for a binary antipodal diversity system with an adaptive receiver using decision-directed channel estimation. The diversity channels are assumed to be nonselective Rayleigh-fading channels with additive white Gaussian noise (AWGN).
The analysis is valid for all linear estimators which use a finite-impulse-response (FIR)-type estimation filter.
Numerical results are presented for a minimum mean-square error (MMSE) filter and a moving average (MA) filter.

Original language	English
Pages (from-to)	1106-1108
Journal	IEEE Transactions on Communications
Volume	46
Issue number	9
DOIs	https://doi.org/10.1109/26.718549
Publication status	Published - 1998
MoE publication type	A1 Journal article-refereed

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title = "Bit-error probability for an adaptive diversity receiver in a Rayleigh-fading channel",

abstract = "The bit-error probability is determined for a binary antipodal diversity system with an adaptive receiver using decision-directed channel estimation. The diversity channels are assumed to be nonselective Rayleigh-fading channels with additive white Gaussian noise (AWGN). The analysis is valid for all linear estimators which use a finite-impulse-response (FIR)-type estimation filter. Numerical results are presented for a minimum mean-square error (MMSE) filter and a moving average (MA) filter.",

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AB - The bit-error probability is determined for a binary antipodal diversity system with an adaptive receiver using decision-directed channel estimation. The diversity channels are assumed to be nonselective Rayleigh-fading channels with additive white Gaussian noise (AWGN). The analysis is valid for all linear estimators which use a finite-impulse-response (FIR)-type estimation filter. Numerical results are presented for a minimum mean-square error (MMSE) filter and a moving average (MA) filter.

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