On the theory and application of universal classification to signal detection

Warke, N.; Orsak, G.C.

doi:10.1109/wits.1994.513908

Cited by 2 publications

(4 citation statements)

References 2 publications

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“….The span of the quantizer is determined such that all samples of X M fall into the range of the quantizer. It should be noted that in [2] it was shown that the performance of the universal receiver did not degrade significantly when employed with a quantizer with sufficient resolution and span. Because of this, and based on our own observations, in this short paper we will not focus on the quantizer as a design issue.…”

Section: A a Blind Traaning Algorathmmentioning

confidence: 99%

“…Asymptotically optiw 11 receivers based upon the original work of Gutman [l] and Ziv 141 have been rece[,'iy proposed by Warke and Orsak [2] and Paris, Orsak,Warke and Chen [3]. These receivers extract statistically suficient channel information from training sets obtained from the channel.…”

Section: A Empirical Receiversmentioning

confidence: 99%

“…They can be categorized as (1) optimal receivers based on a specific channel model, (2) trained receivers using certain pilot signals from the channel] and (3) blind receivers based only on transmitted data.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we demonstrate a highly effective training-free empirical receiver for QAM signals. This receiver is based upon the universal receivers I" transmitted signal is significantly degraded by illdeveloped in [l], [2], [3]. This class of adaptive receivers was shown to be asymptotically optimum over a wide range of channel statistics so long as the amount of training data grows in proportion to the amount test data.…”

Section: Introductionmentioning

confidence: 99%

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A training-free empirical receiver for QAM signals

Paranjpe

Stolpman²,

Orsak³

WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466)

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Noise and interference on communications channels can often deviate significantly from that predicted by Gaussian models. This unfortunate reality can degrade the system performance t o unacceptable levels. Empirical universal receivers have been developed which achieve asymptotic optimality over a very wide range of channels, and are thus useful in such situations. However, these receivers require training or pilot signals from the channel, which in turn reduces the effective bandwidth of the channel. In this paper, we demonstrate a "training-free" empirical receiver which is shown t o perform significantly better than reasonably trained universal receivers and nearly as well as the globally optimal receiver. Importantly, this receiver is capable of deriving the necessary training information directly from the transmitted communication signal, and thus requires no bandwidth overhead. Applications to QPSK reception are discussed thoroughly.

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Section: A a Blind Traaning Algorathmmentioning

confidence: 99%

Section: A Empirical Receiversmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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