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A lower bound on the error probability for signals in white Gaussian noise

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1 Author(s)
Seguin, G.E. ; Dept. of Electr. & Comput. Eng., R. Mil. Coll. of Canada, Kingston, Ont., Canada

In this correspondence we apply a recent inequality by de Caen (1997) to derive a lower bound on the probability of error for M-ary signals derived from a binary linear code and used on the additive white Gaussian noise channel with a maximum-likelihood decoder. This bound depends only on the weight enumerator of the code and the signal-to-noise ratio Eb/N0. We show that this bound converges to the union upper bound as Eb/N0 goes to infinity. Finally, by means of examples, we compare our lower bound with those of Shannon and Swaszek and with Poltyrev's upper bound

Published in:

Information Theory, IEEE Transactions on  (Volume:44 ,  Issue: 7 )

Date of Publication:

Nov 1998

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