Importance sampling for the random phase Gaussian channel

Author

Swaszek, Peter F. ; Levine, Peter J.

Author_Institution

Dept. of Electr. & Comput. Eng., Rhode Island Univ., Kingston, RI, USA

Volume

49

Issue

5

fYear

2001

fDate

5/1/2001 12:00:00 AM

Firstpage

749

Lastpage

753

Abstract

Importance sampling (IS) is developed as a variance reduction technique for Monte Carlo simulation of data communications over random phase additive white Gaussian noise channels. The binary problem (with known performance) is examined initially to determine parameter values and estimate the performance gain of IS. These results can then be applied to intractable m-ary signaling problems through composite IS. An example compares the performance of linear, square-law, and optimum receivers for binary block coded data

Keywords

AWGN channels; Monte Carlo methods; data communication; importance sampling; AWGN channels; Monte Carlo simulation; additive white Gaussian noise channels; binary block coded data; binary problem; data communications; importance sampling; intractable m-ary signaling problems; linear receivers; optimum receivers; performance gain; random phase Gaussian channel; square-law receivers; variance reduction technique; AWGN; Additive white noise; Computational modeling; Computer errors; Data communication; Decoding; Gaussian channels; Monte Carlo methods; Sampling methods; Testing;

fLanguage

English

Journal_Title

Communications, IEEE Transactions on

Publisher

ieee

ISSN

0090-6778

Type

jour

DOI

10.1109/26.923795

Filename

923795