Title :
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
fDate :
5/1/2001 12:00:00 AM
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;
Journal_Title :
Communications, IEEE Transactions on
