Implementation of the Modified Monte Carlo Technique Using Importance Sampling on the Block Oriented System Simulator
Abstract
The purpose of this thesis was to implement the Modified Monte Carlo technique using Importance Sampling on the Block Oriented System Simulator (BOSS). Computer simulation techniques of communications systems were reviewed. Next, conventional Monte Carlo techniques and Modified Monte Carlo techniques using Importance Sampling were reviewed. Models of Binary Phase Shift Keying (BPSK) systems using both Monte Carlo techniques were implemented and simulated. Reasons for the model using Importance Sampling not working correctly are postulated. The Monte Carlo technique is a method of ensuring the an inherently infinite procedure, such as determining system bit error rate (BER), can be determined within an appropriate accuracy and a confidence range after a set number of samples. Conventional Monte Carlo requires a certain number of samples to be generated to determine a certain BER. This number of samples results in an estimated BER in the range of 0.5 to 2.0 of the true BER. The number of samples required using conventional Monte Carlo techniques can result in unacceptable simulation times for low probability events. Importance Sampling is a method of reducing the number of samples required to determine an estimated BER with the same accuracy and confidence as conventional Monte Carlo.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1990
- Accession Number
- ADA230500
Entities
People
- John B. Bennett
Organizations
- Air Force Institute of Technology