RANSim:Simulating a DS-CDMA Fading Channel

with Bursty Traffic Arrivals

Colette Consani

Heidi Proske

Content

IntroductionScenarioQuestions

Introduction: Landman’s Work

Developing an analytic model to analyze trends in the packet error rates and packet throughput as a function of various parameters for a DS-CDMA fading channel with bursty traffic arrivals

Introduction: Landman’s Request

To increase the validity of the (Hidden Markov Model (HMM) developed, results are needed from another source for comparison

Best source = physical system – Not possible Used source = simulated system

Introduction: Problem Definition

Product simulated performance results of a DS-CDMA Fading Channel with Bursty Traffic Arrivals so that they can be compared to the results produced by the HMM developed by Landman.

Introduction: Objectives

Create a Simulation Engine (SE) to produce the required results

Make it easy to enter the input variables, start multiple simulations and view the results using a Graphical User Interface (GUI)

Approach: UMTS Environment

Approach: Components

Scenario: Overview

Joe Blogg wants to generate some simulated results to be compared to the results produced by the HMM. He also wants to compare simulated results with were generated at an earlier date to both sets of results

Scenario: List of things to do

1. Start a new simulation with non-default

input variables (to be specified later)

2. Go get coffee

3. Load both the new and old simulated results

4. Compare each of them to the HMM results

5. Go home

Input Variables: Traffic Generation

The desired user, whose performance we are modelling, has packets arriving at the base station, on average, every 1 millisecond when he is really busy. When idle, the user generally has a packet arriving every 15 milliseconds. The probability of him becoming busy, when he is idle is 0.5, while the probability of him becoming idle when busy is 0.1. He has an average packet size of 1280 bits.

Input Variables: Traffic Generation

So we can see that for the desired users– G1 = 15– G2 = 1– r1 = 0.5– r2 = 0.1– B = 1 / 1280 = 0.00078125

Input Variables: Interference

The user is sitting at his desk in his office. There are between 1 and 10 other user’s trying to send out information of different 3G channels at any stage. The probability that the number is near 10 is 0.5, while it is 0.1 for 1 interfering user.

Input Variables: Ending point

The simulator wants simulation results that are relatively accurate So he specifies that the overall confidence in the point estimates should be high. He specifies that he wants to be 95% confident that the real performance results would lie within 5% around the value of the point estimate

Post Coffee Break Progress Update

Joe has just come back from his half hour coffee break and wants to see how far the simulation is.

Post Coffee Break Progress Update

Joe has just come back from his half hour coffee break and wants to see how far the simulation is.

He decides that it will not be done in time for his to compare the results before he goes home in half an hour. So he starts a shorter simulation run with default input variables.

Viewing Results: Past Results

While the other simulation is running, he decides to pause the original one so that the computer does not lag so much. He then wants to compare the results from the simulation he ran yesterday to the HMM results.

Viewing Results: Paused & Completed

Next he wants to bring up the results from the paused simulation

The latest simulation run has completed. He wants to compare all the results.

He wants to resume the original simulation so that it can run over night

Joe is going home

& the lucky man gets to go play golf and then rest with his feet up watching the rugby…

Discussion

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