Traffic models in LTE: Matlab tutorial

In this post we are going to study the main traffic model in LTE: HTTP, FTP and Video. In addition, we will see the Matlab code that you can use to study them on their own or to embed them in a bigger system simulation, as they are structured in functions.

This tutorial is structured in Traffic Model Theory + Matlab code, so you can easily understand and check what the code means. Ready? Let’s get started!

HTTP:

A typical HTTP session is described in the Figure 1.

Figure 1. HTTP session

This is an example of web browsing, where the red lines represent the download times and the off periods are the reading time. This process corresponds with the interaction human-machine that we experiment when using our web browser.

Let’s establish some terminology:

• A page will represent a packet call ON period
• The HTML page will be referred as main object
• Each of the elements inside a main object will be an embedded object

 

Figure 2. Objects distribution in a website

The parameters for the web browsing traffic are as follows:

• MO: Size of the main object in a page
• EO: Size of an embedded object in a page
• NE: Number of embedded objects in a page
• RT: Reading time
• PT: Parsing time for the main page

 

Now, let’s have a look to the Matlab code that implements the HTTP traffic model:

 

 

FTP:

In FTP applications, a session consists of a sequence of file transfers, separated by reading times. The two main parameters of an FTP session are:

 

• F : the size of a file to be transferred
• RT: reading time, i.e., the time interval between end of download of the previous file and the user request for the next file. The underlying transport protocol for FTP is TCP, so we will use a TCP connected to model the FTP traffic.

 

Figure 3. FTP session

 

The Matlab code for this model will be the following:

VIDEO:

Our last traffic model is the video streaming. A video streaming session is defined as the entire video streaming call time. Each frame of video data arrives at a regular interval T determined by the number of frames per second (fps). Each frame is decomposed into a fixed number of slices, each transmitted as a single packet. The size of these packets/slices is distributed as a truncated Pareto. Encoding delay, Dc, at the video encoder introduces delay intervals between the packets of a frame. These intervals are modeled by a truncated Pareto distribution. The parameter TB is the length (in seconds) of the de-jitter buffer window in the mobile station used to guarantee a continuous display of video streaming data. This parameter is not relevant for generating the traffic distribution but is useful for identifying periods when the real-time constraint of this service is not met.

Using a source video rate of 32 kbps, the video traffic model parameters are defined in the following table:

 

And finally, we could translate those parameters and distributions in the following Matlab code:

 

We hope this tutorial was useful! If you would like to see a post about more traffic models, please, leave a comment below 🙂