Here’s an excerpt:

The concert hall at the Syndey Opera House holds 2,700 people. This blog was viewed about 58,000 times in 2011. If it were a concert at Sydney Opera House, it would take about 21 sold-out performances for that many people to see it.

Click here to see the complete report.

the current release is ns3.10 (January 5, 2011) and can be downloaded from DOWNLOAD NS3.10

Step 1: Download ns3.10 and save it some where , but on the same machine where you want to install (Just Kidding )

Step 2: open the terminal and go to the folder where ns3.10 tar file is.

Step 3: from the terminal run :

$tar -xvf ns-allinone-3.10.tar.bz2

$cd ns-allinone-3.10

$./build.py

you can provide some options to build.py but as a newbie use the default one

When the build process get over (it will take some time), type

$cd ns-3.10

and now we will validate our installation

$./test.py

the out put of this will be some thing like this:

Waf: Entering directory `/media/Installations/ns-allinone-3.10/ns-3.10/build’

Waf: Leaving directory `/media/Installations/ns-allinone-3.10/ns-3.10/build’

‘build’ finished successfully (2.010s)

PASS: TestSuite lte-bearer

PASS: TestSuite lte-propagation-loss-model

PASS: TestSuite wimax-fragmentation

PASS: TestSuite lte-phy

…………..

PASS: Example examples/tcp/tcp-nsc-lfn

PASS: Example examples/wireless/wifi-ap.py

PASS: Example src/contrib/flow-monitor/examples/wifi-olsr-flowmon.py

168 of 168 tests passed (168 passed, 0 skipped, 0 failed, 0 crashed, 0 valgrind errors)

 

$ cp examples/tutorial/first.cc scratch/myfirst.cc

$./waf

Step 5: now it is the time to run the simulation

$cp examples/wireless/ofdm-validation.cc scratch/myofdm.cc

$./waf

$ ./waf –run myofdm

The Blog-Health-o-Meter™ reads Wow.

Crunchy numbers

About 3 million people visit the Taj Mahal every year. This blog was viewed about 39,000 times in 2010. If it were the Taj Mahal, it would take about 5 days for that many people to see it.

In 2010, there were 3 new posts, growing the total archive of this blog to 38 posts. There were 8 pictures uploaded, taking up a total of 39kb.

The busiest day of the year was November 22nd with 199 views. The most popular post that day was How to install Matlab and how to make it work on Linux ?.

Where did they come from?

The top referring sites in 2010 were google.co.in, google.com, linuxidx.com, blogsurfer.us, and google.com.pk.

Some visitors came searching, mostly for digital communication tutorial, install matlab ubuntu, digital communication system, ofdm, and dfts-ofdm.

Attractions in 2010

These are the posts and pages that got the most views in 2010.

How to install Matlab and how to make it work on Linux ? June 2009
41 comments

Tutorial I : Basic Elements of Digital Communication System July 2009
7 comments

Error with ns2 Installations – NS2 Revisited ! May 2009
60 comments

How to install NS2 on Fedora 10 (Cambridge)? December 2008
58 comments

How to install ns2 on Red Hat Linux January 2009
12 comments

We are conducting a Poll to know in which direction we should take this blog. It is our request to every one to cast their votes in the poll and make us know about your views, we will appreciate you will comment also.

The link to the poll

Cast the votes and leave the comment.

Thanks and Regards,
WirelessCafe Team !

Give a look to the above mentioned link.

Regards,

WirelessCafe Team !

Mutual Information:

The information content provided by the occurrence of the event Y = y_i about the event X = x_i is defined as

Mutual Information

I(x_i;y_j) is called the mutual information between x_i and y_j.

Self Information:

when we talk about the information of a single event X= x_i we called it self information and is denoted as

Self Information

it is a matter of fact, that , a high probability event conveys less information than a low probability event. That is, P(x) = 1 which means I(x) = 0.

Conditional Self Information:

In addition to self information and mutual information, conditional self information as

Conditional Self Information

Average Mutual Information:

the mutual information associated with the pair of the events (x_i,y_j), which are possible outcomes of the two random variables X and Y, we can obtain the average value of the mutual information by simply weighting I(x_i,y_j) by the probability of occurrence of the joint event and summing over all possible joint events.

Mathematically

Average Mutual Information

as a matter of fact, I(X;Y) = 0 when X and Y are statistically Independent. Also I(X;Y) ≥ 0.

Entropy:

Entropy or Average self information denoted as H(X) and defined as

Entropy

Conditional Entropy:

the average conditional self information is called conditional entropy

Conditional Entropy

we also get the relation from the above the equations

Relation Between Information and Entropy

Here is a plot of binary conditional entropy produced in matlab. In next post we will discuss some left over theorems of source coding like Kraft’s inequality and will start some real coding work !

binary entropy function