Orthogonal frequency division multiplexing (OFDM) is an improved
enhanced type of multicarrier transmission, where we can transmit a single data stream over a number of lower rate subcarriers.
Due to its important advantage -that is this technique efficiently uses limited frequency spectrum with the orthogonal subcarriers enabling spectral overlapping without interfering, and providing high data rates in severe transmission conditions encountered in wireless radio channels, OFDM has already been implemented in a number of standardized wireless communication systems. DAB (digital audio broadcasting), DVB (digital video broadcasting), IEE 802.11a/g/n are examples of these systems. Moreover, orthogonal frequency division multiplexing has found its place in the fourth generation (4G) of the broadband wireless communication: WiMAX (worldwide interoperability for microwave access) and 3GPP-long term evolution (LTE).
In the previous semester, we were able to study this technique very well, going through every single element of its whole structure, and trying to understand any concerning method of communication we could use.
In this part of our project, we are to implement a full MATLAB model (transmitter and receiver) of OFDM. We will also prepare codes to use it in many environments of broadband wireless communication systems. IEEE 802.11a will be considered and implemented with its well-known specification.
As we already read about OFDM, we could find that this technique consists of 5 or more elements in each side of any communication system. The most important and sensitive parts are mentioned as the following:
· Modulation and demodulation techniques.
· Coding and interleaving methods.
· Mapping and channel estimation.
· The Inverse Fast Fourier Transform (IFFT) in the transmitter side, and FFT in the receiver.
· The cyclic prefix (CP) in the transmitter, and its inverse (R-CP) in the
receiver.
Including the channel, and adding noise (AWGN) to it, we are going to have a complete model starting from sending data, and ending with receiving the same data with high speed and acceptable efficiency.
However, many different shapes can be built to introduce an OFDM
wireless system.
During this semester, our job was to go more deep and find more about every block exists in the previous figure. We were able to implement them using a MATLAB model; moreover, it was a good step to do each operation of these blocks using codes, which would be more clear and easier to understand.
Using the MATLAB Simulink, we have built a complete OFDM model starting from generating data arbitrary, and ending with having the same data at the receiver side.
Many parts of OFDM have been used in our simulation of IEEE 802.11a physical layer transmission using OFDM, those parts are:
* All mandatory and optional data rates: 6, 9, 12, 18, 24, 36, 48, and 54 Mb/s * BPSK, QPSK, 16-QAM, 64-QAM modulations
* Forward error correction coding (convolutional; code rates 1/2, 2/3, 3/4)
* OFDM transmission: 52 subcarriers, 4 pilots, 64-pt FFTs, circular prefix
* Data interleaving
* PLCP preamble (modeled as 2x2 long training sequences)
* Receiver equalization
* Viterbi decoding
* Data rates selectable on-the-fly
* Adaptive modulation demo over dispersive multipath fading channel
We consider IEEE 802.11 a standard in which all its physical layer attributes has been included for example PLCP preamble which is shown below :
We send first 12 symbols 10 for short training and 2 for long training ,the short training use to detect the beginning of the frame and the long training use to estimate the channel to equalize the impact of the channel .
After that , we send The signal field which consist of many field ,the most important one is the rate field which determine the bitrate we want to simulate at the receiver and the length of the data in octet .
After that , we send our data which is in this case an audio bits in symbols , where the symbol consist of 48 data constellation point and 4 pilot to estimate frequency offset .
At the receiver , we receive the 10 short training sequence and detect the start of our frame .Then we receive 2 long training sequence and use it to determine the channel coefficients . After that we receive the signal field which determine the data rate that we transmit the data in and make all the operation that is needed to decode the data , recover the error data and rebuilt the audio file .
All we had done is about to transmit an audio file after convert it to bits code it using punctured convolutional code , interleave the data , demodulate the data and send it over the channel which adds noise to transmitted data . At the receiver we inverse all the operation were done in the transmitter and recollect the decoded audio file .