Optimisation Of Transreceiver For Mimo System

OPTIMISATION OF TRANSRECEIVER FOR MIMO SYSTEM Abstract MIMO stands for multiple input, multiple output and refers to the use of more than one antenna to send and receive two or more unique data streams over the same channel simultaneously in wireless devices, resulting in networks with long ranges and high throughputs .MIMO products create wireless networks that can reach significantly farther than current Wi-Fi networks and still provide high data throughputs.MIMO technology can reach over 300 feet and still send and receive data at 30 mbps.

Introduction Traditional wireless communication system uses a single antenna for transmission and a single antenna for reception. Such systems are known as single input - single output systems (SISO) . Usage of multiple antennas at transmitter and receiver in order to achieve better performance such systems are known as multiple input multiple output systems (MIMO).main challenge that exists is about implementing it in point to point links.

In the above fig. there are three antennas in the transmitter and receiver .For the transmission of data we have taken a bit stream b0,b1,b2…..The data stream is divided into three data blocks consisting of b0,b3,b6…, b1,b4,b7….., b2,b5,b8….

These data stream is modulated by certain modulation scheme for transmission .These transmitted stream is received by the receiving antenna B1,B2 and B3.The transmitted signal is then demodulated and are converted back into the data stream.

Mathematically…………….

The channel capacity for different antennas at the transmitter and receiver side are compared .Starting from 1 antenna at transmitter and receiver side to 4 antennas at the transmitter and receiver side the graph between the channel capacity and the SNR in db is plotted .

From the above fig it can be concluded that the channel capacity is better for 4x4 antenna and least for SISO(1x1) system.

EFFICIENT MODULATION TECHNIQUE……..

The above fig compares the probability of error for different modulation schemes .It is seen that the modulation technique like QAM, QPSK , MSK gives us a better result. Here the red line implies that for about 10^6 bits transmitted the error occurred in only 1 bit. So for the experiment basis we may use any of these above methods. Here the QAM(quadrature amplitude modulation) is considered. This modulation technique is applied to the original signal and transmitted.

THE CHANNEL………… For mobile communication we usually consider the RAYLEIGH channel.For large no. of paths, each path can be modeled as circularly symmetric random variable with time as the variable and this modeled is called as the “RAYLEIGH fading channel”. For any signal transmitted in the channel there is always introduction of noise which distorts the original signal. At the receiver end the resulting signal is obtained .The bit error rate (BER) vs SNR is calculated for this signal obtained .

As we can see that due to interference of noise the graph is not smooth. So a equalizer should be designed which will have a opposite effect than that of the

transmitter. There are different equalizer. The LMS (Least Mean Square) algorithm is used . After applying the LMS algorithm to the received signal and also applying different de modulation schemes we obtained the following output

QPSK modulation modulation

PSK modulation modulation

QAM-16

QAM

From the above diagrams we can conclude that the QAM modulation is giving the better result

Conclusion … MIMO system improves the channel capacity than the SISO system. QAM is the best modulation scheme for the MIMO system.

REFERECES…….. T.S.RAPPAPORT-wireless communication-Phi publication MATTIAS WENNSTORM UPASALA-On MIMO system and adaptive array for wireless communication.