System Setup

1. The software of “IviSharedComponents” and “IviVisaSharedComponents” are installed on the PC. Then the IVI instrument drivers of the VSG and VSA are installed on the PC. After that, the MATLAB of version 2011 is installed on the PC. The MATLAB must contain the instrument control toolbox which is used to connect and control the instruments through software. Finally, the “Agilent IO Libraries Suite” is installed on the PC.

2. The 2.4GHz antennas are connected to VSG and VSA, respectively with cables. Then they are fixed with two separate stable station in order to get steady signal while transmitting and receiving data.

3. The two instruments, VSG and VSA, should be physically connected to the PC through the Ethernet/LAN router with cables. Turn on all of the instruments. Then detecting the instruments through PC. Opening the Agilent IO window, the two instruments, VSG and VSA, can be detected through TCPIP address

and added into the IO control window. If these two instruments are connected to the PC well, then connection should be done and smoothly.

4. This step is to connect/interface the instrument to MATLAB through the PC so that the instruments may be controlled from MATLAB. Then the device and interface objects should be created. The instruments can be connected to the MATLAB by utilising either of these objects. However, the interface objects are used to send the data from the MATLAB to the instrument or to receive the data in MATLAB from the instrument whereas the device objects are used to change different properties of the instrument and perform different functions in the instruments through MATLAB.

5. The final real-time wireless communication system test-bed is shown in Figure 5.1.

Communication between PC and Instruments

In this subsection, the communication method between MATLAB in the PC and the instruments is described, which is used as the main communicating method of this project.

The TCP interface objects of both instruments VSG and VSA are firstly required and created. The creation of the TCP interface objects command can be expressed as

tcpobj=tcpip(‘192.168.0.1010,5025), (5.1)

where ‘tcpobj’ is the variable name of the TCP interface object, ‘192.168.0.101’ is the TCP address of the instrument V2920A taken from “Agilent Connection Expert” and ‘5025’ is the socket no of the instrument. The instrument can be connected and disconnected to the MATLAB using this interface object with the following commands in the command window

f open(tcpobj); f close(tcpobj). (5.2)

From now onward, The communication can be processed directly between MATLAB and the instruments through the LAN interface.

Sending IQ data using MATLAB

• A MATLAB script named “SenData.m” is used for this purpose. The inputs are the IQ data sequences with the sample rate in Mega-sample-per-second (Msps).

• The IQ data is a vector of numbers according to the desired modulation scheme. If BPSK is used, then IQ data is a real vector while it is a complex vector if QPSK or QAM is applied. The IQ data is a time based description of the data which should have an even amount of numbers. If not, an error message occurs in the VSG while transmitting data. Before sending the data to the VSG, the data has to be ready up-sampled, pulse shaped, IFFT if it is OFDM. The IQ data sequence is the final data exactly how the VSG transmit in the time domain.

• The “samplerate” in the sending IQ data command is in Mega-sample per second (Msps) which is specified for the signal MiesterR software. There are specific values that can be taken. If an arbitrary sample rate is imputed, it will be automatically allocated to the nearest allowed value. However, this mechanism is not very beneficial since the data would be up-sampled by the machine and might not be able to down-sampled accordingly after the IQ data extraction. In order to obtain an real-time accurate communication on this platform, a sample rate should be selected carefully.

Extracting IQ data using MATLAB

• Another script named “GetData.m” is used to extract the IQ data from the VSA. The input variables are the output data from VSG convoluted with wireless channel which added with Gaussian Noise.

• The variable is used to tune the extraction parameters, so that the appropriate part of the IQ data can be extracted appropriately.

• The extracting process is based the received time-domain IQ data sequence. It might be oversampled since the VSA extracts data at a minimum of5₄ of its input. However, if the setting is carefully modified, the extracted data would be the same

Figure 5.2: The Reverberation chamber at the University of Liverpool

rate as was in-putted. The approach that has been taken is to oversample the data manually before transmitting with VSG; then a filter bandwidth is setted to

4

5 times the value of the input sample rate data. Under this way, the extracted

data is the same rate as the data that was transmitted.

• Another parameter called out-sample-rate is applied by the VSA to extract the re- ceived data. It can be used to determine the down-sampling ratio if the technique in the preceding point is used used.

• This getting data script is well commented and is easy to follow. When a large amount of IQ data is being extracted, the value of the pause has to be increased to allow the data to settle in the VSA.