ADVANCED APPLICATIONS OF ELECTRICAL ENGINEERING

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1 Development of a Software Tool for Performance Evaluation of MIMO OFDM Alamouti using a didactical Approach as a Educational and Research support in Wireless Communications JOSE CORDOVA, REBECA ESTRADA Electrical and Computer Engineering Faculty Escuela Superior Politecnica del Litoral - ESPOL Km Via Perimetral GUAYAQUIL - ECUADOR jecordov@espol.edu.ec, restrada@espol.edu.ec Abstract: - This paper presents the design and development of a software tool that helps to understand the Alamouti MIMO (Multiple Input Multiple Output) OFDM scheme, the tool is presented through some examples and simulation results of image transmission, giving an attractive and dynamic way through a graphical user interface to introduce the MIMO technique, the tool s objective is to increase the interest on this area of research particularly for the Wireless Communications courses at ESPOL, where students will be able to use this tool as a didactical support. Key-Words: - MIMO, OFDM, GUI, Alamouti, STC, Didactical Software Simulator, Wireless Communications. 1 Introduction The use of multiple antennas in wireless systems instead of a single antenna transmitter and single antenna receiver (referred as SISO Single Input Single Output) is now a topic of great interest and ongoing research, so this paper describes the design details of the system based on the techniques used at the transmitter and receiver and describes the graphic user interface (GUI) analyzing results obtained from the interface that was designed. Section 2 presents the Alamouti coding, this is the MIMO scheme to be used in the development of this system, this section focuses particularly on the spacetime coding [1] of data for the two antennas that it uses and the detection scheme. Section 3 gives implementation details of the system, including image signal processing which is the type of signal to work on simulation and also presents the design of the transmitter as well as the description of the receiver algorithm. Section 4 presents the results of the developed system, these results include screenshots of the GUI developed and details of the usability of the system, besides presenting the results in image format to identify the channel effects on the received images. 2 Alamouti STC S. Alamouti in [2] proposed a scheme of space-time block coding (STBC) [1] technique to achieve diversity transmission using two antennas at the transmitter and one antenna at the receiver, a 2x1 MIMO system. The transmission operation is explained in Table 2.1. INSTANT ANTENNA 1 ANTENNA 2 Table 2.1 Alamouti STC Scheme In this scheme we will assume that the channel is under flat fading and the channel also remains constant over two symbol times. The code generation matrix for the Alamouti scheme on transmission will be: (1) On (1), the first row of the S Matrix corresponds to the transmitting information on the Antenna 1 and the second row corresponds to the transmitting information on the Antenna 2. With the assumption that channel is under flat fading for the MIMO 2x1 configuration in study will be two different propagation trajectories for the channel: (2) ISSN: ISBN:

2 For each of the paths will have different and independent coefficients which represent the fading on each route: (3) (4) Then the corresponding system responses for each of the transmission instants are show on Table 2.2. TIME Table 2.2 Channel Response. RESPONSE Table 2.2 shows that at the receiver we will have to wait two symbol times to construct a reception vector, this reception vector is shown in (5). (5) For the channel Matrix H as is shown on (5) we will calculate the conjugated transpose: (6) With the matrix at (6) we will be able to multiply the received signal after the two symbols times with the matrix at (6) and we will have: (8) In (8) we can see that we already have estimated the transmitted symbols only with a scale factor produced by the channel and an additive term corresponding to white noise, we can recover the original signal with an ML (Maximum Likelihood) detector which will estimate the s signal. 3 MIMO OFDM Solution design 3.1 System Design specifications In the designed systems we have considered using images as the signals for transmission, so we have included a process for digitize those images. The MIMO technique will be the Alamouti encoding scheme described before, also we will implement the SISO system so we would be able to compare both systems. The Alamouti scheme will be evaluated using Orthogonal Frequency Division Multiplexing OFDM modulation; we will use the specifications in the Table 2.3. PARAMETER VALUE FFT Points 64 Number of Data Subcarriers 52 Number of Bits per Symbol 52 Cyclic Prefix 1/4, 16 symbols Total Number of Subcarriers 64 Guard + Symbol 80 Zero Padding 12 symbols Table 2.3 OFDM Specifications The main focus of the simulator will not be to evaluate the OFDM performance; so the parameters specified in Table 2.3 will remain with no changes and also it is assumed that receiver has full Channel State Information (CSI) in order to focus on the Alamouti performance. OFDM detection is based on frequency domain equalization as its explained in [3], the detection scheme for Alamouti coding presented in the past section assumed that channel is under flat fading, in this design we will use the combination of MIMO Alamouti with OFDM. OFDM converts a frequency selective channel into a set of parallel flat fading channels [3, 4]; with this collection of channels the detection scheme for Alamouti could be used in each of the flat channels. 3.1 Simulation details Image processing For the simulation system we have considered processing an image signal, the processing of the image signal prior to use this signal on the MIMO OFDM system is shown in the Figure 3.1. which describes the use of MATLAB [5] function imread, this function digitalizes the image, the process as is shown operates with a JPG 1 file and the resulting signal is a variable in RGB format, as is shown will 1 Joint Photographic Experts Group Image Format ISSN: ISBN:

3 be one matrix for each of the colors of RGB format (Red, Green, Blue). Then we will have that height and width of the image will be the number of rows and columns of each of the resulting matrices and each image color pixel will be represented by the three corresponding values of the elements of the three matrices describing each pixel within its composition of Red, Green and Blue respectively. original matrix but is ready to be mapped into symbols using a BPSK 2 modulation scheme. Having the modulated symbols, these are ready to be assembled into OFDM symbols according to the specifications, in Figure 3.2 is shown the modulation process mentioned before and additionally is represented the symbol formation including zero padding. Each of the matrix s rows represents one OFDM forming symbol at the frequency domain. Figure 3.1 Each element of each RGB matrix will be a value between 0 and 255 which determines the quantity of red, blue and green of the pixel s composition. We will now obtain a binary representation of each of the values for each of the matrices, then, if the image size is MxN pixels, the total of bits for the binary representation will be MxNx3x8, this is because each value between 0 and 255 will need 8 bits to digitize on each of the three matrices. In order to reduce simulation times, our system is designed for processing black and white images, this is why after digitizing the image, using imread, the resulting signal will be converted into a black and white (B/W) signal as Figure 3.1 also describes. Then the resultant signal will be a single binary matrix which will represent the image in B/W format, this signal-variable is then ready for processing in our system Transmission process description The transmission process is the major focus on the system developing; the transmitter will include the space-time encoder which will prepare the system for MIMO transmission. The digitized image signal will be transformed into a long vector which contains the same information that Figure 3.2 The set of symbols must be processed with a spacetime encoder, the Figure 3.3 shows the Alamouti coding process, each matrix in the figure represents the set of coded signals that will be transmitted in each of the transmitting antennas. With the set of symbols coded for each antenna those symbols continues with the OFDM modulation process, IFFT symbol conversion from frequency to time and Cyclic Prefix insertion, as shown in Figure 3.4. Numero de Simbolos Puntos FFT s1 s2 s3 s4. sn STC Figure 3.3 Antena 1 Antena 2 2 Binary Phase Shift Keying Numero de Simbolos Numero de Simbolos Puntos FFT Puntos FFT s1 -s2* s3 -s4*. s2 s1* s4 s3*. ISSN: ISBN:

4 The channel model depends on the number of symbols; this condition will allow keeping multipath fading independent from each symbol and from each antenna. Receiver analysis and signal recovering is based on the inverse process of the OFDM modulation described before, removing the cyclic prefix and taking back the signal to frequency domain using FFT is performed prior to apply the channel considerations and detection scheme for Alamouti stated at section 2, after Alamouti detection symbols are disassembled removing zero padding and then BPSK demodulation finally recovers the original image. In Figure 4.1 (a) is shown the Graphic User Interface developed for the system, in detail (b) shows the interface created for the user selection of the image to use in the simulation and the corresponding control to change the noise relation, also a graphic representation of the noise is presented. In (c) are shown the controls for setting multipath channel parameters which allows changing between multipath and AWGN 3 only, flat fading and frequency selective fading and the number of taps for the frequency selective fading. (a) GUI for Simulator Figure Graphic User Interface and Applications The developed system will be didactical Support tool for the Wireless Communications courses at the particular case of ESPOL, students who takes these courses are not familiarized with current techniques for signal processing in communications like OFDM or in MIMO, so developing a graphic tool will help not only for improve the learning of students but also for create interest in new topics of wireless communications improving the educational and research capacity at ESPOL. The system focuses on demonstrate and evaluate the performance of Alamouti scheme in a wireless link, the idea is to keep the algorithm and usability of the system the simplest, this will allow users to focus on the application of the theory demonstrated in section 2. (b) Signal selection and Noise variance, (c) Multipath fading parameter setting. Figure Additive White Gaussian Noise ISSN: ISBN:

5 After running the simulation with the transmission control another graphic panel is activated for results analysis in the Figure 4.1 is a screen capture where can be seen the image processing details and the corresponding buttons for showing the original image before transmission, the recovered image and the contrast for identifying errors. Figure 4.3 (b) B/W digitized Image. (a) MIMO OFDM results panel, In the panel described before can be evaluated the results according to the image transmitted, as an example in figure 4.3 (a) is shown the original image with JPG color format, in (b) is shown the MATLAB digitized version of the image, as explained in section that image is in black and white format. (b) OFDM result details Figure 4.2 In Figure 4.2 (a) can be seen the quantity of bit errors, BER 4 and simulation time of MIMO OFDM system, in (b) is shown the same information for the OFDM system, users will see that using MIMO Decreases the error rate to one third of the original (a) Recovered Image with OFDM (a) Original JPG color Image, 4 Bit Error Rate Figure 4.4 (b) Recovered Image with MIMO OFDM. In figure 4.4 (a) is shown the recovered image using OFDM and (b) the recovered image using MIMO OFDM where you can identify graphically the improvement within the use of MIMO versus not using it. ISSN: ISBN:

6 Figure 4.5 shows the representation of channel that is available in GUI, as an example is shown a flat fading channel in time and frequency domain, and a 10-tap frequency selective channel, this graphics have didactical purposes and corresponds to the actual simulated channel at different instants of time. A very important approach is the evaluation of the results in BER vs. SNR plots so as can be seen in Figure 4.6 (a) the evaluation of the OFDM system, blue line, the MIMO OFDM system, cyan line, both evaluated under multipath fading, the green line corresponds to evaluation of the system without multipath fading which is only under AWGN, the users of the simulator would generate these plots and recognize the effect of the different system parameters. which is wrong to conclude since no corrections have been made for power. With the correct power adjustment, we can obtain the plot shown in Figure 4.6 (c), where can be seen that MIMO OFDM BER curve follows the same trend with the change in the number of channel taps, this plot will lead the users to the right conclusions and to determine why Figure 4.6 (b) is incorrect. (a) OFDM SISO, MIMO OFDM Alamouti, AWGN MIMO OFDM (a) Frequency Selective Fading, (b) MIMO OFDM without Power adjustment from 1-10taps, (b) Flat fading. Figure 4.5 GUI representations. In figure 4.6 (b) is shown the effect of power correction and adjustment that is necessary for channel based on number of taps and number of transmitting antennas, with a didactical approach users would understand that to evaluate two systems MIMO versus SISO they have to be under the same power conditions, In the plot is shown that apparently as the number of taps increase the BER curve improves its behavior under multipath noisy channel (c) MIMO OFDM with Power adjustment from 1-10taps. Figure 4.6 ISSN: ISBN:

7 5 Conclusions and Future Work This work has achieved its goal of serving as a support tool, has developed a friendly interface that is used to help increase the capacity of education and development of young researchers with simple examples, keeping a simple approach can identify and evaluate a complex system which is attractive to students. Moreover the developed system focuses fairly according to the results in evaluating the performance of MIMO technology and provides guidance in the understanding of these concepts in a graphical way and practice to students, as well as variants such as those related to adjustment of power demonstrate the great ability to support education in wireless communications. The platform developed not only serves as a support tool but also could be used in implementation, we are currently in the development of the physical evaluation of this system which is based on transmitting the signals generated in the simulation with MATLAB and then use the detection algorithm also used in the simulation, this scheme is known as "Offline Test bed," our future work will focus on evaluating the testbed and MIMO channel estimation. References: [1] A.B. Gershman, N. D. Sidiropoulus, Space-Time Processing for MIMO Communications, Wiley,2005. [2] S. M. Alamouti, A Simple Transmit Diversity Technique for Wireless Communications, IEEE Journal on Select Areas in Communications, vol. 16, no. 8, Oct [3] Y. Li and G. L. Stüber, Orthogonal Frequency Division Multiplexing for Wireless Communications, Springer, [4] H. Bolcskei, D. Gesbert, and A. J. Paulraj, On the capacity of OFDM-based spatial multiplexing systems, IEEE Trans. Commun., vol. 50, no. 2, pp. 225{234, Feb [5] MATLAB, Online Reference Guide, c/matlab.shtml. ISSN: ISBN: