Implementing Of Uwb Simulation 4 1 Matlab Computer Science Essay

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In this chapter is introduced the MATLAB Simulink to implement the Simulink models. The model was improved by fundamental models and developed block by block. Mainly the Additive White Guissian Noise(AWGN), Multipath Rayleigh fading and effects of multipath propagation has taken in to consideration for designing the system model.

Hardware applications of Communication Engineering implementation is important part in the simulation testing. MATLAB simulation software is one of key factor in communication Engineering product designing in the world. MATLAB Simulink is one of the main platform for multi domain simulation. And also has used for model based designing in the dynamic systems. It has provided interactive graphical environment and a customizable set of block libraries. From this software can be simulated and the practical scenarios systems well as can be monitored and analysed. The blocks consists of tools can be used not only for testing and also validating accuracy results.[15] For this project was used MATLAB Simulink to carry out the UWB channel system implementation based on IEEE802.15.3a standard.

4.2 UWB Channel Model Implementation

To implement the UWB wireless Communication System has divided in to two parts.

Implement UWB channel Simulink with AWGN channel and Multipath Rayleigh fading channel.

Develop the Simulink from adding OFDM Transmitter and OFDM Receiver

The basic UWB channel system Simulink path with AWGN channel and Multipath Rayleigh fading channel has implemented shown as below in Figure 4-1.

4.2.1 Implement UWB channel Simulink with AWGN channel and Multipath Rayleigh fading channel

Figure 4-1: UWB channel Simulink with AWGN channel and Multipath Rayleigh fading channel

At the beginning of implement the system was designed for indoor environment applications within 30m distance, different data rate such as 110Mbps, 200Mpbs and 480Mbps by using UWB frequency ranges. with Bernoulli binary generator , QPSK modulator and demodulator, error rate calculator and display. Bernoulli binary generator was set the samples time 1/48 according to the IEEE802.11n standard. The Simulink and parameters was discussed in Chapter 4.2, 4.3 sections .Then that model developed with adding Convolutional encoder and Viterbi Decoder. The convolution encoding block set to 2 level signals. And also set the trellis structure to poly2trellis (7, [133 171]). Then set the operation mode to continuous. Viterbi Decoder also set was to the Trellis Structure poly2trellis (7, [133 171]. The trace back depth was set to 34. Adding delay unit was able to overcome the delay time to synchronize with the receiving antenna. Therefore the delay unit has set to z-34. Then output of Viterbi decoder was connected to the receiver port in the Error rate calculation block. Transmission path was connected via delay unit.

This simulation model was created with QPSK Modulation and convolution encoding. But these two blocks cannot be connected together, because QPSK modulation required 4level signals and output of the Convolution Encoder block was two level signals. Therefore need to add Bit to integer convertor well as Integer to bit convertor. In the Bit to integer block the parameter, number of bit per integer was set to 2. Then integer to bit convertor has obtained two level of signals from output of QPSK modulation 4 level signals. AWGN channel was added from the library and check the performance with changing the SNR value with Calculate the Error rate(Bit error rate).

Then after added the Multipath Rayleigh fading block connected to the model as shown in figure4-1. Then after evaluate the performance of Rayleigh Fading channel and AWGN channel with varying the SNR values Doppler effect. Then the error rate block was connected to the display to show the Bit error rate.

4.2.2. Develop the Simulink from adding OFDM Transmitter and OFDM Receiver

Figure 4-2: UWB channel system with OFDM Transmitter and Receiver.

Figure4-3: Block set of inside the OFDM Transmitter

Figure 4-4: Block set of inside the OFDM Receiver

In this section, OFDM transmitter subsystem block and OFDM receiver subsystem block has added to the Simulink block set. As Figure 4-3 was shown OFDM transmitter subsystem and OFDM receiver subsystem were connected before and after the UWB channel block respectively to the previous model.

Output of the QPSK modulator block was connected to multiport selector to make the signal to subcarriers and it is called multi carrier transmission. The parallel signals was called subcarriers and these 48 number of sub carriers was guided from four pilot carriers. The 12 number of guard bands were set to the sub carriers on the top middle and the bottom. The matrix block was used to make (64=48 data sub carriers +4 pilot carriers+12 guard bands) carriers. The OFDM Subcarriers Arrangement has shown in figure 4-3 and has shown how the subcarriers, pilot carriers and guard bands are appears in after the Matrix Concatenation1 block .The 64x1 matrix signals then has gone to IFFT block which frequency domain signal was converted to the time domain signal. Then the subcarriers were made for the orthogonal by using mathematics in IFFT (Inverse Fast Fourier Transformation). The Cycle prefix block was added to avoid the mixing of sequence OFDM symbols in the receiver. It was a advantage of by reducing the cause interference. The cyclically extended in the guard time at the transmitter to avoid inter carrier interference. The AWGN channel block was connected to the eliminate Cyclic prefix block to remove cyclic prefix added in the transmission side. [17]

The FFT (Fast Fourier Transformation)block was used to make the time domain signal in to frequency domain signal. Then that signal goes to the To Frame block .That signal converted in to frame base signal. Then frame base signal was gone to the Remove Zero-padding and reorder blocks. In there guard bands were removed which were added at the OFDM transmitter. Finally Pilots carriers were identify and terminated by was using Select Rows block. The receiver block was operated as the opposite of the transmitter block.

4.3. Setting up block parameters

4.3.1 Bernoulli Binary Generator

The Model generates the random data using the Bernoulli Binary generator which generates data bits by uniform distribution. As shown in below the Bernoulli distribution parameters have set to according to the UWB channel model. The parameter which probability of zero has showed value for produces zero with probability p and one with probability 1-p. The Probability of a zero parameter has specified 0.5 value. In this scenario samples per frame has get 48 according to the stranded of OFDM system[17]. The UWB channel system validated according to these bit rates 110Mb/s, 200Mb/s and 480Mb/s in order to 10m-30m, 4m and 2m distance. For the bit rates 110Mb/s, 220Mb/s and 480Mb/s have used sample time respectively 2.18E-7, 1.2E-7 and 8.571E-8.

Figure 4-5 Bernoulli Binary Generator parameter block

4.3.2 Convolutional Encoder

Figure4-6: Convolutional Encoder

The convolutional encoder block has used to encode a sequence of binary input vectors of producing a sequence of binary output of vectors. Another advantage is has able to process multiple symbols at a time. The Trellis structure parameter has used to define the convolutional encoder which poly 2 trellis command architecture. It has contained constrain length, generator polynomials and possibly feedback connection. Polly 2 trellis (7,[133 171]) command was used in the project. According to the command 7 which has constrained length, and command that[133 177] contained with generator polynomials and also 171 is a possible feedback connection[15] .

The constrain length has specified the number of bits stored in each shift register with including the current input bits when constrain length equal to the 7, therefore there should be 6 shift registers. The generator polynomials has specified the connection from the outputs of the register to the adder, but the value has set to the 133,171 that has been in octal format. when this parameter has being converted to the binary format it occurred like as way 133=1011011 and 171=1111001.In that binary format 1 indicates connection to the adder and 0 indicates no connection to the adder[17]. The input and output sizes for the data ports, the block supports double, single, Boolean, int8, uint8, int16, uint16, int32, uint32, and ufix1.[15] The port data types have inherited from the signals that drive the block. The input reset port supports double and Boolean typed signals.

Figure4-7: convolutional Encoder parameter block

4.3.3 Viterbi Decoder

Figure 4-8 :Viterbi Decoder[15]

Viterbi Decoder use the Viterbi algorithm to decode which has convolutional encoded input data. The Viterbi decoder use same method which Polly 2 trellis function that had use in encoder, to create a trellis using constraint length, code generator, and feedback connection. When the code rate is &Acirc;½ the trace back depth have to be five times the constraint length. Operation mode parameter controls which method the block has used as the convolution encoder use[15].

4.3.4 QPSK Modulation and Demodulation

Figure4-9: QPSK modulator and QPSK Demodulator [9]

The QPSK Modulator Baseband block modulates input signals that has using the quaternary phase shift keying method. Demodulator block has demodulated the input signals also using same method. The parameter of phase offset has used to change the phase of the signal in consolation. The output is a baseband the modulated signal has represented. There has two types of input parameters which one type is bit and another one is integer. The input type set to integer then the block can be accepted the data types int8, uint8, int16, uint16, int32, uint32, single, and double. Set to the bit inputs, the block can accept int8, uint8, int16, uint16, int32, uint32, Boolean, single, and double.

4.3.5 AWGN Channel

Figure 4-10: AWGN Channel [15]

Additive White Gaussian Noise (AWGN) referred as thermal noise and it has generated cause, motion of the electrons. AWGN channel present in all communication channel and also it is a function of temperature. In the real world occurrence can be added to the simulation process by using AWGN channel block. At the simulation consider If the input signal is real, AWGN block adds real Gaussian noise and produces a real output signal. When the input signal is complex AWGN block adds complex Gaussian noise and produces a complex output signal.[15] Input signal power parameter allows changing the mean square power of the input symbols. Mode parameter allows specifying the noise variance. [10]

The transmitted signal has being send through the AWGN channel. The SNR value can be change as desired. This block can change the amount of noise in the channel and also when the transmitting signal is going through in the channel path, noise will be added to the signal as real world scenario. The sample time is inherited from the input signal. Parameters are shown in below.

Figure4-11: AWGN Channel parameter block

4.3.6. Multipath Rayliegh Fading

Figure4-12: Multipath Rayleigh Fading

In the real world mobile wireless communication systems occurs noise , interference well as fading in the channel. The Multipath Rayleigh Fading Channel block has act in a baseband simulation of a multipath Rayleigh fading propagation channel. This block preferred only frame-based complex signals at its input. The input signal should be discrete sample time greater than 0.

Between the transmitter and receiver causes Relative motion of Doppler shifts in the signal frequency. From this block able to change the Doppler spectrum type parameter by the Rayleigh process. In this Simulink considered the channels with multiple paths, which able to assign each path a different Doppler spectrum, by assigning a vector of Doppler objects in the Doppler spectrum field. Because a multipath channel reflects signals at multiple places, a transmitted signal travels to the receiver along several paths, each of paths may have different lengths and associated with time delays.[15]

Another parameter is Average path gain of in the Rayleigh fading channel .From this able to change normalize gain vector to 0 dB overall gain or specifies the gain for each path. By selecting the average path gain vector its choosing gain itself, choosing the scaling factor so that the channel's effective gain considering all paths, is 0 dB. In this UWB channel model consider 0.001W the small effective of gain to the path and experiment the UWB channel how it performance .

4.3.7. Scope

Figure 4-13: Scope

The Scope block displays the input with according to simulation time. This block which have multiple axes (one per port) and all axes have a common time range with independent y-axes. And also allows to adjust the amount of time and the range of input values for display. When move and resize the scope window and it able to modify the Scope's parameter values during the simulation.

4.3.8. Buffer

Figure 4-14: Buffer

The Buffer block rearranges the input samples to a new frame size. Buffering to a larger frame size has produced an output with a slower frame rate rather than the input, and has illustrated below for scalar input.