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Matlab Code For Serial To Parallel Conversion In Ofdml

I'm building basic matlab code for ofdm, but when I change the CP OFDM into ZP-OFDM with sme parameters, I get the performance is worse by up to 10 dB!! Is that right ? or there is some thing wrong in the code !!

Matlab Code For Serial To Parallel Conversion In Ofdml


Abstract- In the actual scenario of communication, present day chips have parallel data bus but for long distancecommunication laying down parallel channels for every bit is costlyand hardware consuming. Therefore, we use only a single channel tocommunicate between the two ports i.e. transmitter and receiver.For the receiver chips we use serial data from the channel andconvert to parallel for future use.

The task of a serial to parallel converter is to take a stream of datain serial format and for N-bit parallel converter, give N-bits asparallel output. Parallel data is required in several places likecommunication in a network, radar equipment etc. But the data cannot befed to these systems in parallel format as the external hardwarebecomes cumbersome. A serial to parallel converter comes to rescue inthese situations.

Serial to parallel convertor can also be considered as a serial-inparallel-out shift register. The basic structural component of theshift register is negative edge triggered D flip-flop. For N-bit serialto parallel convertor, N number of D flip-flops will be required.

productivity. Here comes the need of serial to parallel converter. Thetransmitter section consists of a vice-versa parallel to serialconverter and the receiver consists of serial to parallel converter.

Figure 1(a) gives a global view of the system model of our proposed digital domain power division multiplexed dual polarization coherent optical OFDM (PDM-DP-CO-OFDM) transmission system. The digital signal processing (DSP) module at the transmitter side of conventional OFDM modulation includes serial-to-parallel (S/P) conversion, symbol mapping, discrete Fourier transform (DFT) spreading, inverse fast Fourier transform (IFFT), and the parallel-to-serial (P/S) conversion. Two branches of OFDM baseband signal are overlaid together with different power levels before dual polarization modulation process. After transmission along the optical fiber channel, at the receiver side, the synchronization including frame symbol alignment and frequency offset estimation/compensation is conducted first. Then, serial-to-parallel (S/P) conversion is completed before the fast Fourier transform (FFT), after which multiple input multiple output (MIMO) processing is performed to separate signals with different polarization states. Finally, inverse DFT spreading and phase recovery are carried out before de-multiplexing overlaid signals with different power levels.

Orthogonal Frequency Division Multiplexing technology, the evolution and development of multicarrier modulation (MCM) technology, has been widely attracted much attention [7]. The main idea of OFDM is that divided a high-speed serial data stream into multiple independent low-speed parallel data streams, and then respectively modulated onto different carriers to form more of narrow band data streams transmitted in parallel, to improve the capabilities of data stream against multipath time delay spread [8]-[10].

Figure 1 presents the transmitter end and receiver models for optical coherent 64QAM-OFDM transmission system which this paper mainly studied. Firstly, transmitter data stream should pass the serial to parallel (S/P) converter which converts the serial data stream into a parallel data stream, followed by it is modulated. Then, each sub-carrier is transformed into the time domain waveform by an inverse fast Fourier transform (IFFT). The parallel data stream is then moved back to a serial data stream. The end portion of integrating range is copied into front of the symbol as guard interval to eliminate inter-symbol interference (ISI). After digital-to-analogue conversion, the OFDM modulated signal is transmitted in the form of analog signal.

In this MC/DS-CDMA scheme, data after conversion from serial to parallel form are modulatedusing DSSS technique. This is done using spreading code. This time domain spreading process leads tonarrow band sub channels in the frequency domain. These are transmitted in parallel overmultiple different subcarriers. Here there will not be MAI (Multiple Access Intereference) in synchronizeddownlink under slow selective frequency fading environment.

This OFCDM scheme is derived initially from MC-CDMA.It takes advantage of both transmitting low rate subcarriers over broadband channel due to OFDM andspreading the data using coded signals over parallel multiple subcarriers because of CDMA.Hence it is able to make use of both multipath fading as well as frequency diversity effect.

Given that multiple nodes transmit and receive signals simultaneously in an underwater MIMO-OFDM system. Each node is equipped with multiple hydrophones to construct a multiantenna MIMO system, some of which are used to transmit signals, and others receive signals. Firstly, when transmitting, the S/P (serial/parallel) conversion is performed in the input signal. Secondly, the STBC coding is executed. Finally, the OFDM processing is carried out, which mainly includes the operating of an inverse fast Fourier transform (IFFT) and an insertion of the guard interval (GI). When the OFDM processing is completed, each subcarrier that has been inserted into the clock is allocated to a different subchannel, and parallel/serial conversion is performed. At last, a low-pass filtering is executed to convert the digital signal into an analog one and sent it out through the corresponding hydrophone. The transmission process is shown in Figure 1.

After the signal is received, the node performs low-pass filtering, converts the analog signal into a digital one, and carries on serial/parallel conversion. Then, OFDM inverse is carried out, which includes the removing of GI and transforming FFT. Finally, STBC decoding and parallel/serial conversion are performed, and the processed subdata stream is sent to the detector for decoding reception. The receiving process is shown in Figure 2.

hidden morkov model and selected applications in speech recognition in mat lab implementation . in which i didn,t get an idea that can restructure the model by using matlab code.please can you help me to proceed to write a code in mat lab.and can u help me to modification in the existing hidden model in speech recognition so that we will get benefit .

thanks alot for your helpful work please I work in my master in frequency synchronization in mimo ofdm and I have problem in the matlab code try to examine the estimator accuracy in term of its mean and variance and find out if estimation of the CFO on one path is affected by the CFO values of the adjacent paths

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