Investigation of QAM based on mean square error (MSE) channel estimation (CE) for MIMO-OFDM pilot based system / Mohd Ariff Ibrahim
Channel Estimation (CE) is functioning as a medium to reduce the diversity and error in MIMO-OFDM system which containing few other techniques which are Least Square Error (LSE), Mean Square Error (MSE) and Discrete Fourier Transform (DFT). The diversity in MIMO-OFDM is based on the lowest Bit Error...
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| Format: | Thesis |
| Language: | English |
| Published: |
2013
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| Online Access: | https://ir.uitm.edu.my/id/eprint/79637/1/79637.pdf |
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| Summary: | Channel Estimation (CE) is functioning as a medium to reduce the diversity and error in MIMO-OFDM system which containing few other techniques which are Least Square Error (LSE), Mean Square Error (MSE) and Discrete Fourier Transform (DFT). The diversity in MIMO-OFDM is based on the lowest Bit Error Rate (BER) of each result by the estimation of Quadrature Amplitude Modulation (QAM) scheme size. Fast Fourier Transform (FFT) and Inverse Fast Fourier Transform (IFFT) are the main optimizer as it convert input signal or output signal from frequency domain to time domain or vice versa either on serial or parallel block. The Multiple Input Multiple Output (MIMO) is perform in the transceiver technology so that it can improve the performance of the radar, satellite or any other devices that uses signal frequency as the input. The Orthogonal Frequency Division Multiplexing (OFDM) is the technique that use for many companies, distributers, researchers, industries and many other signal processing usage for many years. There is Channel Estimation (CE) which consists of different statement to obtain high gain and a better performance of Bit Error Rate (BER). This is why the study of Mean Square Error (MSE) is made so that the technique can reduce the error and perform a better Bit Error Rate (BER). The Least Square Error (LSE) and Discrete Fourier Transform (DFT) BER are not shown because these are other CE techniques and Mean Square Error (MSE) is used just by applying the algorithm from Least Square Error (LSE) and converted into MSE with combination of few complex matrix correlations. |
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