PAPR Reduction & Channel Estimation Techniques For MIMO-OFDMA Systems
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In the last couple of years, wireless communications have experienced a quick growth due to the ubiquitous mobility, super internet speed and huge multimedia services and applications. OFDM signals have a generic problem of high peak to average power ratio (PAPR). The drawback of high PAPR is that the dynamic range of the power amplifier (PA) and digital-to-analog converter (DAC) during the transmission and reception of the signal is higher. The focus of this book is to design and implement PAPR reduction techniques based on amplitude clipping and filtering method which reduces the PAPR signif...
In the last couple of years, wireless communications have experienced a quick growth due to the ubiquitous mobility, super internet speed and huge multimedia services and applications. OFDM signals have a generic problem of high peak to average power ratio (PAPR). The drawback of high PAPR is that the dynamic range of the power amplifier (PA) and digital-to-analog converter (DAC) during the transmission and reception of the signal is higher. The focus of this book is to design and implement PAPR reduction techniques based on amplitude clipping and filtering method which reduces the PAPR significantly in OFDMA signal. However, for OFDM systems with multiple transmit antennas, different signals are transmitted from different antennas simultaneously, so that the received signal is the superposition of transmitting signals, which gives a challenging task for channel estimation (CE) at the receiver. This book represents the variable step size-least mean square (VSS-LMS) CE algorithm for MIMO OFDMA systems.
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