Linear Precoder Design for PAPR Reduction of GFDM Signals Using Gradient Descent Methods
semanticscholar(2021)
摘要
This paper addresses linear precoder design for Peak-to-Average Power Ratio (PARP) reduction of Generalized Frequency Division Multiplexing (GFDM). A general framework, which is composed of four different scenarios and utilizes Gradient-based iterative methods to reduce PAPR through minimizing statistical parameters of the instantaneous power of GFDM signal including variance, power, and third moment, is suggested. Numerical results confirm when the step-size of the Gradient method is dynamically computed using the Wolf line search rule, the suggested algorithm circumvents drawbacks of existing studies and converges to a precoder providing advantages in design speed, obtained PAPR, symbol error rate, and out-of-band emission.
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