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An Efficient Bayesian PAPR Reduction Method for OFDM-Based Massive MIMO Systems

An Efficient Bayesian PAPR Reduction Method for OFDM-Based Massive MIMO Systems

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 An Efficient Bayesian PAPR Reduction Method for OFDM-Based Massive MIMO Systems

 We consider the problem of peak-to-average power ratio (PAPR) reduction in orthogonal frequency-division multiplexing (OFDM) based massive multiple-input multiple-output (MIMO) downlink systems. Specifically, given a set of symbol vectors to be transmitted to K users, the problem is to find an OFDM-modulated signal that has a low PAPR and meanwhile enables multiuser interference (MUI) cancelation. Unlike previous works that tackled the problem using convex optimization, we take a Bayesian approach and develop an efficient PAPR reduction method by exploiting the redundant degrees of freedom of the transmit array.


 


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  • Model: PROJ7175
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Monday 12 June, 2017.

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