Abstract

This work presents a wide class of digital signal-processing schemes for orthogonal frequency-division multiplexing (OFDM) transmission which combine a nonlinear operation in the time domain and a linear filtering operation in the frequency domain. The ultimate goal of these schemes is to reduce the envelope fluctuation of ordinary OFDM, while keeping its high spectral efficiency and allowing a low-cost, power-efficient implementation. An appropriate statistical model concerning the transmitted frequency-domain blocks is developed, which is derived from well-established results on Gaussian stochastic processes distorted by memoryless nonlinearities. This model can be employed for performance evaluation by analytical means, with highly accurate results whenever the corresponding conventional OFDM signals exhibit quasi-Gaussian characteristics. Cases where the signal-processing scheme is repeatedly used, in an iterative way, are treated through an extension of the proposed statistical modeling. A set of numerical results is presented and discussed so as to show the practical interest of both the proposed schemes and the analytical methods for evaluation of their performance. For the sake of comparisons, this paper includes numerical results concerning the partial transmit sequence technique, which is an alternative peak-to-mean envelope power ratio-reducing technique of higher complexity, often recommended due to its distortionless nature. The superior performance/complexity tradeoffs through the proposed class of nonlinear signal-processing schemes is emphasized.

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