Optimal Envelope Approximation in Fourier Basis with Applications in TV White Space

TL;DR

This paper presents a near-optimal algorithm for lowpass envelope approximation of smooth signals in the Fourier basis, crucial for applications like TV white space protection, using convex optimization techniques.

Contribution

It introduces a novel linear Fourier series-based method for envelope approximation that minimizes mean-squared error and is computationally efficient.

Findings

The algorithm is near-optimal in envelope approximation.

Convex optimization techniques effectively solve the approximation problem.

Simulation results validate the analytical approach.

Abstract

Lowpass envelope approximation of smooth continuous-variable signals are introduced in this work. Envelope approximations are necessary when a given signal has to be approximated always to a larger value (such as in TV white space protection regions). In this work, a near-optimal approximate algorithm for finding a signal's envelope, while minimizing a mean-squared cost function, is detailed. The sparse (lowpass) signal approximation is obtained in the linear Fourier series basis. This approximate algorithm works by discretizing the envelope property from an infinite number of points to a large (but finite) number of points. It is shown that this approximate algorithm is near-optimal and can be solved by using efficient convex optimization programs available in the literature. Simulation results are provided towards the end to gain more insights into the analytical results presented.