Maximum likelihood detection of nonlinearly distorted OFDM signal

Nir Regev, Ilia Iofedov, Dov Wulich

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

This paper deals with a Maximum Likelihood receiver for a nonlinearly distorted OFDM signal over a flat channel with AWGN. The nonlinearity destroys the orthogonality between subcarriers, consequently, a per subcarrier decision, used when the linear PA is considered, is no longer optimal. We propose a sub-optimal receiver based on the Maximum Likelihood (ML) criterion. The ML receiver has to find the minimum Euclidean distance between the received vector and a set of all possible OFDM symbols passed through the same nonlinearity. This approach has exponential complexity. To reduce the complexity, we propose a sub-optimal receiver that minimizes the Euclidean distance, seen as a cost function, by the gradient descent algorithm. Unfortunately, due to the nonlinearity, the cost function is non-convex. In order to overcome this obstacle, we propose a method to classify the solution, i.e., to decide if the achieved minimum is local or global. We modify the gradient descent algorithm to avoid convergence to a local minimum. It is shown that the proposed receiver outperforms the simple OFDM and iterative receivers in terms of symbol error rate (SER) performance.

Original languageEnglish
Title of host publication2015 IEEE Global Communications Conference, GLOBECOM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479959525
DOIs
StatePublished - 1 Jan 2015
Event58th IEEE Global Communications Conference, GLOBECOM 2015 - San Diego, United States
Duration: 6 Dec 201510 Dec 2015

Publication series

Name2015 IEEE Global Communications Conference, GLOBECOM 2015

Conference

Conference58th IEEE Global Communications Conference, GLOBECOM 2015
Country/TerritoryUnited States
CitySan Diego
Period6/12/1510/12/15

Keywords

  • Gradient Descent Algorithm
  • Maximum Likelihood
  • Nonlinear Power Amplifier
  • OFDM

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