Nonlinearity estimation for specific emitter identification in multipath channels

Ming Wei Liu, John F. Doherty

Research output: Contribution to journalArticlepeer-review

61 Scopus citations


We present a radio frequency (RF) front-end nonlinearity estimator that is based on the knowledge of a training sequence to perform specific emitter identification (SEI), which discerns radio emitters of interest. Design and fabrication variations provide unique signal signatures for each emitter, and we extract those characteristics through the estimation of transmitter nonlinearity coefficients. The algorithm provides robust identification by first using alternative degrees of nonlinearities associated with symbol amplitudes for initial estimation, and then iteratively estimating the channel coefficients and distorted transmit symbols to overcome the inter-symbol interference (ISI) effect. The convergence and unbiasedness of the iterative estimator are demonstrated semi-analytically. Based on this analysis, we also trade error performance for complexity reduction using the regularity of the estimation process. The algorithm is applicable to a wide range of multi-amplitude modulation schemes, and we present an SEI system designed for an orthogonal-frequency-division multiplexing (OFDM) system over an empirical indoor channel model with associated numerical results.

Original languageEnglish (US)
Article number5740592
Pages (from-to)1076-1085
Number of pages10
JournalIEEE Transactions on Information Forensics and Security
Issue number3 PART 2
StatePublished - Sep 2011

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications


Dive into the research topics of 'Nonlinearity estimation for specific emitter identification in multipath channels'. Together they form a unique fingerprint.

Cite this