Identifier

etd-11182013-115645

Degree

Master of Science in Electrical Engineering (MSEE)

Department

Electrical and Computer Engineering

Document Type

Thesis

Abstract

Nowadays, adaptive modulation and coding (AMC) techniques can facilitate flexible strategies subject to dynamic channel quality. The AMC transceivers select the most suitable coding and modulation mechanisms subject to the acquired channel information. Meanwhile, a control channel or a preamble is usually required to synchronously coordinate such changes between transmitters and receivers. On the other hand, low-density parity-check (LDPC) codes become more and more popular in recent years due to their promising capacity-approaching property. The broad range of variations in code rates and codeword lengths for LDPC codes makes them ideal candidates for future AMC transceivers. The blind encoder identification problem emerges when the underlying control channel is absent or the preamble is not allowed in AMC systems. It would be quite intriguing for one to build a blind encoder identification technique without spectrum-efficiency sacrifice. Therefore, in this thesis, we investigate blind LDPC encoder identification for AMC systems. Specifically, we would like to tackle the blind identification of binary LDPC codes (encoders) for binary phase-shift keying (BPSK) signals and nonbinary LDPC codes for quadrature-amplitude modulation (QAM) signals. We propose a novel blind identification system which consists of three major components, namely expectation-maximization (EM) estimator for unknown parameters (signal amplitude, noise variance, and phase offset), log-likelihood ratio (LLR) estimator for syndrome a posteriori probabilities, and maximum average-LLR detector. Monte Carlo simulation results demonstrate that our proposed blind LDPC encoder identification scheme is very promising over different signal-to-noise ratio conditions.

Date

2013

Document Availability at the Time of Submission

Release the entire work immediately for access worldwide.

Committee Chair

Wu, Hsiao-Chun

DOI

10.31390/gradschool_theses.3323

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