A CMOS radio-frequency front-end for multi-standard wireless communications

The explosive growth of wireless communication market has led the development of low-cost, highly-integrated wireless communication systems. Even though most blocks in the front-end have successfully been integrated by using the CMOS technology, it is still a formidable challenge to integrate the entire front-end. Thus, the objective of this research is to demonstrate the feasibility of the integrated front-end by using improved circuit techniques as well as the improved process technologies. This dissertation proposes an improved control scheme to enhance the high-power handling capability of an antenna switch. As a part of this research, an antenna switch controller for a GaAs antenna switch was first developed to enhance the performances of the GaAs antenna switch by using the boosted control voltage. To enhance the efficiency of the front-end, efficiency improvement techniques for the antenna switch controller has also been studied. With the suggested efficiency improvement techniques, a fully-integrated antenna switch was implemented using the SOI technology, and exceeding performances over many commercial products for watt-level high-power applications have been successfully demonstrated. As an effort to improve the efficiency of a power amplifier, a linear envelope detector was also implemented, and the results show that the envelope detector is suitable for dynamic biasing of the power amplifier. The research presented in this dissertation, thus, provides a low-cost and high-performance solution for highly-integrated RF front-end used in various wireless communication systems.Ph.D.Committee Chair: Tentzeris, Emmanouil; Committee Member: Kang, Sung Ha; Committee Member: Kim, Jongman; Committee Member: Lee, Chang-Ho; Committee Member: Shen, Shyh-Chian

Syllable pattern-based unknown morpheme estimation for hybrid part-of-speech tagging of Korean

This paper presents a syllable pattern directed generalized unknown morpheme handling method with POSTAG (POStech TAGger)

Generalized unknown morpheme guessing for hybrid POS tagging of Korean

Most of errors in Korean morphological analysis and POS (Part-of-Speech) tagging are caused by unknown morphemes. This paper presents a generalized unknown morpheme handling method with POSTAG (POStech TAGger) which is a statistical/rule based hybrid POS tagging system. The generalized unknown morpheme guessing is based on a combination of a morpheme pattern dictionary which encodes general lexical patterns of Korean morphemes with a posteriori syllable tri-gram estimation. The syllable tri-grams help to calculate lexical probabilities of the unknown morphemes and are utilized to search the best tagging result. In our scheme, we can guess the POS's of unknown morphemes regardless of their numbers and positions in an eojeol, which was not possible before in Korean tagging systems. In a series of experiments using three different domain corpora, we can achieve 97% tagging accuracy regardless of many unknown morphemes in test corpora

Hybrid POS tagging with generalized unknown-word handling

This paper presents POSTAG 1 as a statistical/rulebased hybrid part-of-speech (POS) tagging system with generalized unknown-word handling. The POSTAG integrates morphological analysis with statistical POS disambiguation and post rule-based error-correction. The error-correction rules are automatically learned from a tagged corpus and selectively correct standard HMM tagging errors. The morphological analysis is tightly coupled with the generalized unknown-word handling which uses a morpheme-pattern dictionary that encodes general lexical patterns of Korean morphemes. In this way, we can guess the POS's of unknown-words regardless of their numbers and positions in an eojeol. Experiments demonstrate the effectiveness of our POS tagging methods with generalized unknown-word handling, and the POSTAG will be especially suited to web indexing where most of the indexing terms are unknown words. Keywords: POS tagging, morphological analysis, unknown-word handling, HMM tagging, rule-based ta..

Syllable-Pattern-Based Unknown- Morpheme Segmentation and Estimation for Hybrid Part-of-Speech Tagging of Korean

Most errors in Korean morphological analysis and part-of-speech (POS) tagging are caused by unknown morphemes. This paper presents a syllable-pattern-based generalized unknownmorpheme-estimation method with POSTAG (POStech TAGger), 1 which is a statistical and rule-based hybrid POS tagging system. This method of guessing unknown morphemes is based on a combination of a morpheme pattern dictionary that encodes general lexical patterns of Korean morphemes with a posteriori syllable trigram estimation. The syllable trigrams help to calculate lexical probabilities of the unknown morphemes and are utilized to search for the best tagging result. This method can guess the POS tags of unknown morphemes regardless of their numbers and/or positions in an eojeol (a Korean spacing unit similar to an English word), which is not possible with other systems for tagging Korean. In a series of experiments using three different domain corpora, the system achieved a 97 % tagging accuracy even though 10 % of the morphemes in the test corpora were unknown. It also achieved very high coverage and accuracy of estimation for all classes of unknown morphemes. 1