【電機系書報討論演講訊息】

書報討論網址：http://www.ee.nthu.edu.tw/~ee591000/

演講公告網址：/p/403-1175-2629-1.php

題   目：Low-Complexity Soft-Output Sphere Decoding with Modified Repeated Tree Search Strategy

講   員：謝欣霖 教授(台北大學通訊工程研究所)

時       間：2012年11月30日(星期五) 下午2時20分 (2時10分入場)

地       點：資電館206教室
 

Bio:
    Shin-Lin Shieh Graduate Institute of Communication Engineering National Taipei University Shin-Lin Shieh received the B.Sc. and M.Sc. degrees in electrical engineering from the National Tsing-Hua University, Hsinchu, Taiwan, in 1999 and 2001, respectively, and a Ph.D. degree in the department of communications engineering from National Chiao-Tung university, Hsinchu, Taiwan. After serving in the military for three months, he joined the Wireless Communication Technology Department, Computer and Communication Laboratory (CCL), Industrial Technology Research Institute (ITRI), Taiwan, in 2002, where he was engaged in several projects on the development of baseband communication algorithms. In 2005, he switched to the Wideband Code Division Multiple Access (WCDMA) Project, Sunplus Technology Company, Ltd. He continued to work with the HT mMobile, Inc., Hsinchu, a subsidiary spun-off from the Sunplus Technology Company, Ltd. in 2008, and was involved in designing baseband algorithms of enhanced data rates for global system for mobile communications evolution (EDGE), WCDMA, high-speed downlink packet access (HSDPA), long-term evolution (LTE) and other communication systems. Started from August 2010, he joined the Graduate Institute of Communication Engineering at National Taipei university, Taipei, Taiwan, as an assistant professor.

Talk abstract:
    Many solutions for detecting signals transmitted over flat-faded multiple input multiple output (MIMO) channels have been proposed, e.g., the zero-forcing (ZF), minimum mean squared error (MMSE), sphere decoding (SD) algorithms, to name a few. These approaches however suffer from either unsatisfactory performance or high complexity. In this talk, we focus on the soft-output SD algorithm and propose a modification on the repeated tree search (RTS) strategy. It is shown that our modification can maintain a fixed upper limit in decoding complexity and results in a good performance-complexity tradeoff.

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