題目:Downlink transmission with heterogeneous services
主講人:黃昱智教授 (陽明交通大學電機系)
時間:113年05月03日(星期五13:00- 15:00)
地點:臺北大學三峽校區音律電機資訊大樓電1F02
Abstract: The problem of designing downlink transmission schemes for supporting heterogeneous ultra-reliable low-latency communications (URLLC) and/or with other types of services in future communication systems is investigated. We consider the broadcast channel, where the base station sends superimposed signals to multiple users that may not receive the entire transmitted signal due to the heterogeneous blocklengths. Under heterogeneous blocklength constraints, strong users who are URLLC users cannot wait to receive the entire transmission frame and perform successive interference cancellation (SIC) due to stringent latency requirements, in contrast to the conventional infinite blocklength cases. Even if SIC is feasible, SIC may be imperfect under finite blocklength constraints.
In this talk, I will talk about our recent progress in coping with the heterogeneity in latency and reliability requirements. Specifically, we propose a practical downlink transmission scheme with discrete signaling and single-user decoding (SUD), i.e., without SIC. We carefully design the discrete input distributions to enable efficient SUD by exploiting the structural interference. The proposed approach is then rigorously analyzed to show its second-order achievable rate under heterogenous blocklength and error probability constraints. It is shown that in terms of achievable rate under short blocklength, the proposed scheme with regular quadrature amplitude modulations and SUD can operate extremely close to the benchmark schemes that assume perfect SIC with Gaussian signaling.
Bio: Yu-Chih Huang is a professor at the Institute of Communications Engineering, National Yang Ming Chiao Tung University. Prior to this position, he served as an assistant professor (2015-2018) and as an associate professor (2018-2020) at the Department of Communication Engineering, National Taipei University. He received his Ph. D. degree from Texas A&M University. His research interest lies in information theory, coding theory, statistical communication theory, and statistical machine learning. Currently, he advises five outstanding Ph. D students, all graduated from National Taipei University.