Abstract: Backscatter communication (BC) is a promising method of providing low-power interconnection for green or Internet of Things applications. To combat the strong interference from the direct link, it often uses a small constellation size for modulation, leading to a low data rate. In this talk, backscatter index modulation (BIM) is proposed to increase the data rate of BC by employing multiple single-antenna tags and activating one tag a time to carry extra data bits for information delivery. Both coherent detection with full channel knowledge and non-coherent detection with partial channel knowledge are studied. In each case, ambient backscatter communication with either Gaussian distributed or constant modulus source signals, as well as dedicated backscatter communication with known source signals, are considered. The optimal detectors are derived using the maximum likelihood principle, and their symbol error rate (SER) performances are analyzed in closed-form expressions. Numerical results are presented to examine the effects of different system parameters on the SER. In particular, BIM performs well in coherent detection with full channel knowledge but could quickly reach error floors in non-coherent detection with partial channel knowledge. Also, the number of tags is more important than the number of samples in some cases. The channel asymmetry in the tag-to-reader links can also play an important role in the SER performance.
时间：2025.07.17 10:35-11:20
地点：紫金山实验室新大楼2楼报告厅3
Yunfei Chen (S'02-M'06-SM'10) received his B.E. and M.E. degrees in electronics engineering from Shanghai Jiaotong University, Shanghai, P.R.China, in 1998 and 2001, respectively. He received his Ph.D. degree from the University of Alberta in 2006. He is currently working as a Professor in the Department of Engineering at Durham University, U.K. His research interests include wireless communications, performance analysis, joint radar communications designs, cognitive radios, wireless relaying and energy harvesting.
