2014 Poster Sessions : Channel Diversity needed for Vector Interference Alignment

Student Name : Cheuk Ting Li
Advisor : Abbas El Gamal
Research Areas: Information Systems
We consider vector space interference alignment strategies over the K-user interference channel and derive an upper bound on the achievable degrees of freedom as a function of the channel diversity L. The channel diversity L is modeled by L independently fading real-valued parallel channels. Existing results in the literature for K=3 show that the optimal 1/2 degrees of freedom per user can be approached at the speed of 1/L (i.e. the gap to 1/2 degrees of freedom per user decreases inversely proportional to L). In this paper, we show that when K>3, the speed of convergence is significantly slower. In particular, the gap to 1/2 degrees of freedom per user can decrease at most like 1/sqrt(L). Furthermore when K is of the order of sqrt(log(L)), we show that the speed of convergence is smaller than L^(-1/4).

This project was done under the guidance of Prof. Ayfer Ozgur

Cheuk Ting Li is a PhD student in the Department of Electrical Engineering at Stanford University. He received his B.Sc. in Mathematics (first-class honors) and B.Eng. in Information Engineering (first-class honors) from The Chinese University of Hong Kong. He is currently working on information theory under the supervision of Prof. Abbas El Gamal. His research interest includes communication with feedback, network information theory and wireless communication.