Speaker: Yiming Kong, Ph.D. Student, Georgia Institute of Technology
Title: Lattice Reduction Aided Precoding and Detection Designs for Multiuser Large MIMO Systems
Multi-input multi-output (MIMO) technology has been intensively studied and incorporated into latest wireless communication standards since it can greatly improve the capacity and reliability of wireless systems. For example, the LTE standard supports up to 8 base station (BS) transmit antennas and up to 8 receive antennas in the user equipment (UE). To further reap the benefits of MIMO, massive MIMO has been proposed by equipping each BS with hundreds of antennas or more. One key issue in such large-dimension MIMO system is the design of efficient precoding/detection algorithms, especially when the total number of serving UE antennas is close to that at the base station, in which case linear schemes fall short in performance due to high orthogonality deficiency of the MIMO channel. Recently, lattice reduction (LR)-aided detections have been proposed in MIMO systems to achieve near-optimum bit-error-rate (BER) performance with average-case polynomial complexity. In this talk, we will dive deep into the analysis and applications of LR algorithms in multiuser large MIMO systems. Specifically, we propose a LR-aided precoding scheme and a LR-aided detection scheme. Compared to other state-of-the-art schemes, LR-aided designs achieve superior BER while maintaining low complexity.
Yiming Kong is a Ph.D. student working with Professor Xiaoli Ma with a research focus on the design and application of low-complexity high-performance detectors for large MIMO systems. Her other research interests include applying machine learning algorithms in telecommunication systems/networks, and mining telecom data. She was a research intern with FutureWei Technologies during 2016 and summer 2017. Before coming to Georgia Tech, she obtained her bachelor of engineering at Zhejiang University, Hangzhou, China.