Communication DSP Algorithms, Architectures, and Integrated Circuits

MIMO Preprocessing and Signal Processors

Spatial multiplexing multiple-input and multiple-output is an important technique for improving the transmission capacity of a communication system. The receiver must mitigate the interference between antennas and detect the transmitted symbols by processing MIMO channel matrix and detecting the constellation symbols. Our research designs hardware-oriented MIMO preprocessing and signal processing algorithms and architecture and implements byw FPGA or ASIC chips. 

Research topics: Quantized Precoding for massive MIMO,

Multiple-Input Multiple-Output System   
MIMO Preprocessing and Detection Architecture 
MIMO Mathematical Model

  MIMO Detector Chip

MIMO Beamforming for mmWave Systems:

Millimeter wave (mmWave) system is an emerging transmission technique to improve the reliability and transmitted quality for the future 5G communication systems. MIMO beamforming technique can use the RF phase controller to achieve high-resolution spatial transmission channel to overcome the problems of path-loss and high-correlation of the mmWave channel. Our research focuses on hybrid RF/baseband beamforming for the mmWave MIMO systems. The DSP algorithms/processors are designed to build up the optimal RF beam-forming phase array vector and baseband MIMO precoding matrix. This approach can reduce the RF chain number and the power consumption of the analog front-end for massive MIMO systems.

Research Topics: Wideband mmWave Hybrid Beamforming, 5G Baseband Processor VLSI

Hybrid Beamforming  

 Beamforming Simulation
Hybrid Beamforming Processing Architecture 

Beamforming Processor Chip