Design and Chip Implementation of A SMI/MVDR Dual-mode Beamformer for Wireless MIMO Communication Systems

Kuan-Ting Chen, Yin-Tsung Hwang, Cheng-Yi Huang
2020 IEEE Access  
This paper presents a low complexity chip design supporting dual-mode beamforming, i.e. sampling matrix inversion (SMI) and the minimum variance distortionless response (MVDR), for wireless Multiple-Input Multiple-Output (MIMO) communication systems. The auto-correlation matrix inversion is the critical computing kernel shared by the two beamforming schemes. To alleviate the computing complexity, the auto-correlation matrix is approximated by a Toeplitz counterpart, which can be decomposed
more » ... iently by applying the Cholesky decomposition and the Schur algorithm. This leads to an O N 3 to O N 2 complexity reduction, where N is the matrix size, while preserving computing parallelism for the hardware design. In addition, a diagonal loading technique is employed to mitigate the stability problem when the matrix is ill-conditioned. Simulation results indicate that no performance loss is observed due to the algorithm simplification measures. A systolic array based mapping procedure converts the two beamforming algorithms to a unified hardware accelerator design with 80% shared circuitry. Complex-valued divisions are achieved by adopting a hardware efficient coordinate rotation digital computer (CORDIC) scheme. In chip implementation, a TSMC 90nm UTM process technology is used and the design specs largely follow the requirements of IEEE 802.11ac standard. The core size of the chip design is 0.68mm 2 . The measurement results show that the chip can operate up to 200MHz with a power consumption of 49.03mW. It can complete the computation of a new beamforming vector (of size 8) every 0.64us and exhibits the highest throughput among the 6 compared designs. INDEX TERMS Adaptive beamforming, Cholesky decomposition, Schur algorithm, systolic array, hardware accelerator, chip design. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 8, 2020 KUAN-TING CHEN received the B.S. and M.S. degrees from the
doi:10.1109/access.2020.2986028 fatcat:ezanpqetfjbs5jrdm3ylytjgqe