VLSI Architecture for Matrix Inversion using Modified Gram-Schmidt based QR Decomposition

Chitranjan Singh, Sushma Prasad, Poras Balsara
2007 20th International Conference on VLSI Design held jointly with 6th International Conference on Embedded Systems (VLSID'07)  
Matrix inversion and triangularization problems are common to a wide variety of communication systems, signal processing applications and solution of a set of linear equations. Matrix inversion is a computationally intensive process and its hardware implementation based on fixed-point (FP) arithmetic is a challenging problem. This paper proposes a fully parallel VLSI architecture under fixed-precision for the inverse computation of a real square matrix using QR decomposition with Modified
more » ... chmidt (MGS) orthogonalization. The MGS algorithm is stable and accurate to the integral multiples of machine precision under fixed-precision for a well-conditioned non-singular matrix. For typical matrices (¢ ¤ £ ¥ ¢ ) found in MIMO communication systems, the proposed architecture was able to achieve a clock rate of 277 MHz with a latency of 18 time units and area of 72K gates using 0.18-¦ § CMOS technology. For a generic square matrix of order © , the latency required is © which is better than all previously known architectures. With the use of LUTs and log-domain computations, the total area has been reduced compared to architectures based on linear-domain computations.
doi:10.1109/vlsid.2007.177 dblp:conf/vlsid/SinghPB07 fatcat:r5m3jh4swvawpfg36dpb643wmi