Optimised floating point arithmetic-based QR decomposition for wireless communication systems Online publication date: Wed, 24-Nov-2021
by Alahari Radhika; Satya Prasad Kodati; Kishan Rao Kalitkar
International Journal of Ultra Wideband Communications and Systems (IJUWBCS), Vol. 4, No. 3/4, 2021
Abstract: In wireless communication systems, matrix inversion is the most common operation to provide a solution to the system of linear equations. Also, OMP compressive sensing is widely preferred for signal reconstruction at the receiver side. In both these processes, the accuracy and achievable performance rate of fixed-point arithmetic restrict its applicability in many real-time applications. In this paper, floating-point enabled systolic array implementation of iterative QR decomposition (QRD) based on the modified Gram-Schmidt (MGS) algorithm is proposed for matrix inversion. Here, the computational efficiency is improved using floating-point optimisation techniques and parallel systolic implementation which results in robust numerical stability. By exploiting the potential metrics of the systolic array, the proposed QRD architecture offered maximum throughput rate and inherent errorless FPU computation which help in improving the accuracy in matrix inversion.
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