Published February 1, 2022 | Version v1
Journal article Open

A review of optimisation and least-square problem methods on field programmable gate array-based orthogonal matching pursuit implementations

  • 1. Reconfigurable Computing for Analytics Acceleration (ReCAA) Research Laboratory, Microelectronics and Nanotechnology Shamsuddin Research Centre (MiNTSRC), Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia

Description

Orthogonal matching pursuit (OMP) is the most efficient algorithm used for the reconstruction of compressively sampled data signals in the implementation of compressive sensing. OMP operates in an iteration-based nature, which involves optimisation and least-square problem (LSP) as the main processes. However, optimisation and LSP processes comprise complex mathematical operations that are computationally demanding, and software-based implementations are slow, power-consuming, and unfit for real-time applications. To fill the research gap, we reviewed the optimisation and LSP techniques implemented on the FPGA platform as the hardware accelerator. Aspects that contributed to the performance, algorithm, and methods involved in the implemented works were discussed and compared. The methods were found to be improved when modified or combined. However, the best approach still depends on the requirement of the system to be developed, and this review is significant as a reference.

Files

33 26927 v25i2 Feb22.pdf

Files (927.1 kB)

Name Size Download all
md5:21a8a0d2d77ce437f13b1280b5a02355
927.1 kB Preview Download