Abstract

CORDIC algorithm has been widely used for efficient implementation of vector rotation operations in hardware.However,it's hard to achieve small iteration numbers while not compromising the ease of scale factor computing and compensation.This paper proposes a novel table-driven CORDIC rotation algorithm with predictable scale factors and short pipelines.It maps the input angle during into and generates signals to modify the initial iteration value and control the rotation direction.The rotation process is composed of two steps.The coefficients and scale factors of step1 are acquired through lookup table indexed by the MSB(Most Significant Bits) of the mapped angle.After large-angle rotations of step1,the residual angle is brought into the convergence region of step2.The iteration of step2 is scaling-free,with the coefficients directly gotten from the binary representation of the residual angle.During such two processes,no further arithmetic computation in the angle approximation(z datapath) and scale factor computing datapath is required.The coefficients of step1 are generated by our angle decomposition algorithm,with two coefficients in one group,at most one non-zero value each group,and the scale factors are pre-computed and coded with radix-4 Booth recoding algorithm.In addition,some adjacent simple micro rotations are combined into one.All these techniques effectively reduce the iteration number,which is also beneficial to high accuracy due to less rounding errors.Moreover,the algorithm uses carry-save adders to accumulate three operands and omits expressions of machine zero,which reduces the latency and complexity of the system greatly.The MSB indexed lookup table gets over the poor scalability of full-word indexed lookup table,and entries grow slowly with accuracy.When using 28-bit datapath,the algorithm requires 38% less pipeline stages and 27.9% less area consumption compared to those of the conventional CORDIC,while achieving 3 more bits accuracy,which shows great performance superiority.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.