Approximate computing (AC) is an emerging embedded computing paradigm whereby accurate arithmetic units (i.e., adders and multipliers) of a computing platform (e.g., CPU, FPGA, ASIC etc.) are replaced by their inexact counterparts. For the applications (e.g., voice, images etc.) where the error induced by inaccurate arithmetic units remains within tolerable limits, AC is a promising technique because it leads to the design of energy-efficient computing hardware that occupies less circuit area, and has lower latency as well. This work is the first to investigate the feasibility of the AC for single-antenna and dual-antenna 6G downlink. Specifically, we consider the AC-empowered transceiver design of a 6G downlink whereby the state-of-the-art approximate/inexact arithmetic units are leverage to implement the pulse shaping filters (at the base station (BS) side) and decoders/equalizers (at the user equipment (UE) side). For simulation purpose, images and randomly generated bits are transmitted using M-ary phase shift keying scheme. To quantify the loss in arithmetic accuracy due to the AC, bit error rate (BER), structural similarity index (SSIM) and correlation coefficient (CC) are utilized as performance metrics; while to quantify the energy-efficiency benefit of the proposed AC techniques, dynamic power and on-chip power are utilized as performance metrics. Monte-Carlo results indicate up to 87% savings in dynamic power and very reasonable arithmetic accuracy (with SSIM above 93% and a CC of 99%), due to the proposed AC techniques.
- Approximate computing
- Communication software/hardware
- Digital filters
- Low power
ASJC Scopus subject areas
- Electrical and Electronic Engineering