Exploiting special-purpose function approximation for hardware-efficient QR-decomposition

Efficient signal processing takes a key role in application-specific circuit design. For instance, future mobile communication standards, e.g., high-performance industrial mobile communication, require high data rates, low latency and/or high energy-efficiency. Hence, sophisticated algorithms and computing schemes must be explored to satisfy these challenging constraints. In this paper we leverage the paradigm of approximate computing to enable hardware-efficient QR-decomposition for channel pre-coding. For an efficient computation of the Givens-Rotation, bivariate, non-linear numeric functions are taken into account. An effective design method is introduced leading to highly adapted (special-purpose) functions. For evaluation, our work is tested with different configurations in a Tomlinson-Harashima pre-coding downlink environment. In addition, a corresponding HDL implementation is set up and logic and physical CMOS synthesis is performed. The comparison to actual references prove our work to be a powerful approach for future mobile communication systems.