Photonic Computing to Accelerate Data Processing in Wireless Communications

TL;DR

This paper introduces a photonic computing approach for massive-MIMO systems in wireless communications, significantly improving processing speed and energy efficiency over traditional digital electronics.

Contribution

It develops a novel photonic MAC architecture with preprocessing to handle complex values, enabling faster and more energy-efficient data processing in 5G wireless systems.

Findings

Photonic computing achieves higher speed than GPUs.

The approach maintains system performance without degradation.

Significant energy savings demonstrated.

Abstract

Massive multiple-input multiple-output (MIMO) systems are considered as one of the leading technologies employed in the next generations of wireless communication networks (5G), which promise to provide higher spectral efficiency, lower latency, and more reliability. Due to the massive number of devices served by the base stations (BS) equipped with large antenna arrays, massive-MIMO systems need to perform high-dimensional signal processing in a considerably short amount of time. The computational complexity of such data processing, while satisfying the energy and latency requirements, is beyond the capabilities of the conventional widely-used digital electronics-based computing, i.e., Field-Programmable Gate Arrays (FPGAs) and Application-Specific Integrated Circuits (ASICs). In this paper, the speed and lossless propagation of light is exploited to introduce a photonic computing approach that addresses the high computational complexity required by massive-MIMO systems. The proposed computing approach is based on photonic implementation of multiply and accumulate (MAC) operation achieved by broadcast-and-weight (B&W) architecture. The B&W protocol is limited to real and positive values to perform MAC operations. In this work, preprocessing steps are developed to enable the proposed photonic computing architecture to accept any arbitrary values as the input. This is a requirement for wireless communication systems that typically deal with complex values. Numerical analysis shows that the performance of the wireless communication system is not degraded by the proposed photonic computing architecture, while it provides significant improvements in time and energy efficiency for massive-MIMO systems as compared to the most powerful Graphics Processing Units (GPUs).