Photonic computing to accelerate data processing in wireless communications

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).

Integrated Microwave Photonics Coherent Processor for Massive-MIMO Systems in Wireless Communications

“…In a previous work, Salmani, M. et al [21] presented an optical processor for massive-MIMO systems that is based on B&W. This type of systems rely on the use of MRRs and wavelength division multiplexing (WDM). It presents some advantages over our presented architecture, specially in terms of footprint, but on the other hand, are inherently unable to implement complex matrix multiplications introducing extra pre-and post-processing steps.…”

“…Interference cancellation, where the signal of interest is separated from added noise have been experimentally demonstrated using tunable delays [14], [15], semiconductor optical amplifiers [16], [17], dispersive elements [18], microring resonators (MRRs) [19] or the nonlinear response of optical modulators [20]. Furthermore, a more general scheme based on the broadcast-and-weight (B&W) protocol using MRRs to perform the matrix multiplications in optical domain have been theoretically studied and great improvements in terms of bandwidth and energy consumption over DSP systems have been calculated [21].…”

Integrated photonic-electronic platform for real-time analog data processing in LiDARs

“…We develop an optical fully-connected layer following the generic photonics-based matrix-to-matrix multiplication architecture, which is using B&W protocol, that has been proposed in Ref. 15. Accordingly, our proposed optical fully-connected layer includes k i+1 parallel wavelength channels with k i all-pass MRRs to implement each row of the input matrix, and k i add-drop MRRs to implement the corresponding column of the weight matrix.…”

“…Furthermore, based on the computational requirements of the task to be executed, the power consumption of the photonic computing system can be 1/3 of that of the best digital electronic processors in the literature; see Ref. 15.…”

“…The details of computing the runtime, and hence the time efficiency of the ANN computation architecture is explained in our previous work, i.e., Ref. 15. In this work, we provide the * We acknowledge that realizing 100 MRRs in each part of the system can be challenging.…”