In this paper, we combine multi-level coding to the hexagonal modulation to provide a system which is capacity-approaching. This concept may be use the ternary convolutional encoder introduced previously related to the constellation used.

In this paper, we propose time-efficient methods for C2Q data encoding and Q2C data decoding for quantum algorithms. Decoherence optimized circuits for C2Q data encoding are presented along with analysis of their circuit depths.

The proposed multi-level encoding scheme implements a direct value mapping to translate an n -bit digital number to an analog value, and requires calibration and validation stages

The multi-stage decoding algorithm (MSD) is not optimum even though the decoding of each component code is opti-mum. It is suboptimum. The difference in performance between the optimum decod-ing of the overall multi-level modulation code and the sub-optimal MSD is very small, a fraction of dB in coding gain.

Abstract—Photonic processors have enabled applications in machine learning and neuromorphic computing. An information encoding/decoding scheme will be critical for scalable photonic computing. We experimentally demonstrate a “multi-level” en-coding/decoding scheme and operation procedures.

Abstract— This paper deals with -ary transmission using multilevel coding (MLC) and multistage decoding (MSD). The known result that MLC and MSD suffice to approach capacity if the rates at each level are appropriately chosen is reviewed.

Aug 5, 2022 · Here, we propose a multi-level encoding and decoding scheme, and experimentally demonstrate it with a wavelength-multiplexed silicon photonic processor. We also discuss the scalability of our proposed scheme by introducing a photonic general matrix multiply compiler, and consider the effects of speed, bit precision, and noise.

In this paper, we propose time-efficient methods for C2Q data encoding and Q2C data decoding for quantum algorithms. Decoherence optimized circuits for C2Q data encoding are presented along with analysis of their circuit depths.

Photonic processors have enabled applications in machine learning and neuromorphic computing. An information encoding/decoding scheme will be critical for scalable photonic computing. We experimentally demonstrate a "multi-level" encoding/decoding scheme and operation procedures.

These codes provide a flexible trade-off between coding gain, decoding complexity, and decoding delay. New multi-level trellis coded modulation schemes using generalized set partitioning methods are developed for Quadrature Amplitude Modulation (QAM) and Phase Shift Keying (PSK) signal sets.