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This article presents a novel eight-ary modulation technique with improved signal-to-noise ratio (SNR) compared to conventional pulse amplitude modulation 8 (PAM-8). The proposed SNR-enhanced 8-ary (SNRE-8) scheme modulates pulse width, position, and amplitude to improve the SNR. The proposed SNRE-8 modulation leverages the wireline channel loss to perform the modulation. Digital decoding of mutually exclusive eyes generated by the proposed SNRE-8 modulation further improves the eye margin at the receiver. A 27-Gb/s transceiver is implemented in a 65-nm CMOS process employing the proposed modulation. A PAM-8 transmitter is implemented on the same chip for comparison purposes. Compared to the PAM-8 modulation, the proposed SNRE-8 modulation shows an average SNR improvement of 10.6 dB at the near-end eye at the cost of 6.6% eye width reduction. With the aid of a time-domain feed-forward equalizer (FFE) and a continuous-time linear equalizer (CTLE), the proposed SNRE-8 transceiver achieves a bit error rate (BER) of 10−8 on a 9-dB loss channel with an energy efficiency of 5.39 pJ/bit.
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This content will become publicly available on July 1, 2026
An Efficient Continuous-Variable Quantum Key Distribution with Parameter Optimization Using Elitist Elk Herd Random Immigrants Optimizer and Adaptive Depthwise Separable Convolutional Neural Network
Quantum memory is essential for the prolonged storage and retrieval of quantum information. Nevertheless, no current studies have focused on the creation of effective quantum memory for continuous variables while accounting for the decoherence rate. This work presents an effective continuous-variable quantum key distribution method with parameter optimization utilizing the Elitist Elk Herd Random Immigrants Optimizer (2E-HRIO) technique. At the outset of transmission, the quantum device undergoes initialization and authentication via Compressed Hash-based Message Authentication Code with Encoded Post-Quantum Hash (CHMAC-EPQH). The settings are subsequently optimized from the authenticated device via 2E-HRIO, which mitigates the effects of decoherence by adaptively tuning system parameters. Subsequently, quantum bits are produced from the verified device, and pilot insertion is executed within the quantum bits. The pilot-inserted signal is thereafter subjected to pulse shaping using a Gaussian filter. The pulse-shaped signal undergoes modulation. Authenticated post-modulation, the prediction of link failure is conducted through an authenticated channel using Radial Density-Based Spatial Clustering of Applications with Noise. Subsequently, transmission occurs via a non-failure connection. The receiver performs channel equalization on the received signal with Recursive Regularized Least Mean Squares. Subsequently, a dataset for side-channel attack authentication is gathered and preprocessed, followed by feature extraction and classification using Adaptive Depthwise Separable Convolutional Neural Networks (ADS-CNNs), which enhances security against side-channel attacks. The quantum state is evaluated based on the signal received, and raw data are collected. Thereafter, a connection is established between the transmitter and receiver. Both the transmitter and receiver perform the scanning process. Thereafter, the calculation and correction of the error rate are performed based on the sifting results. Ultimately, privacy amplification and key authentication are performed using the repaired key via B-CHMAC-EPQH. The proposed system demonstrated improved resistance to decoherence and side-channel attacks, while achieving a reconciliation efficiency above 90% and increased key generation rate.
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- Award ID(s):
- 1946442
- PAR ID:
- 10654370
- Publisher / Repository:
- Future Internet, MDPI
- Date Published:
- Journal Name:
- Future Internet
- Volume:
- 17
- Issue:
- 7
- ISSN:
- 1999-5903
- Page Range / eLocation ID:
- 307
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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