Proposal for Slepian-States-Based DV- and CV-QKD Schemes Suitable for Implementation in Integrated Photonics Platforms

Quantum key distribution (QKD) leverages underlying principles of quantum mechanics to realize distribution of keys with verifiable security. Despite appealing features of QKD, there are some fundamental and technical challenges that need to be solved prior to its widespread applications. First, QKD secret-key rate (SKR) is fundamentally limited by channel loss, as dictated by the rate-loss tradeoff. Quantum repeaters would be an ultimate solution to overcome this problem; however, they are well beyond the reach. The second challenge lies in the scalability and cost. Future's QKD systems must be suitable for mass production with low cost, reliable realignment-free operations, and small power consumption. To solve for these problems in a simultaneous manner, we propose to encode information in the orthogonal Slepian sequences' bases. Such an approach is highly robust against turbulence effects in free-space optical links and dispersion effects/fiber non-linearities in fiber-optics channels, thereby improving QKD distance. Moreover, exploiting multidimensional encoding space enables high spectral efficiency QKD so that the SKR can be significantly improved. Critically, generation, processing, and detection of Slepian states can be reliably implemented in an integrated quantum photonics platform, based on both reflective and transmissive waveguide Bragg gratings (WBGs). Proposed reflective/transmissive WBG-based Slepian states are applicable to both discrete variable and continuous variable QKD systems.Multidisciplinary University Research Initiatives Office of Naval Research [N00014-13-1-0627]; National Science FoundationOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Throughput Maximization by Adaptive Switching with Modulation Coding Scheme and Frequency Symbol Spreading

It is required to realize higher transmission rate and higher reliability for mobile communication due to the increase in Internet use. However, wireless channel capacity can not be used with maximum efficiency due to fluctuating channels affected by shadowing, multipath fading and mobility.Adaptive modulation and coding (AMC) scheme is now commonly implemented to maximize the throughput performance under the given link qualities. Forward Error Correction (FEC) based link adaptation is effective to improve throughput in a lower SNR regime, however, it immolates maximal throughput in good channel condition. Frequency symbol spreading (FSS) has been proposed that can improve BER even without FEC. It fully exploits the frequency diversity gain by spreading symbol per subcarrier to all frequency components. This paper proposes a new adaptation control scheme for OFDM by switching FSS and legacy AMC. Simulation result verifies its maximized throughput performance harvesting both of frequency diversity gain and coding gain

Throughput Maximization by Adaptive Switching with Modulation Coding Scheme and Frequency Symbol Spreading

It is required to realize higher transmission rate and higher reliability for mobile communication due to the increase in Internet use. However, wireless channel capacity can not be used with maximum efficiency due to fluctuating channels affected by shadowing, multipath fading and mobility.Adaptive modulation and coding (AMC) scheme is now commonly implemented to maximize the throughput performance under the given link qualities. Forward Error Correction (FEC) based link adaptation is effective to improve throughput in a lower SNR regime, however, it immolates maximal throughput in good channel condition. Frequency symbol spreading (FSS) has been proposed that can improve BER even without FEC. It fully exploits the frequency diversity gain by spreading symbol per subcarrier to all frequency components. This paper proposes a new adaptation control scheme for OFDM by switching FSS and legacy AMC. Simulation result verifies its maximized throughput performance harvesting both of frequency diversity gain and coding gain

A survey on fiber nonlinearity compensation for 400 Gbps and beyond optical communication systems

Optical communication systems represent the backbone of modern communication networks. Since their deployment, different fiber technologies have been used to deal with optical fiber impairments such as dispersion-shifted fibers and dispersion-compensation fibers. In recent years, thanks to the introduction of coherent detection based systems, fiber impairments can be mitigated using digital signal processing (DSP) algorithms. Coherent systems are used in the current 100 Gbps wavelength-division multiplexing (WDM) standard technology. They allow the increase of spectral efficiency by using multi-level modulation formats, and are combined with DSP techniques to combat the linear fiber distortions. In addition to linear impairments, the next generation 400 Gbps/1 Tbps WDM systems are also more affected by the fiber nonlinearity due to the Kerr effect. At high input power, the fiber nonlinear effects become more important and their compensation is required to improve the transmission performance. Several approaches have been proposed to deal with the fiber nonlinearity. In this paper, after a brief description of the Kerr-induced nonlinear effects, a survey on the fiber nonlinearity compensation (NLC) techniques is provided. We focus on the well-known NLC techniques and discuss their performance, as well as their implementation and complexity. An extension of the inter-subcarrier nonlinear interference canceler approach is also proposed. A performance evaluation of the well-known NLC techniques and the proposed approach is provided in the context of Nyquist and super-Nyquist superchannel systems.Comment: Accepted in the IEEE Communications Surveys and Tutorial

Parallel Neural Network Structures for Signal-to-Noise Ratio Estimation in Optical Fiber Communication Systems

This paper proposes two novel neural network (NN) structures to estimate long-term steady linear and nonlinear signal-to-noise ratio (SNR) components in optical fiber communication systems. The first proposed structure is a parallel NNbased (ParNN) estimator, which estimates each SNR component using a different NN structure and input feature set. A combination of gated recurrent unit and dense layers is used to estimate the linear SNR component. On the other hand, the nonlinear SNR component is estimated using a combination of convolutional layer with dense layer. The proposed input features of the ParNN estimator are generated solely from the received signal without knowledge of the transmitted signal. These features are formed of the lower quartile, upper quartile, and entropy, which can accurately characterize the behavior of the SNR components by measuring the received signal spread and uncertainty. For further improvement of the ParNN estimator, an additional stage is added to form the proposed enhanced ParNN (EParNN) estimator. This additional stage consists of two feedforward NNs (FFNNs), each with a single dense layer, where the first FFNN is used to estimate the linear SNR component and the second one estimates the nonlinear SNR component. The input of this additional stage is a combination of the input features and output of the ParNN estimator. The computational complexity is derived for the proposed estimators. The training and testing dataset is built from 16-ary quadrature amplitude modulation of a dual polarization on a wide range of standard single-mode fiber system configurations, e.g., number of wavelength division multiplexing channels, optical launch power, and number of spans. Numerical results demonstrate that the proposed ParNN estimator achieves better SNR estimation accuracy with comparable computational complexity compared to the most efficient work in the literature. The proposed ParNN estimator can independently estimate each SNR component, in which the complexity per SNR component is reduced.</p

Convex optimization-based high-speed and security joint optimization scheme in optical access networks

Data availability: Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.Data rate and security are essential performance metrics for passive optical networks (PON). However, existing optical access networks lack standardized metrics to evaluate rate and security performance uniformly. This paper introduces a high-speed and security joint optimization scheme for optical access networks using convex optimization. Evaluation metrics for data rate and security performance in PON are established. According to the evaluation metrics, the security optimization objective function Us, high-speed optimization objective function GMI, and high-speed security joint-optimization objective function Hs are established. An optimization problem is formulated to maximize weighted rate and security indicators, factoring in constraints such as maximum power, probability, amplifier capacity, normalized mutual information, and key and frame lengths. An alternating optimization method is applied to iteratively address sub-problems by exploiting successive convex approximations and differences of convex functions. This transforms non-convex sub-problems into convex optimizations. Experimental results highlight notable improvements in objective function values, confirming the effectiveness of the proposed high-speed security optimization algorithm for optical access networks.Chongqing Postdoctoral Funding Project (2112012727685993); China Postdoctoral Science Foundation (2021M700563); Chongqing Municipal Education Commission (CXQT21019, KJQN202100643); National Natural Science Foundation of China (62025105, 62071076, 62205043)