113 research outputs found

    Constellation Mapping for Physical-Layer Network Coding with M-QAM Modulation

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    The denoise-and-forward (DNF) method of physical-layer network coding (PNC) is a promising approach for wireless relaying networks. In this paper, we consider DNF-based PNC with M-ary quadrature amplitude modulation (M-QAM) and propose a mapping scheme that maps the superposed M-QAM signal to coded symbols. The mapping scheme supports both square and non-square M-QAM modulations, with various original constellation mappings (e.g. binary-coded or Gray-coded). Subsequently, we evaluate the symbol error rate and bit error rate (BER) of M-QAM modulated PNC that uses the proposed mapping scheme. Afterwards, as an application, a rate adaptation scheme for the DNF method of PNC is proposed. Simulation results show that the rate-adaptive PNC is advantageous in various scenarios.Comment: Final version at IEEE GLOBECOM 201

    An attempt using equatorial waves to predict tropical sea surface temperature anomalies associated with the Atlantic zonal mode

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    IntroductionThe forecast for anomalous sea surface temperature (SST) events associated with Atlantic zonal mode, also known as Atlantic Niño/Niña, is full of challenge for both statistical and dynamical prediction models. MethodsThis study combines SST, wind and equatorial wave signal to construct a linear model, aiming to evaluate the potential of equatorial waves in extending the lead time of a skilful prediction for Atlantic Niño/Niña events. Wave-induced geopotential simulated by linear ocean models and potential energy flux calculated using a group-velocity-based wave energy flux scheme are involved to capture the signal of equatorial waves in the model establishment. ResultsThe constructed linear prediction model has demonstrated comparable prediction skill for the SST anomaly to the dynamical models of the North American Multimodel Ensemble (NMME) during the test period (1992-2016). Compared with the statistical forecast using SST persistence, the model notably improves the six-month-lead prediction (Anomaly correlation coefficient increases from 0.07 to 0.28), which owes to the conservation of wave energy in the narrow Atlantic basin that the Rossby waves reflected in the eastern boundary will transfer the energy back to the central equatorial basin and again affect the SST there. ConclusionThis study offers a streamlined model and a straightforward demonstration of leveraging wave energy transfer route for the prediction of Atlantic Niño/Niñas

    Distributed MAC Protocol Supporting Physical-Layer Network Coding

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    Physical-layer network coding (PNC) is a promising approach for wireless networks. It allows nodes to transmit simultaneously. Due to the difficulties of scheduling simultaneous transmissions, existing works on PNC are based on simplified medium access control (MAC) protocols, which are not applicable to general multi-hop wireless networks, to the best of our knowledge. In this paper, we propose a distributed MAC protocol that supports PNC in multi-hop wireless networks. The proposed MAC protocol is based on the carrier sense multiple access (CSMA) strategy and can be regarded as an extension to the IEEE 802.11 MAC protocol. In the proposed protocol, each node collects information on the queue status of its neighboring nodes. When a node finds that there is an opportunity for some of its neighbors to perform PNC, it notifies its corresponding neighboring nodes and initiates the process of packet exchange using PNC, with the node itself as a relay. During the packet exchange process, the relay also works as a coordinator which coordinates the transmission of source nodes. Meanwhile, the proposed protocol is compatible with conventional network coding and conventional transmission schemes. Simulation results show that the proposed protocol is advantageous in various scenarios of wireless applications.Comment: Final versio

    Assimilation and application of nearshore ocean wave models

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    This thesis concentrates on wind-induced ocean waves in coastal areas including two main aspects: wave energy assessment with numerical models and development of a 4D variational assimilation scheme (4DVAR) for nearshore wave simulations. The method for assessing the wave energy potential was developed and applied to the south coast of Java Island. The 4D variational assimilation scheme including partition methods for nearshore wave models has been tailored to SWAN model for adjusting both, wave boundary conditions and wind fields. Also, the proposed scheme was modified for low spatial observation coverage by assuming a group of 'basic' inputs to contain all errors so as to be applied in the German Bight

    Solving dynamic multi-objective problems with a new prediction-based optimization algorithm

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    Funding Information: This work is supported by the National Natural Science Foundation of China under Grants 62006103 and 61872168, in part by the Jiangsu national science research of high education under Grand 20KJB110021. The authors express sincerely appreciation to the anonymous reviewers for their helpful opinions.Peer reviewedPublisher PD

    Review of computational methods for estimating cell potency from single-cell RNA-seq data, with a detailed analysis of discrepancies between method description and code implementation

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    In single-cell RNA sequencing (scRNA-seq) data analysis, a critical challenge is to infer hidden dynamic cellular processes from measured static cell snapshots. To tackle this challenge, many computational methods have been developed from distinct perspectives. Besides the common perspectives of inferring trajectories (or pseudotime) and RNA velocity, another important perspective is to estimate the differentiation potential of cells, which is commonly referred to as "cell potency." In this review, we provide a comprehensive summary of 11 computational methods that estimate cell potency from scRNA-seq data under different assumptions, some of which are even conceptually contradictory. We divide these methods into three categories: mean-based, entropy-based, and correlation-based methods, depending on how a method summarizes gene expression levels of a cell or cell type into a potency measure. Our review focuses on the key similarities and differences of the methods within each category and between the categories, providing a high-level intuition of each method. Moreover, we use a unified set of mathematical notations to detail the 11 methods' methodologies and summarize their usage complexities, including the number of ad-hoc parameters, the number of required inputs, and the existence of discrepancies between the method description in publications and the method implementation in software packages. Realizing the conceptual contradictions of existing methods and the difficulty of fair benchmarking without single-cell-level ground truths, we conclude that accurate estimation of cell potency from scRNA-seq data remains an open challenge

    Wireless Powered Metaverse: Joint Task Scheduling and Trajectory Design for Multi-Devices and Multi-UAVs

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    To support the running of human-centric metaverse applications on mobile devices, Unmanned Aerial Vehicle (UAV)-assisted Wireless Powered Mobile Edge Computing (WPMEC) is promising to compensate for limited computational capabilities and energy supplies of mobile devices. The high-speed computational processing demands and significant energy consumption of metaverse applications require joint resource scheduling of multiple devices and UAVs, but existing WPMEC solutions address either device or UAV scheduling due to the complexity of combinatorial optimization. To solve the above challenge, we propose a two-stage alternating optimization algorithm based on multi-task Deep Reinforcement Learning (DRL) to jointly allocate charging time, schedule computation tasks, and optimize trajectory of UAVs and mobile devices in a wireless powered metaverse scenario. First, considering energy constraints of both UAVs and mobile devices, we formulate an optimization problem to maximize the computation efficiency of the system. Second, we propose a heuristic algorithm to efficiently perform time allocation and charging scheduling for mobile devices. Following this, we design a multi-task DRL scheme to make charging scheduling and trajectory design decisions for UAVs. Finally, theoretical analysis and performance results demonstrate that our algorithm exhibits significant advantages over representative methods in terms of convergence speed and average computation efficiency
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