In this paper, we proposed a point-to-multipoint fiber-optic time transfer scheme over ring networks. The proposed scheme is experimentally demonstrated over a 400 km ring fiber network with the communication data tra...
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We experimentally demonstrate high-capacity coherent DA-RoF fronthaul leveraging pilot symbol- and BPS-based carrier phase recovery. Up to 4.42- This and 32.6- This CPRI-equivalent rates are achieved with single-carri...
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We demonstrate 1.0-Pb/s CPRI-equivalent rate fronthaul with 1024-QAM by using digital-analog radio-over-fiber and coherent detection based on modulator bias-induced residual carrier for phase tracking. The reach is ex...
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We leverage modulator finite extinction ratio-induced residual carrier for transparent digital signal processing in coherent time-frequency-division-multiplexing PON. We experimentally demonstrate flexible data rates ...
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We propose and experimentally demonstrate an inter-subcarrier crosstalk cancellation algorithm for fasterthan-Nyquist transmission. At 20% HD-FEC threshold, the achievable faster-than-Nyquist rate improves from 0.875 ...
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We propose an optical Hilbert direct detection receiver with an all-pass transfer function for carrier-assisted complex-valued double-sideband signal reception. We experimentally demonstrate single-wavelength line rat...
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We propose a low-complexity and IF-free radio-over-fiber scheme using low-pass delta-sigma modulator and RZ shaping for both sub-6GHz and millimeter-wave bands. Up to 262144-QAM, 65536-QAM and 4096-QAM formats are exp...
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We demonstrate 203.6Tb/s CPRI-equivalent-rate 1024-QAM self-homodyne fronthaul using digital-analog radio-over-fiber and comb-based SDM and WDM superchannel from a single laser source. We further present new records f...
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This paper investigates the multi-Unmanned Aerial Vehicle(UAV)-assisted wireless-powered Mobile Edge Computing(MEC)system,where UAVs provide computation and powering services to mobile *** aim to maximize the number o...
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This paper investigates the multi-Unmanned Aerial Vehicle(UAV)-assisted wireless-powered Mobile Edge Computing(MEC)system,where UAVs provide computation and powering services to mobile *** aim to maximize the number of completed computation tasks by jointly optimizing the offloading decisions of all terminals and the trajectory planning of all *** action space of the system is extremely large and grows exponentially with the number of *** this case,single-agent learning will require an overlarge neural network,resulting in insufficient ***,the offloading decisions and trajectory planning are two subproblems performed by different executants,providing an opportunity for *** thus adopt the idea of decomposition and propose a 2-Tiered Multi-agent Soft Actor-Critic(2T-MSAC)algorithm,decomposing a single neural network into multiple small-scale *** the first tier,a single agent is used for offloading decisions,and an online pretrained model based on imitation learning is specially designed to accelerate the training process of this *** the second tier,UAVs utilize multiple agents to plan their *** agent exerts its influence on the parameter update of other agents through actions and rewards,thereby achieving joint *** results demonstrate that the proposed algorithm can be applied to scenarios with various location distributions of terminals,outperforming existing benchmarks that perform well only in specific *** particular,2T-MSAC increases the number of completed tasks by 45.5%in the scenario with uneven terminal ***,the pretrained model based on imitation learning reduces the convergence time of 2T-MSAC by 58.2%.
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