The optical saturation characteristics in the germanium-on-silicon（Ge-on-Si） photodetector are studied for the first time, to the best of our knowledge. The relationship between the optical saturation characteristic...
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The optical saturation characteristics in the germanium-on-silicon（Ge-on-Si） photodetector are studied for the first time, to the best of our knowledge. The relationship between the optical saturation characteristics and the optical field distribution in the Ge layer is illustrated by the simulation. This theory is verified by comparative experiments with single-injection and dual-injection structures. The dual-injection photodetector with a more balanced and uniform optical field distribution has a 13% higher responsivity at low optical power and 74.4%higher saturation current at 1550 nm. At higher optical power, the bandwidth of the dual-injection photodetector is five times larger than that of the single-injection photodetector.
Intelligent Eco Networking (IEN) makes significant progress to be a shared in-network computing infrastructure towards the future Internet, owing to its value-oriented ideology, content-centric fashion, intelligent co...
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ISBN:
(数字)9781728192161
ISBN:
(纸本)9781728192178
Intelligent Eco Networking (IEN) makes significant progress to be a shared in-network computing infrastructure towards the future Internet, owing to its value-oriented ideology, content-centric fashion, intelligent collaborative management, and decentralized consensus trust preservation. Comprehensively uniting resources of computing, storage, and network, IEN executes the computing tasks in the network layer with name-based functions, integrating the SDN-like collaborative schedule and coexisting with the current TCP/IP via network slicing. To gradually evolve to be an advanced networking ecosystem, IEN copes with ultra-low latency, massive connections, and large-scale coverage to sustain the new rising information services. The simple evaluations demonstrate the profound potential of IEN in settling the in-network computing, providing the practical foundation for the multimodal computing paradigm in the future Internet.
Recent advances in communication and networking technologies are leading to a plethora of novel wireless services that range from unmanned aerial vehicle (UAV) communication to smart cognitive networks and massive Int...
Recent advances in communication and networking technologies are leading to a plethora of novel wireless services that range from unmanned aerial vehicle (UAV) communication to smart cognitive networks and massive Internet of Things (IoT) systems. Enabling these emerging applications over the fifth generation (5G) of wireless cellular systems requires meeting numerous challenges pertaining to spectrum sharing and management. In fact, most 5G applications will be highly reliant on intelligent spectrum management techniques, which should adapt to dynamic network environments while also guaranteeing high reliability and high quality-of-experience (QoE). In this context, the use of artificial intelligence (AI) techniques that include deep learning, convolutional neural networks, and reinforcement learning, among many others, is expected to play a very important role in paving the way towards truly AI-driven spectrum management, thus enabling tomorrow's smart city services. Therefore, it has become imperative to investigate and apply AI techniques to solve emerging spectrum management problems in various wireless networks. This includes leveraging AI to address a wide range of wireless networking challenges ranging from network management to dynamic spectrum sharing and resource management.
A cost effective and ultra-simple dual-polarization interferometric fiber optic gyroscope utilizing single-mode components was proposed and tested, which achieves an overall bias instability below 2 χ 10-2 °/h a...
We report an all-optical atomic vector magnetometer using dual Bell-Bloom optical pumping beams in a Rb vapor cell. This vector magnetometer consists of two orthogonal optical pumping beams, with amplitude modulations...
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Dictionary learning methods can be split into two categories: i) class specific dictionary learning ii) class shared dictionary learning. The difference between the two categories is how to use the discriminative info...
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In many application areas such as large-scale disaster detection, IoT networks connote the characteristics of LLN (Low power and Lossy Network). With few exceptions, prior work on RPL(Routing Protocol for LLN), a stan...
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We investigate the problem of resource allocation in a downlink orthogonal frequency-division multiple access （OFDMA） broadband network with an eavesdropper under the condition that both legitimate users and the eav...
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We investigate the problem of resource allocation in a downlink orthogonal frequency-division multiple access （OFDMA） broadband network with an eavesdropper under the condition that both legitimate users and the eavesdropper are with imperfect channel state information （CSI）. We consider three kinds of imperfect CSI： （1） noise and channel estimation errors, （2） feedback delay and channel prediction, and （3） limited feedback channel capacity, where quantized CSI is studied using rate-distortion theory because it can be used to establish an information-theoretic lower bound on the capacity of the feedback channel. The problem is formulated as joint power and subcarrier allocation to optimize the maximum-minimum （max-min） fairness criterion over the users＇ secrecy rate. The problem considered is a mixed integer nonlinear programming problem. To reduce the complexity, we propose a two-step suboptimal algorithm that separately performs power and subcarrier allocation. For a given subcarrier assignment, optimal power allocation is achieved by developing an algorithm of polynomial computational complexity. Numerical results show that our proposed algorithm can approximate the optimal solution.
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