概括
这项研究介绍了用于太赫兹 (THz) 无线系统的新型复杂值神经网络,改进了数据传输. 新方法提高了信号的准确性,并减少了未来移动宽带网络的复杂性.
科学领域:
- 光学通信是指光学通信.
- 无线通信无线通信
- 信号处理 信号处理
背景情况:
- 对高带宽无线服务的日益增长的需求需要先进的移动前程解决方案.
- 太赫兹 (THz) 频段为实现超高容量的数据传输提供了一个可行的选择.
研究的目的:
- 研究光学辅助的THz信号生成与多输入多输出 (MIMO) 和极化分裂多重复合 (PDM) 技术的集成.
- 提出并验证使用MIMO复杂值神经网络 (CVNNs) 的新型时空域等级算法.
主要方法:
- 开发一种基于MIMO复杂值神经网络 (CVNNs) 的新型时空域均等算法.
- 使用光子辅助的THz生成,MIMO和PDM进行信号传输的实验演示.
- 在320 GHz的100米2×2无线MIMO链路上传输60GBaud的PDM-QPSK和30GBaud的PDM-16QAM信号.
主要成果:
- 实现的比特错误率 (BER) 在QPSK下为3.8 × 10-3和16QAM信号下为1.56 × 10-2.
- 与MIMO-Volterra方法相比,拟议的MIMO-CVNN算法表现出优越的性能.
- 该算法有效地保留了信号相位和极化之间的关系.
结论:
- 新的MIMO-CVNN等分算法在THz无线系统的计算复杂性和决策准确性方面提供了显著的优势.
- 这种方法有效地同时处理相位信息和相互极化关系.
- 这些发现支持光子辅助的THz通信的潜力,与先进的信号处理集成,用于未来的高带宽无线服务.
相关概念视频
Linear Approximation in Time Domain
81
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
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Linear Approximation in Frequency Domain
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Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
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Time and frequency -Domain Interpretation of Phase-lag Control
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Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
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Time and frequency -Domain Interpretation of Phase-lead Control
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Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
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State Space to Transfer Function
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The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
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Linear time-invariant Systems
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A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
258


