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Design Example01:23

Design Example

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The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
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The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
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The z-transform is a fundamental tool in digital signal processing, enabling the analysis of discrete-time systems through its various properties. It is an invaluable tool for analyzing discrete-time systems, offering a range of properties that simplify complex signal manipulations. One fundamental property is linearity. For any two discrete-time signals, the z-transform of their linear combination equals the same linear combination of their individual z-transforms. This property is essential...
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A signal x(t) is a set of data or a time function representing a variable of interest. Signals typically convey information about a phenomenon, such as atmospheric temperature, humidity, human voice, television images, a dog's bark, or birdsongs. More generally, a signal can be a function of more than one independent variable. For instance, images depend on horizontal and vertical positions and can be regarded as two-dimensional signals. However, this text will focus on one-dimensional...
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The Discrete-Time Fourier Transform (DTFT) is an essential mathematical tool for analyzing discrete-time signals, converting them from the time domain to the frequency domain. This transformation allows for examining the frequency components of discrete signals, providing insights into their spectral characteristics. In the DTFT, the continuous integral used in the continuous-time Fourier transform is replaced by a summation to accommodate the discrete nature of the signal.
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综合传感和通信目标检测框架和基于信息理论的波形设计方法.

Qilong Miao1, Xiaofeng Shen1, Chenfei Xie2

  • 1School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

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概括

综合传感和通信 (ISAC) 系统的新框架改进了使用正交时频空间 (OTFS) 波形的目标检测. 这种相对测试 (RET) 方法在低信号噪声比 (SNR) 条件下显著优于传统测试.

关键词:
这就是OTFS OTFS.信息理论信息理论集成传感和通信.目标检测 目标检测 目标检测波形设计 波形设计

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科学领域:

  • 电气工程 电气工程
  • 信号处理 信号处理
  • 信息理论 信息理论

背景情况:

  • 综合传感和通信 (ISAC) 系统对于目标检测至关重要.
  • 传统的概率比测试 (LRT) 和直角频率分割复杂化 (OFDM) 在低信号噪声比 (SNR) 和高速场景中分别面临局限性.

研究的目的:

  • 为ISAC系统提出一个先进的目标检测框架.
  • 提高ISAC目标检测的性能,特别是在具有挑战性的低SNR和高速条件下.

主要方法:

  • 一个基于信息理论的框架,利用正交时频空间 (OTFS) 波形来进行ISAC目标检测.
  • 实施相对测试 (RET) 用于将回声信号与目标存在/缺席假设进行比较.
  • 开发一种代的OTFS-ISAC波形设计 (I-OTFS-WD) 方法,使用小化-最大化 (MM) 和半确定的放松 (SDR) 来最大化相对.

主要成果:

  • 在低SNR条件下,RET算法显示性能比LRT提高9.12倍.
  • I-OTFS-WD 方法将 RET 算法的样本要求减少 40%.

结论:

  • 与传统方法相比,拟议的OTFS-ISAC框架与RET提供了优越的目标检测能力.
  • 代波形设计有效地提高了系统性能,减少了数据需求,提高了ISAC应用中的检测精度.