对OTFS系统进行叠加完美二进制数组辅助通道估计
Zuping Tang1, Hengyou Kong1, Ziyu Wu1
1School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China.
Entropy (Basel, Switzerland)
|August 26, 2023
概括
本研究引入了一种用于使用叠加完美二进制数组 (PBA) 的正角时频空间 (OTFS) 调制的新通道估计方法. 这种方法在高流动性场景中提高了光谱效率 (SE),而不需要额外的.
科学领域:
- 无线通信无线通信
- 信号处理 信号处理
- 信息理论 信息理论
背景情况:
- 在高流动性环境中,正交时频空间 (OTFS) 调制提供了优于正交频率分割复杂化 (OFDM) 的性能,这是由于增强的通道估计.
- 叠加的试点 (SP) 基于通道估计提高了光谱效率 (SE) 与嵌入式试点 (EP) 方法相比,但传统上需要单独的延迟多普勒点击估计.
研究的目的:
- 为OTFS调制提出一种新的高SE通道估计方法,消除了对额外试验的需求.
- 提高高流动性无线通信系统的频谱效率.
主要方法:
- 提出了一种新的通道估计技术,将完美的二进制数组 (PBA) 叠加到数据符号上,作为同一内的飞行员.
- 道估计是通过利用PBA的自相关性属性来识别相关性峰值来执行的,提取延迟-多普勒点击信息和复杂的道增益.
- 通过最大化信号与干扰加噪声比 (SINR) 来获得PBA叠加的最佳功率比,以增强系统SE.
主要成果:
- 拟议的基于PBA的叠加试点方法实现了准确的通道估计,与现有的EP方法相美.
- 该方法通过将试点信息集成到数据框架中,显著提高了光谱效率 (SE).
- 优化PBA功率比进一步提高了信号与干扰加噪声比 (SINR).
结论:
- 基于PBA的新通道估计方法为高流动性场景中的OTFS调制提供了高SE解决方案.
- 这种方法克服了传统的SP方法的局限性,消除了单独的试点框架的需要.
- 拟议的技术为改善无线通信系统性能提供了可行的替代方案.
相关概念视频
01:21Properties of Fourier Transform I
195
The application of Fourier Transform properties in radio broadcasting is multifaceted, enabling significant advancements in the way signals are transmitted and received. Key areas where these properties are utilized include simultaneous multi-channel transmission, audio clip speed adjustments, live broadcast delays for different time zones, audio frequency adjustments, and signal demodulation.
In radio broadcasting, multiple audio signals often need to be transmitted simultaneously. The Fourier...
In radio broadcasting, multiple audio signals often need to be transmitted simultaneously. The Fourier...
195
01:26Linear Approximation in Frequency Domain
110
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....
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....
110
01:10Fast Fourier Transform
378
The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
The computational efficiency of the FFT becomes...
378
01:20Discrete-Time Fourier Series
298
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.
For a discrete-time periodic signal x[n]...
For a discrete-time periodic signal x[n]...
298
01:07Basic signals of Fourier Transform
521
The Fourier Transform is a pivotal mathematical tool in signal processing, enabling the transformation of time-domain signals into their frequency-domain representations. Among the numerous elements within this domain, certain functions like the sinc function, delta function, and exponential signals hold significant importance due to their unique properties and implications.
The sinc function, defined as sinc(x) = sin(πx)/(πx), is particularly notable for its symmetry and behavior at...
The sinc function, defined as sinc(x) = sin(πx)/(πx), is particularly notable for its symmetry and behavior at...
521
01:21Linear Approximation in Time Domain
101
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,...
101