基于亚奈奎斯特采样的宽带频率和角频谱联合频谱感知

Azril Haniz, T. Matsumura, F. Kojima
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引用次数: 0

摘要

未来5G和超5G (B5G)网络的先进频谱共享技术有可能通过利用多个基站发射的信号的载波频率和到达角(AOA)的知识来实现更高的频谱利用效率。本文提出了一种利用亚奈奎斯特模数转换器(ADC)同时沿频率域和角域进行宽带频谱检测的算法。为了支持AOA估计,该算法是在传统的多协集采样(MCS)算法的基础上发展起来的,并被表示为一个典型的压缩感知问题。通过蒙特卡罗仿真对该方法的频谱传感性能进行了评估,结果表明该方法可以在不需要高速adc的情况下成功地实现宽带二维频谱的传感。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint Spectrum Sensing of Wideband Frequency and Angular Spectrum based on Sub-Nyquist Sampling
Advanced spectrum sharing technology for future 5G and Beyond 5G (B5G) networks have the potential to achieve higher spectrum utilization efficiency by utilizing knowledge of the carrier frequency and angle-of-arrival (AOA) of the signals emitted from multiple base stations. In this paper, an algorithm to perform wideband spectrum sensing along the frequency and angular domains simultaneously utilizing sub-Nyquist analog-to-digital converters (ADC) is proposed. The proposed algorithm is developed based on the conventional multi-coset sampling (MCS) algorithm in order to support AOA estimation, and is expressed as a typical compressive sensing problem. Spectrum sensing performance is evaluated using Monte Carlo simulation, and results show that it can successfully sense the wideband two-dimensional spectrum without the need for high-rate ADCs.
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