Abstract
AbstractAs the bandwidth increases, the high-speed sampling rate becomes the bottleneck for the development of wideband spectrum sensing. Wideband spectrum sensing with sub-Nyquist sampling attracts more attention and modulated wideband converter (MWC) is an attractive sub-Nyquist sampling system. For the purpose of breaking the system structure limit, an advanced sub-Nyquist sampling framework is proposed to simplify the MWC system structure, adopting the single sampling channel structure with a frequency shifting module to acquire the sub-Nyquist sampling values. In order to recover the signal support information, the sensing matrix must be built according to the only one mixing function. Most existing support recovery methods rely on some prior knowledge about the spectrum sparsity, which is difficult to acquire in practical electromagnetic environment. To address this problem, we propose an adaptive residual energy detection algorithm (ARED), which bypasses the need for the above-mentioned prior knowledge. Simulation results show that, without requiring the aforementioned prior knowledge, the ARED algorithm based on the advanced sub-Nyquist sampling framework has the similar performance as MWC and even higher than MWC in some cases using only one sampling channel.
Funder
Heilongjiang Postdoctoral Financial Assistance
Natural Science Foundation for Outstanding Young Scholars of Heilongjiang Province
National Key Research and Development Program of China
Fundamental Research Funds for the Central Universities
Publisher
Springer Science and Business Media LLC
Cited by
1 articles.
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1. Broadband Spectrum Sensing Based on Exponential Sum Decomposition;2023 IEEE 11th Joint International Information Technology and Artificial Intelligence Conference (ITAIC);2023-12-08