Abstract
As known to us all, it is challenging to monitor wideband signals in frequency domain due to the restriction of hardware. Several practical sampling schemes, such as multicoset sampling and the modulated wideband converter (MWC), have been proposed. In this work, a co-prime array (CA) based modulated wideband converter (MWC) spectrum sensing method is suggested. Our proposed method has the same sampling principle as the MWC but has some advantages compared to MWC. Firstly, CA-based MWC is an array-based MWC system. Each sensor is usually corrupted by independent noise for an array system which can be used for noise averaging, while all channels in conventional MWC have the same receiving noise. Secondly, by incorporating the co-prime array, we can estimate the power spectrum of signal directly employing its second-order statistical properties. Moreover, the system minimal sampling rate can be reduced further because of the reduction of sampling channels. Simulation results show that our method has better performance than traditional methods.
Highlights
Nowadays, spectral resources traditionally allocated to licensed users by governmental organizations are becoming scant
System, because the signal in each sampling channel comes from the same sensor, we can assume that all sampling channels are corrupted by the same additive Gaussian white noise
In our proposed array-based modulated wideband converter (MWC) system, we can assume that each sampling channel has uncorrelated
Summary
Spectral resources traditionally allocated to licensed users by governmental organizations are becoming scant. It is necessary to sense a wide band of spectrum, leading to prohibitively high Nyquist rates. Another practical issue stems from the time shift since it is difficult to maintain accurate delays or synchronization among the ADCs at such high rates To solve this problem, an analog system, referred to as the modulated wideband converter (MWC) which is comprised of a bank of modulators and low-pass filters is adopted in [7,8,9]. An enhanced virtual ULA can be produced by vectorizing the data covariance matrix of the co-prime array It can detect more transmissions than ULA-based MWC or can reduce the system sampling rate further when the number of transmissions is fixed. Returns the eigenvalue of input matrix. d.e returns the nearest integer towards positive infinity
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
