Broadband Microwave Spectrum Sensing Based on Photonic RF Channelization and Compressive Sampling

Shuna Yang,Zizheng Cao,Hao Chi,Yanrong Zhai,Bo Yang,Jun Ou

doi:10.1109/jphot.2019.2960377

Shuna Yang, Zizheng Cao + Show 4 more

Open Access

https://doi.org/10.1109/jphot.2019.2960377

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Abstract

A novel approach to realize broadband microwave spectrum sensing based on photonic RF channelization and compressive sampling (CS) is proposed. The photonic RF channelization system is used to slice the input broadband signal into multiple sub-channel signals with narrow bandwidth in parallel and thus the rate of pseudo-random binary sequence (PRBS) and the bandwidth of the MZM for CS can be largely decreased. It is shown that a spectrally sparse signal within a wide bandwidth can be captured with a sampling rate far lower than the Nyquist rate thanks to both photonic RF channelization and CS. In addition, the influence of the non-ideal filtering of the photonic channelizer is evaluated and a novel approach based on measuring twice is proposed to overcome the problem of frequency aliasing induced by the non-ideal filtering. It is demonstrated that a system with 20 Gbit/s PRBS and 2.5 GS/s digitizer can be used to capture a signal with multiple tones within a 40 GHz bandwidth, which means a sampling rate 32 times lower than the Nyquist rate.

Highlights

Microwave signal processing with photonic technology has attracted much interest owing to the advantages of wide bandwidth, low loss, and immunity to electromagnetic interference offered by photonics
A variety of photonics-based approaches for microwave spectrum sensing have been proposed [1]–[28]. These approaches can be roughly divided into four categories: photonic instantaneous frequency measurement [1]–[4], spectrum analysis based on optical frequency scanning [5]–[7], photonic RF channelization [8]–[15], and photonic-assisted analog-to-digital conversion (ADC) [16]–[28]
For the first sub-channel, the process of compressive sampling (CS) measurement can be modeled by y = DHRx1 = DHRW1θ, where x1 = W1θ is a column vector with length I, W1 is a I × I matrix denoting the Fourier orthogonal basis, W1 ∈ [0, BF TCF ], θ is a I × 1 vector denoting the spectrum information of x1, R is a I × I matrix denoting the mixing by the pseudo-random binary sequence (PRBS) r (t ), H is a I × I matrix denoting the impulse response of the low-pass filter (LPF), and D is a J × I matrix denoting the down-sampling of the digitizer (I = J × RCS)

Summary

Introduction

Microwave signal processing with photonic technology has attracted much interest owing to the advantages of wide bandwidth, low loss, and immunity to electromagnetic interference offered by photonics. The photonic CS based on random demodulator aims to capture sparse multitone signals with simple structure [21] while the MWC-based photonic CS is preferred for the capture of sparse multiband signals with good approximation [22] These two schemes both involve random mixing, low-pass filtering, and down-sampling, while differ in the structure, recovery algorithm, and assumed signal model. In [26], an optical mixing scheme for realizing the MWC or the random demodulator is proposed to avoid high speed electronics, the PRBS is recorded in the frequency domain by using a spectrum shaper with spatial light modulator (SLM). In [27], an approach to realizing microwave spectrum sensing based on photonic time stretch and CS is proposed, the signal to be measured is slowed down in the time domain by photonic time stretch and the rate of the applied PRBS can be decreased. It is shown that a system with a 20 Gbit/s PRBS and a 2.5 GS/s digitizer can be used to capture a signal with multiple tones in a 40 GHz bandwidth

Operation Principle

Results and Discussions

Summary