Portrait of CK Mididoddi

CK Mididoddi

Research Student


My research includes Compressed sensing in Photonic system to detect high speed RF signals, All-optical random pattern generation using Photonic time stretch.  



  • Mididoddi, C. and Wang, C. (2017). Adaptive non-uniform photonic time stretch for blind RF signal detection with compressed time-bandwidth product. Optics Communications [Online] 396:221-227. Available at: http://dx.doi.org/10.1016/j.optcom.2017.03.052.
    Photonic time stretch significantly extends the effective bandwidth of existing analog-to-digital convertors by slowing down the input high-speed RF signals. Non-uniform photonic time stretch further enables time bandwidth product reduction in RF signal detection by selectively stretching high-frequency features more. However, it requires the prior knowledge of spectral-temporal distribution of the input RF signal and has to reconfigure the time stretch filter for different RF input signals. Here we propose for the first time an adaptive non-uniform photonic time stretch method based on microwave photonics pre-stretching that achieves blind detection of high-speed RF signals with reduced time bandwidth product. Non-uniform photonic time stretch using both quadratic and cubic group delay response has been demonstrated and time bandwidth product compression ratios of 72% and 56% have been achieved respectively.
  • Mididoddi, C. et al. (2017). High throughput photonic time stretch optical coherence tomography with data compression. IEEE Photonics Journal [Online]. Available at: https://doi.org/10.1109/JPHOT.2017.2716179.
    Photonic time stretch enables real time high throughput optical coherence tomography (OCT), but with massive data volume being a real challenge. In this paper, data compression in high throughput optical time stretch OCT has been explored and experimentally demonstrated. This is made possible by exploiting spectral sparsity of encoded optical pulse spectrum using compressive sensing (CS) approach. Both randomization and integration have been implemented in the optical domain avoiding an electronic bottleneck. A data compression ratio of 66% has been achieved in high throughput OCT measurements with 1.51 MHz axial scan rate using greatly reduced data sampling rate of 50 MS/s. Potential to improve compression ratio has been exploited. In addition, using a dual pulse integration method, capability of improving frequency measurement resolution in the proposed system has been demonstrated. A number of optimization algorithms for the reconstruction of the frequency-domain OCT signals have been compared in terms of reconstruction accuracy and efficiency. Our results show that the L1 Magic implementation of the primal-dual interior point method offers the best compromise between accuracy and reconstruction time of the time-stretch OCT signal tested.

Conference or workshop item

  • Mididoddi, C. and Wang, C. (2018). Photonic compressive sensing enabled data efficient time stretch optical coherence tomography. in: Podoleanu, A. G. H. and Bang, O. eds. Second Canterbury Conference on Optical Coherence Tomography, 2017, Canterbury, United Kingdom. SPIE. Available at: https://doi.org/10.1117/12.2283035.
    Photonic time stretch (PTS) has enabled real time spectral domain optical coherence tomography (OCT). However, this method generates a torrent of massive data at GHz stream rate, which requires capturing as per Nyquist principle. If the OCT interferogram signal is sparse in Fourier domain, which is always true for samples with limited number of layers, it can be captured at lower (sub-Nyquist) acquisition rate as per compressive sensing method. In this work we report a data compressed PTS-OCT system based on photonic compressive sensing with 66% compression with low acquisition rate of 50MHz and measurement speed of 1.51MHz per depth profile. A new method has also been proposed to improve the system with all-optical random pattern generation, which completely avoids electronic bottleneck in traditional binary pseudorandom binary sequence (PRBS) generators.
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  • Mididoddi, C. et al. (2018). Ultrafast User Localization and Beam Steering in Optical Wireless Communication Using an In-Fibre Diffraction Grating. in: 2018 International Topical Meeting on Microwave Photonics (MWP). IEEE. Available at: https://doi.org/10.1109/MWP.2018.8552858.
    Wavelength-controlled laser beam steering has been successfully demonstrated for indoor optical wireless communications (OWC). Here we demonstrate ultrafast user localization (50 million scans per second) in OWC based on real-time wavelength monitoring. A separate time stretched pulsed laser source is introduced to implement ultrafast optical wavelength (hence optical beam) scanning. A dispersion unbalanced Mach-Zehnder interferometric configuration creates chirped encoding in stretch optical pulses. The reflected optical wavelength from a remote user carrying the location information of the user is detected by real-time instantaneous microwave frequency detection. This new approach facilitates simultaneous ultrafast user localization and data transmission at communication C-band. A proof-of-concept experiment is carried out to verify the proposed approach.
  • Mididoddi, C., Ahmad, E. and Wang, C. (2017). Data-efficient high-throughput fiber Bragg grating sensors using photonic time-stretch compressive sensing. in: European Conferences on Laser and Opto-electronics.. Available at: https://doi.org/10.1109/CLEOE-EQEC.2017.8086896.
    In this paper, we demonstrate the first application of photonic compressive sensing technique in a data-efficient interrogation system for high-throughput distributed FBG sensors. In particular, reconstruction of a wide bandwidth chirped temporal waveform has been achieved using compressive sensing with optical integration. This enables data-compressed high-throughput interrogation of FBG sensors for dynamic non-uniform strain sensing
  • Mididoddi, C., Ahmad, E. and Wang, C. (2017). All-optical random sequence generation for compressive sensing detection of RF signals. in: International Topical Meeting on Microwave Photonics (MWP), 2017. IEEE, pp. 1-4. Available at: https://doi.org/10.1109/MWP.2017.8168639.
    Photonic compressive sensing is a promising data compression method and has been successfully applied in high-speed RF signal detection with greatly reduced requirement for receiver bandwidth. A key challenge is due to the electronic bottleneck in high-speed random sequence generation and mixing. In this work, we propose and experimentally demonstrated for the first time all-optical random sequence generation and mixing for compressive sensing detection of RF signals. The technique is based on photonic time stretch involving cascaded Mach-Zehnder Interferometers (MZIs) for spectral domain random mixing. In a proof-of-concept experiment, successful detection of 1 GHz RF signal with 25% compression ratio using only 50 MHz detection bandwidth has been demonstrated。
  • Mididoddi, C. et al. (2017). Photonic time-stretch optical coherence tomography with data compression and improved resolution. in: 2017 Conference on Lasers and Electro-Optics Pacific Rim (CLEO-PR). IEEE. Available at: http://dx.doi.org/10.1109/CLEOPR.2017.8118840.
    In this paper, we investigate the reconstruction of non-harmonic tones in data-compressed PTS-OCT based on multiple pulse integration. To the best of our knowledge, this is the first time that frequency reconstruction resolution less than the pulse repetition rate has been demonstrated in PTS-OCT through all-optical compressive sensing, leading to improved depth resolution in OCT measurement.
  • Mididoddi, C., Wang, G. and Wang, C. (2016). Data Compressed Photonic Time-Stretch Optical Coherence Tomography. in: 2016 IEEE Photonics Conference (IPC).. Available at: http://ieeexplore.ieee.org/document/7830959/.
    Photonic time stretch enables real-time optical coherence tomography, but at the cost of extreme requirement for high-speed signal acquisition and massive data set. This work reports a data compressed real-time Fourier-domain optical coherence tomography based on photonics-assisted compressive sensing. Compression ratio of 66% is achieved.