prof.dr. Z. Tian

1. Efficient Angle Estimation for MIMO Systems via Redundancy Reduction Representation
   Zhang, Yu; Wang, Yue; Tian, Zhi; Leus, G.; Zhang, Gong;
   IEEE Signal Processing Letters,
   Volume 29, pp. 1052--1056, 2022. DOI: 10.1109/LSP.2022.3164850

2. Efficient Super-Resolution Two-Dimensional Harmonic Retrieval With Multiple Measurement Vectors
   Zhang, Yu; Wang, Yue; Tian, Zhi; Leus, G.; Zhang, Gong;
   IEEE Transactions on Signal Processing,
   Volume 70, pp. 1224--1240, 2022. DOI: 10.1109/TSP.2022.3150964

3. Direction of Arrival Estimation of Wideband Sources Using Sparse Linear Arrays
   Wang, Feiyu; Tian, Zhi; Leus, G.; Fang, Jun;
   IEEE Transactions on Signal Processing,
   Volume 69, pp. 4444--4457, 2021. DOI: 10.1109/TSP.2021.3094718

4. Low-Complexity Gridless 2D Harmonic Retrieval via Decoupled-ANM Covariance Reconstruction
   Yu Zhang; Yue Wang; Zhi Tian; G. Leus; Gong Zhang;
   In 29th European Signal Processing Conference (EUSIPCO 2020),
   Amsterdam (Netherlands), EURASIP, pp. 1876-1880, August 2020.
   document

5. Efficient Super-Resolution Two-Dimensional Harmonic Retrieval Via Enhanced Low-Rank Structured Covariance Reconstruction
   Yue Wang; Yu Zhang; Zhi Tian; G. Leus; Gong Zhang;
   In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
   pp. 5720-5724, 2020. DOI: 10.1109/ICASSP40776.2020.9054756
   document

6. Wideband Direction of Arrival Estimation with Sparse Linear Arrays
   Feiyu Wang; Zhi Tian; Jun Fang; G. Leus;
   In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
   pp. 4542-4546, 2020. DOI: 10.1109/ICASSP40776.2020.9053681
   document

7. Super-Resolution Channel Estimation for Arbitrary Arrays in Hybrid Millimeter-Wave Massive MIMO Systems
   Yue Wang; Yu Zhang; Zhi Tian; Geert Leus; Gong Zhang;
   IEEE Journal of Selected Topics in Signal Processing,
   Volume 13, Issue 5, pp. 947--960, 2019. ISSN: 1932-4553. DOI: 10.1109/JSTSP.2019.2937632
   
   Abstract: ...

   This paper develops efficient channel estimation techniques for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems under practical hardware limitations, including an arbitrary array geometry and a hybrid hardware structure. Taking on an angle-based approach, this work adopts a generalized array manifold separation approach via Jacobi-Anger approximation, which transforms a non-ideal, non-uniform array manifold into a virtual array domain with a desired uniform geometric structure to facilitate super-resolution angle estimation and channel acquisition. Accordingly, structure-based optimization techniques are developed to effectively estimate both the channel covariance and the instantaneous channel state information (CSI) within a short sensing time. The different time-varying scales of channel path angles versus path gains are capitalized to design a two-step CSI estimation scheme that can quickly sense fading channels. Theoretical results are provided on the fundamental limits of the proposed technique in terms of sample efficiency. For computational efficiency, a fast iterative algorithm is developed via the alternating direction method of multipliers. Other related issues such as spurious-peak cancellation in non-uniform linear arrays and extensions to higher-dimensional cases are also discussed. Simulations testify the effectiveness of the proposed approaches in hybrid mmWave massive MIMO systems with arbitrary arrays.
   
   document

8. Angle-Based Channel Estimation with Arbitrary Arrays
   Yue Wang; Yu Zhang; Zhi Tian; G. Leus; Gong Zhang;
   In Proc. of IEEE Global Communications Conf. (GLOBECOM),
   Waikoloa, Hawaii, USA, December 2019. DOI: 10.1109/GLOBECOM38437.2019.9013215

9. Super-Resolution Spatial Channel Covariance Estimation for Hybrid Precoding in mmWave Massive MIMO
   Yu Zhang; Yue Wang; Zhi Tian; G. Leus; Gong Zhang;
   In Proc. of IEEE Global Communications Conf. (GLOBECOM),
   Waikoloa, Hawaii, USA, December 2019. DOI: 10.1109/GLOBECOM38437.2019.9014327

10. Compressive Covariance Sensing: Structure-based compressive sensing beyond sparsity
    D. Romero; D.D. Ariananda; Zhi Tian; G. Leus;
    IEEE Signal Processing Magazine,
    Volume 33, Issue 1, pp. 78-93, January 2016. DOI: 10.1109/MSP.2015.2486805
    document

11. Tracking target signal strengths on a grid using sparsity
    S. Farahmand; G.B. Giannakis; G.J.T. Leus; Zhi Tian;
    EURASIP J. Advances Signal Proc.,
    Volume 2014, Issue 7, July 2014. DOI: 10.1186/1687-6180-2014-7
    document

12. Special issue on Compressive Sensing in Communications
    W.U. Bajwa; G. Leus; A. Scaglione; M. Stojanovic; Zhi Tian;
    Physical Communication,
    Volume 5, Issue 2, pp. 61-63, June 2012. ISSN 1874-4907. DOI: 10.1016/j.phycom.2011.11.003
    document

13. Joint Dynamic Resource Allocation and Waveform Adaptation for Cognitive Networks
    Zhi Tian; G. Leus; V. Lottici;
    IEEE J. Sel. Areas Comm. (JSAC),
    Volume 29, Issue 2, pp. 443-454, February 2011. DOI: 10.1109/JSAC.2011.110216
    document

14. Multi-coset sampling for power spectrum blind sensing
    D. Dony Ariananda; G. Leus; Zhi Tian;
    In 2011 17th Int. Conf. on Digital Signal Proc. (DSP),
    July 2011. DOI: 10.1109/ICDSP.2011.6005003
    document

15. Sparsity-aware Kalman tracking of target signal strengths on a grid
    S. Farahmand; G.B. Giannakis; G. Leus; Zhi Tian;
    In 2011 Proc. 14th Int. Conf. on Information Fusion (FUSION),
    July 2011. Print ISBN: 978-1-4577-0267-9.
    document

16. Recovering Second-Order Statistics from Compressive Measurements
    G. Leus; Zhi Tian;
    In 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP),
    Puerto Rico, IEEE, pp. 337-340, December 2011. ISBN 978-1-4577-2103-8.
    document

17. Compressed Sensing Techniques for Dynamic Resource Allocation in Wideband Cognitive Networks
    Z. Tian; G. Leus; V. Lottici;
    In Proc. Signal Processing Advances in Wireless Communications (SPAWC),
    Marrakech, IEEE, June 2010.
    document

18. A Novel Approach to UWB Data Detection with Symbol-Level Synchronization
    V. Lottici; Z. Tian; G. Leus;
    Physical Communication,
    Volume 2, Issue 4, pp. 296-305, 2009.
    document

19. Detection of sparse signals under finite-alphabet constraints
    Zhi Tian; G. Leus; V. Lottici;
    In Proc. IEEE ICASSP,
    Taipei (Taiwan), IEEE, April 2009.
    document

20. Joint dynamic resource allocation and waveform adaptation in cognitive radio networks
    Z. Tian; G. Leus; V. Lottici;
    In Proc. IEEE ICASSP,
    Las Vegas, IEEE, pp. 5368-5371, April 2008. ISBN: 1-4244-1484-9.
    document

21. A Synchronization-Free Approach to Data Recovery for Multiple Access UWB Communications
    V. Lottici; G. Tian; G. Leus;
    In IEEE Int. Conf. UWB (ICUWB 2008),
    Hannover, Germany, pp. 153-156, September 2008.
    document

22. Frequency agile waveform adaptation for cognitive radios
    Z. Tian; G. Leus; V. Lottici;
    In Proc. IEEE Int. Waveform Diversity and Design Conf. (WDDC'07),
    Pisa (IT), IEEE, pp. 326-329, June 2007. DOI: 10.1109/WDDC.2007.4339436
    document

23. Synchronization-Free Data Detection for UWB Communications
    V. Lottici; Z. Tian; G. Leus;
    In Proc. IEEE 14th annual Symp. on Comm. Vehicular Techn. in the Benelux (SCVT'07),
    Delft, The Netherlands, November 2007. ISBN 1-4244-1370-2.
    document

BibTeX support