Collaborative Wideband Compressed Signal Detection in Interplanetary Internet

Abstract As the development of autonomous radio in deep space network, it is possible to actualize communication between explorers, aircrafts, rovers and satellites, e.g. from different countries, adopting different signal modes. The first mission to enforce the autonomous radio is to detect signals of the explorer autonomously without disturbing the original communication. This paper develops a collaborative wideband compressed signal detection approach for InterPlaNetary (IPN) Internet where there exist sparse active signals in the deep space environment. Compressed sensing (CS) can be utilized by exploiting the sparsity of IPN Internet communication signal, whose useful frequency support occupies only a small portion of an entirely wide spectrum. An estimate of the signal spectrum can be obtained by using reconstruction algorithms. Against deep space shadowing and channel fading, multiple satellites collaboratively sense and make a final decision according to certain fusion rule to gain spatial diversity. A couple of novel discrete cosine transform (DCT) and walsh-hadamard transform (WHT) based compressed spectrum detection methods are proposed which significantly improve the performance of spectrum recovery and signal detection. Finally, extensive simulation results are presented to show the effectiveness of our proposed collaborative scheme for signal detection in IPN Internet. Compared with the conventional discrete fourier transform (DFT) based method, our DCT and WHT based methods reduce computational complexity, decrease processing time, save energy and enhance probability of detection.

[1]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[2]  Geoffrey Ye Li,et al.  Cooperative Spectrum Sensing in Cognitive Radio, Part II: Multiuser Networks , 2007, IEEE Transactions on Wireless Communications.

[3]  Özgür B. Akan,et al.  InterPlaNetary Internet: state-of-the-art and research challenges , 2003, Comput. Networks.

[4]  Geoffrey Ye Li,et al.  Cooperative Spectrum Sensing in Cognitive Radio, Part I: Two User Networks , 2007, IEEE Transactions on Wireless Communications.

[5]  Georgios B. Giannakis,et al.  Compressed Sensing for Wideband Cognitive Radios , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[6]  Xiang Wang,et al.  Compressive wideband spectrum sensing based on single channel , 2015 .

[7]  Marvin K. Simon,et al.  Autonomous Software-Defined Radio Receivers for Deep Space Applications , 2006 .

[8]  Changxing Pei,et al.  Space-Time Bayesian Compressed Spectrum Sensing for Wideband Cognitive Radio Networks , 2010, 2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN).

[9]  Geert Leus,et al.  Distributed compressive wide-band spectrum sensing , 2009, 2009 Information Theory and Applications Workshop.

[10]  Emmanuel J. Candès,et al.  Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.

[11]  Joel A. Tropp,et al.  Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit , 2007, IEEE Transactions on Information Theory.

[12]  Kul B. Bhasin,et al.  Space Internet architectures and technologies for NASA enterprises , 2002, 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542).

[13]  Oswald Wallner,et al.  The drivers for future interplanetary communication and navigation , 2009, 2009 International Workshop on Satellite and Space Communications.

[14]  Zhi Tian,et al.  Compressed Wideband Sensing in Cooperative Cognitive Radio Networks , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[15]  Özgür B. Akan,et al.  The state of the art in interplanetary Internet , 2004, IEEE Communications Magazine.

[16]  Igor Bisio,et al.  Interplanetary Networks: Architectural Analysis, Technical Challenges and Solutions Overview , 2010, 2010 IEEE International Conference on Communications.

[17]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[18]  A. Ghasemi,et al.  Collaborative spectrum sensing for opportunistic access in fading environments , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[19]  Deanna Needell,et al.  CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, ArXiv.

[20]  E. Candès,et al.  Stable signal recovery from incomplete and inaccurate measurements , 2005, math/0503066.

[21]  Jon Hamkins,et al.  An Overview of the Architecture of an Autonomous Radio , 2004 .

[22]  Gregory W. Wornell,et al.  Cooperative diversity in wireless networks: Efficient protocols and outage behavior , 2004, IEEE Transactions on Information Theory.