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Pilot Design Strategies for Block Sparse Channel Estimation in OFDM Systems

Affiliations

  • Department of Electronics and Communication Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalai Nagar, Chidambaram – 608002, Tamil Nadu, India

Abstract


Objectives: The objective functions for pilot design to minimize the inter-intra block coherence of sensing matrix. The efficient pilot design strategies was considered for the recovery of block sparse channel in pilot aided Orthogonal Frequency Division Multiplexing (OFDM) system using Compressive Sensing (CS) technique Methods: In particular, the pilot design directly influences the construction of sensing matrix in CS Frame work. This paper examines design measure of pilots based on minimizing a weighted sum of the inter and intra block coherence of the equivalent sensing matrix to improve block sparse channel estimation using block sparse CS algorithms. Findings: The multi carrier modulation, OFDM can achieve its benefits over multipath fading channel if Channel coefficients are perfectly estimated at the receiver. Block sparse with varying block size is prevalent in wideband frequency selective channel due to the presence of reflectors in the transmission. The explicit use of channel block sparsity and proper construction of sensing matrix for CS block sparse recovery algorithms yields better reconstruction performance. Applications: The proposed measure of pilot in sensing matrix design for varying block size of block sparse channel significantly outperforms the common inter block coherence along with CS based block sparse recovery algorithm.

Keywords

Channel Estimation, Compressive Sensing, Inter Block Coherence, Intra Block Coherence, Pilot Design

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References


  • Coleri S, Ergen M, Puri A, Bahai A. Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems.IEEE Transactions on Broadcasting. 2002 Oct; 48(3):223–9. Crossref
  • Ma TM, Shi YS, Wang YG. A Low Complexity MMSE for OFDM Systems over Frequency-Selective Fading Channels. IEEE Communications Letters. 2012 Mar; 16(3):304–6. Crossref
  • Ozdemir MK, Arslan H. Channel Estimation for Wireless OFDM Systems. IEEE Communications Surveys & Tutorials.IEEE Press Piscataway, NJ, USA. 2007 Apr; 9(2):18–48.
  • Sho YS, Kim J, Yang WY, Kang CGU. MIMO-OFDM Wireless Communication with MATLAB. John Wiley and Sons Pvt. Ltd; 2010.
  • Donoho D. Compressed Sensing. IEEE Transaction Information Theory. 2006 Apr; 52(4):1289–306. Crossref
  • Candes EJ, Wakin MB. An Introduction to Compressive Sampling. IEEE Signal Processing Magazine. 2008 Mar; 25(2): 21–30. Crossref
  • Tropp JA, Gilbert AC. Signal Recovery from Random Measurements via Orthogonal Matching Pursuit.
  • IEEE Transactions on Information Theory. 2007 Dec; 53(12):4655–66. Crossref
  • Ganesh A, Zhou Z, Ma Y. Separation of a Subspace Signal: Algorithms and Conditions. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP); 2009 Apr19-24; Taipei, Taiwan.
  • Qi C, Wu L. A Hybrid Compressed Sensing Algorithm for Sparse Channel Estimation in MIMO OFDM systems.
  • , 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP); 2011 May 22-27.
  • Crossref
  • Gowda NM, Kannu AP. Interferer Identification in HetNets using Compressive Sensing Framework.
  • IEEE Transactions on Communications. 2013 Nov; 61(11):4780–7. Crossref
  • Baraniuk R, Davenport M, Devore R, Wakin M. A Simple Proof of the Restricted Isometry Property for Random Matrices. Constructive Approximation. 2008 Dec; 28(3):253–63. Crossref
  • Candes EJ. The Restricted Isometry Property and its Implications for Compressed Sensing. Comptes Rendus Mathematique. 2008 May; 346(9-10):589–92. Crossref
  • Stojnic M, Parvaresh F, Hassibi B. Reconstruction of BlockSparse Signals with an Optimal Number of Measurements.IEEE Transactions on Signal Processing. 2009 Aug; 57(8):3075–85. Crossref
  • Eldar YC, Kuppinger P, Boolcskei H. Block-Sparse Signals: Uncertainity Relations and Efficient recovery. IEEE Transaction on Signal Processing. 2010 Jun; 58(6):3042–54.Crossref
  • Qi C, Yue G, Wu SL, Huang Y, Nallanathan A. Pilot Design Schemes for Sparse Channel Estimation in OFDM Systems. IEEE Transactions on Vehicular Technology. 2015 Apr; 64(4):1493–505. Crossref

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