Pilot Design for Sparse Channel Estimation in OFDM-Based Cognitive Radio Systems

Chenhao Qi*, Guosen Yue, Lenan Wu, Arumugam Nallanathan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

70 Citations (Scopus)


In this correspondence, sparse channel estimation is first introduced in orthogonal frequency-division multiplexing (OFDM)-based cognitive radio systems. Based on the results of spectrum sensing, the pilot design is studied by minimizing the coherence of the dictionary matrix used for sparse recovery. Then, it is formulated as an optimal column selection problem where a table is generated and the indexes of the selected columns of the table form a pilot pattern. A novel scheme using constrained cross-entropy optimization is proposed to obtain an optimized pilot pattern, where it is modeled as an independent Bernoulli random process. The updating rule for the probability of each active subcarrier selected as a pilot subcarrier is derived. A projection method is proposed so that the number of pilots during the optimization is fixed. Simulation results verify the effectiveness of the proposed scheme and show that it can achieve 11.5% improvement in spectrum efficiency with the same channel estimation performance compared with the least squares (LS) channel estimation.

Original languageEnglish
Article number6589017
Pages (from-to)982-987
Number of pages6
JournalIEEE Transactions on Vehicular Technology
Issue number2
Publication statusPublished - Feb 2014


  • Cognitive radio (CR)
  • compressed sensing (CS)
  • orthogonal frequency-division multiplexing (OFDM)
  • pilot design
  • sparse channel estimation


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