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OFDM for Underwater Acoustic Communications by Zhaohui Wang, Shengli Zhou

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Chapter 7Channel and Noise Variance Estimation

In this chapter, we focus on channel estimation within each received OFDM block. The underwater acoustic channel is well-known to consist of sparsely distributed propagation paths. Compared to the canonical least squares based method which estimates all the discretized channel samples within the channel delay spread, channel sparsity can be exploited to reduce the number of unknown parameters to estimate. This chapter treats sparse channel estimation for OFDM in both time-invariant and time-varying environments.

Sparse channel estimation has been underpinned by the striking development of compressive sensing theory in the last decade. To facilitate the development of sparse channel estimation in this chapter, the basics of compressive sensing are presented in Appendix A. The reader is encouraged to read this chapter and Appendix A in parallel for an in-depth understanding.

This chapter is organized as follows.

  • In Section 7.1, to exploit the sparsity of underwater acoustic channels, a dictionary based formulation of the system input–output relationship is developed. It subsumes the classical input–output relationship formulation for the least squares (LS) based channel estimation, yet allows channel parameterization with a limited number of measurements.
  • In Sections 7.2 and 7.3, building upon the dictionary-based formulation, an ICI-ignorant sparse channel estimator and an ICI-aware sparse channel estimator are derived for the single-input ...

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