Compressive estimation of UWA channels for OFDM transmission using iterative sparse reconstruction algorithms

Channel estimation is an important aspect in wireless communication, in which an estimate of the interference caused to the normal transmission is found, which is then cancelled to retrieve the original signal. In UnderWater Acoustic transmission, two main effects are delay spread and Doppler shift. It has been found[10] that while sampling in the delay - Doppler domain, the effect of the channel can be treated as sparse. Thus framing the estimation problem as an optimization problem of the form of a Basis Pursuit De Noising (BPDN)[21] and solving it using sparse reconstruction methods could be a good technique. In addition to giving good sparse solution, the technique also assures low computational complexity, (due to iterative nature of solution methodology) when compared to traditional estimation methods like Least Square Estimation (LSE) and Minimum Mean Square Error Estimation(MMSE).