BER and NCMSE based Estimation algorithms for Underwater Noisy Channels

Khalil Paracha, Fahad and Ahmed, Sheeraz and Arshad Jaleel, M. and Shahid, Hamza and Tayyab, Umais (2018) BER and NCMSE based Estimation algorithms for Underwater Noisy Channels. EAI Endorsed Transactions on Internet of Things, 3 (11): 3. ISSN 2414-1399

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Channel estimation and equalization of sparse multipath channels is a real matter of concern for researchers in the recent past. Such type of channel impulse response is depicted by a very few significant non-zero taps that are widely separated in time. A comprehensive comparison of few algorithms in this regard has been provided. The algorithms simulated are LS, LMS and MP while simulation results along with observations are also presented in this paper. The metrics used for performance evaluation are Bit error rate (BER) and Normalized channel mean square error (NCMSE). On the basis of obtained simulation results, it is observed that MP algorithm requires shorter training sequence for estimation of channel response at the receiver as compared with LS. Furthermore, it is observed that MP has best performance while LS and LMS stand after respectively.

Item Type: Article
Uncontrolled Keywords: Least Square, Matching Pursuit, Least Mean Square, Normalized Channel Mean Square error, Bit error rate, Additive white gaussian noise
Subjects: Q Science > QA Mathematics > QA76 Computer software
Depositing User: EAI Editor III.
Date Deposited: 22 Sep 2020 13:43
Last Modified: 22 Sep 2020 13:43

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