Empirical Likelihood-Based Channel Estimation with Laplacian Noise
This paper introduces a new method to estimate channel with Laplacian noise based on empirical likelihood algorithm. The received signal is assumed to be a transmitted signal which has been corrupted by a multipath channel, modeled as a FIR filter, the output being further disturbed by additive independent Laplacian noise. Then the channel estimation is treated as a nonparametric estimation issue in the model and the channel parameter is estimated by Empirical Likelihood approach. Furthermore, the MSE and BER performance of channel estimation are explored via numerical simulations.
KeywordsLaplacian noise Empirical likelihood Channel estimation
This work was supported by the National Natural Science Foundation of China (61271180), Major National Science and Technology Projects (2012zx03001022) and Special Foundation for State Internet of Things Program (Radio frequency and communication security testing service platform of Internet of things).
- 1.Proakis JG, Dimitris GM (1995) Digital communications, vol 3. McGraw-Hill, New YorkGoogle Scholar
- 2.Van Trees HL (2004) Detection, estimation, and modulation theory. Wiley, New YorkGoogle Scholar
- 3.Kassam SA (1989) Signal detection in non-Gaussian noise. Sringer, BerlinGoogle Scholar
- 11.Xu F (2009) An empirical likelihood scheme for signal detection in MIMO systems with nonlinear interference. Circuit Commun Syst. PACCS’09. Pacific-Asia conference on IEEE, 2009, pp 540–543Google Scholar
- 12.Xu F, Xu X, Zhang P (2007) Semiparametric theory based MIMO model and performance analysis. J China Univ Posts Telecomm 14(4):36–40Google Scholar