IEEE communications letters, 2020-08, Vol.24 (8), p.1812-1815
2020
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- Autor(en) / Beteiligte
- Titel
- Fast Blind Equalization Using Bounded Non-Linear Function With Non-Gaussian Noise
- Ist Teil von
- IEEE communications letters, 2020-08, Vol.24 (8), p.1812-1815
- Ort / Verlag
- New York: IEEE
- Erscheinungsjahr
- 2020
- Quelle
- IEEE/IET Electronic Library (IEL)
- Beschreibungen/Notizen
- Blind equalization is widely utilized to eliminate inter-symbol interference in communication system. It is still a challenge to support blind equalization method within non-Gaussian noise environments. Aiming at improving its convergence speed and robustness performance, in this letter, a novel fast blind equalization method is proposed by using bounded nonlinear function (BNF) and quasi-Newton method. Firstly, BNF-based cost function is proposed to effectively eliminate non-Gaussian noise and realize equalization. Next, quasi-Newton method is developed as the iteration method, which can accelerate the convergence speed. Moreover, theoretical analysis is provided to illustrate that the proposed algorithm has a robust convergence performance. Simulation results show that the proposed method enables evident performance improvement in terms of convergence speed and robustness with non-Gaussian noise.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 1089-7798eISSN: 1558-2558DOI: 10.1109/LCOMM.2020.2991046Titel-ID: cdi_proquest_journals_2434120733
- Format
- –
- Schlagworte
- Acceleration, Algorithms, Blind equalization, Blind equalizers, bounded nonlinear function (BNF), Communications systems, Computer simulation, Convergence, Cost function, Equalization, Gaussian elimination, Gaussian noise, Interference, Linear functions, Noise, non-Gaussian noise, Quasi Newton methods, quasi-Newton, Random noise, Robustness, Simulation