Adaptive & Blind Equalization in Digital Optical Receivers using Constant Modulus Algorithm (CMA)

Adaptive & Blind Equalization in Digital Optical Receivers using Constant Modulus Algorithm (CMA)

Bandana MallickBibhu Prasad M. Bandyopadhyay N. Mandal S. Chattopadhyay 

Department of Electronics and Communication Engineering, Gandhi Institute of Engineering

Department of Electronics and Instrumentation Engineering, Gandhi Institute of Engineering

Department of Electrical Engineering, Asansol Engineering College, Asansol India

Department of Electronics Engineering, IIT(ISM) Dhanbad, India

Department of Electrical Engineering, National Institute of Technical Teachers’ Training and Research, Kolkata, India

Corresponding Author Email: 
bandana.mallick@gmail.com; bibhu.lect@gmail.com; mom_saltlake@yahoo.co.in; nirupama_cal@rediffmail.com; subrata0507@gmail.com
Page: 
113-121
|
DOI: 
https://doi.org/10.18280/ama_d.220108
Received: 
October 2017
|
Accepted: 
31 December 2017
|
Published: 
31 December 2017
| Citation

OPEN ACCESS

Abstract: 

In this work a high precision adaptive equalization method is proposed and analysed using constant modulus algorithm (CMA). It includes blindand adaptive equalization. This proposed algorithm is described and evaluated using quadrature phase shift keying (QPSK) transmission. The QPSK modulation in combination with frequency-domain constant modulus algorithm (CMA) method, which exhibits remarkable robustness to received signal. Complex-valued communication link utilizes new advanced algorithm for blind equalisation as constant module algorithm. The studied Digital Signal Processing algorithm is considered as important building blocks in digital coherent receivers for the future generation of optical communication systems. The simulated results are different in both based on bandwidth and side lobe suppression ratio.

Keywords: 

Adaptive equalizers, blind equalization, CMA equalizer, Constant modulus algorithm, Error measurement, QPSK.

1. Introduction
2. Blind Channel Equalization & CMA
3. Proposed Algorithm
4. Conclusion
  References

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