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Modulation Identifier for Software Defined Radios


Affiliations
1 St.Peter's University, Chennai-54, India
2 Electronics and Communication Department, Dr. MGR Educational and Research Institute, University, Chennai, India
3 MicroLogic Systems, Chennai, India
     

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Software Defined Radios (SDR) is integrated with dynamically configurable software to enable Cognitive Radio (CR) design. Higher Channel densities management and continuous service provision are the performance measures for SDR. Incorporating adaptive modulation capability in sophisticated wireless communication techniques necessitates an Automatic Modulation Recognition for SDR. The abundant demodulation requisite for SDR is not catered sufficiently by available Automatic Modulation Recognition techniques. This paper deals with a novel method of automatic modulation identification for Software defined radio. The proposed technique uses a simple method of appending a unique pilot sequence to each modulated data for identification purpose. This work analyzes the performance of the identifier for typical modulations under noisy conditions and at different Signal to Noise Ratios (SNRs). A pre-processing module is also adapted in the modulation identification technique and performs rejection of noise, normalization, carrier frequency estimation and recovery of complex envelope.

Keywords

Software Defined Radio (SDR), Cognitive Radio (CR), Signal to Noise Ratio (SNR).
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  • Modulation Identifier for Software Defined Radios

Abstract Views: 232  |  PDF Views: 2

Authors

K. Senthamil Selvan
St.Peter's University, Chennai-54, India
S. Ravi
Electronics and Communication Department, Dr. MGR Educational and Research Institute, University, Chennai, India
B. LakshmiDhevi
MicroLogic Systems, Chennai, India

Abstract


Software Defined Radios (SDR) is integrated with dynamically configurable software to enable Cognitive Radio (CR) design. Higher Channel densities management and continuous service provision are the performance measures for SDR. Incorporating adaptive modulation capability in sophisticated wireless communication techniques necessitates an Automatic Modulation Recognition for SDR. The abundant demodulation requisite for SDR is not catered sufficiently by available Automatic Modulation Recognition techniques. This paper deals with a novel method of automatic modulation identification for Software defined radio. The proposed technique uses a simple method of appending a unique pilot sequence to each modulated data for identification purpose. This work analyzes the performance of the identifier for typical modulations under noisy conditions and at different Signal to Noise Ratios (SNRs). A pre-processing module is also adapted in the modulation identification technique and performs rejection of noise, normalization, carrier frequency estimation and recovery of complex envelope.

Keywords


Software Defined Radio (SDR), Cognitive Radio (CR), Signal to Noise Ratio (SNR).