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Wireless Networks

, Volume 25, Issue 2, pp 699–712 | Cite as

Joint signal detection and synchronization for OFDM based cognitive radio networks and its implementation

  • Manish KumarEmail author
  • Sudhan Majhi
Article
  • 146 Downloads

Abstract

In the cooperative cognitive radio networks (CRN), often secondary user (SU) relays the information of primary user (PU) as a rewarding relay to improve diversity gain of PU without being a legitimate user. So the SU needs to detect the signal, blindly estimate the parameters introduced in channel and reconstruct the signal before relaying it to the primary receiver. In this paper, a joint scheme for signal detection and non-data-aided (blind) parameter estimation of orthogonal frequency division multiplexing (OFDM) based CRN has been discussed. Based upon binary hypothesis testing problem, the SU formulates a minimum cost signal detection scheme for the presence of OFDM based PU signal in CRN. The probability of detection, probability of false alarm and receiver operating characteristics have been presented to illustrate the performance of signal detection scheme in the CRN. Further, the effective throughput analysis of the secondary system has been demonstrated in the context when the primary system is detected as idle. Blind synchronous parameters of OFDM signal such as carrier frequency offset and symbol timing offset has been presented over the wireless fading channel in the CRN. Existing theoretical studies on blind parameter estimation algorithms for signals have been carried out but most of them have not been implemented in order to validate their feasibility. Here, a software-defined radio testbed has been implemented using national instruments hardware in a multipath indoor environment and experimental results have been provided using real measurement system. The preliminary measurement and simulation results demonstrate that the proposed blind estimator is capable of estimating the concerned parameters and constellation symbols over an indoor propagation environment.

Keywords

Cognitive radio network Detection and estimation Orthogonal frequency division multiplexing Blind parameter estimation Software-defined radio 

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of Electrical EngineeringIndian Institute of TechnologyPatnaIndia

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