• Corpus ID: 51781214

Hardware-Efficient and Reconfigurable VLSI Architectures & Techniques for Spectrum Sensing in Cognitive Radio Wireless Networks

  title={Hardware-Efficient and Reconfigurable VLSI Architectures \& Techniques for Spectrum Sensing in Cognitive Radio Wireless Networks},
  author={Mahesh S. Murty and Rahul Shrestha},
Wireless communication has expanded its horizon in almost every aspect of human lives and its consequence is rapid surge in the demand of spectral resource. Electromagnetic spectrum is a gift of nature and such spectrum bands cannot be increased beyond certain limit. Presently, spectrum is licensed by government agencies to the interested parties by accepting a license fee. At the time of allocation, it is assumed that the licensed party will be utilizing the spectrum up-to its full potential i… 


Multi-mode, multi-band spectrum sensor for cognitive radios embedded to a mobile phone
An mobile device scale implementation of multi-mode, multi-band spectrum sensor for cognitive radio, utilized to detect digital television on UHF band and IEEE802.11a/g on 2.4/5 GHz (ISM/WLAN) bands is described.
VLSI Architecture for Cyclostationary Feature Detection Based Spectrum Sensing for Cognitive-Radio Wireless Networks and Its ASIC Implementation
This work deals with the very-large scale integration VLSI architectural transformation of cyclostationary feature detection for spectrum sensing in cognitive radio network for field-programmable gate-array prototyping and application-specific integrated-circuit (ASIC) design.
Collaborative autocorrelation-based spectrum Sensing of OFDM signals in cognitive radios
A detector exploiting the well-known autocorrelation property of cyclic prefix based OFDM signals is developed and the proposed scheme is extended to the case of many secondary users collaborating in order to detect the primary user in the face of shadowing and fading.
A CMOS Spectrum Sensor Based on Quasi-Cyclostationary Feature Detection for Cognitive Radios
A quasi-cyclostationary feature (QCF) detector is proposed based on both energy and feature detection methods and can take advantage of both methods to reach a fast and accurate decision without the need for an analog-to-digital converter for decision making.
FPGA implementation of spectrum sensing based on energy detection for Cognitive Radio
  • S. Srinu, S. L. Sabat
  • Computer Science
  • 2010
Energy detection technique based on Neyman-pearson criterion is used to detect the presence of deterministic primary user signals in the channel and it is revealed that the algorithm fits into the Virtex2pro FPGA and can execute with operating frequency between 110 to 138 MHz for different sample size ofPrimary user signals.
Spectrum Sensing in Cognitive Radios Based on Multiple Cyclic Frequencies
A generalized likelihood ratio test (GLRT) for detecting the presence of cyclostationarity using multiple cyclic frequencies is proposed and distributed decision making is employed by combining the quantized local test statistics from many secondary users.
Spectrum sensing for cognitive radios: Algorithms, performance, and limitations
Main aim in studying the effects of quantization and channel errors on the cooperative sensing is to provide a framework for the designers to choose the operating values of the number of quantized bits and the target bit error probability for the reporting channel such that the performance loss caused by these non-idealities is negligible.
A Wavelet Approach to Wideband Spectrum Sensing for Cognitive Radios
  • Z. Tian, G. Giannakis
  • Business
    2006 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications
  • 2006
A wavelet approach to efficient spectrum sensing of wideband channels based on the local maxima of the wavelet transform modulus and the multi-scale wavelet products is developed.
Cognition in Wireless Sensor Networks: A Perspective
The main contribution of this paper is providing the vision and advantage of a holistic approach to cognition in sensor networks, which can be achieved by incorporating learning and reasoning in the upper layers, and opportunistic spectrum access at the physical layer.
Matched Filter Based Spectrum Sensing on Cognitive Radio for OFDM WLANs
Such unused spectrum for OFDM WLAN (IEEE 802.11a) is predicted by exploring the signals presence in minimum time using matched filter based detection incorporating optimal threshold selection, thereby increasing the sensing accuracy and interference reduction of secondary network.