Recent papers on wideband spectrum sensing for cognitive radio sytems
A Class of Spectrum-Sensing Schemes for Cognitive Radio Under Impulsive Noise Circumstances: Structure and Performance in Nonfading and Fading Environments, by HG Kang, I Song, S Yoon, YH Kim. This paper exploits a nonlinear diversity-combining strategy together with the generalized likelihood ratio test detectors on each of the antenna branches.
A Parallel Cooperative Spectrum Sensing in Cognitive Radio Networks. In this work S. Xie, Y. Liu, Y. Zhang and R. Yu propose a sensing scheme in which several secondary users are selected to perform sensing in different channels. They present an analytical model to investigate the tradeoff between the transmitted data and the sensing overhead, which results into a throughput maximization problem.
Multiantenna spectrum sensing: The case of wideband rank-one primary signals. In this work D Ramırez, J Via and I Santamaria derive multiantenna detector based on the asymptotic likelihood under the asumptions of a wideband rank-one signal under spatially uncorrelated noise with equal or different power spectral densities.
Distributed Compressive Spectrum Sensing in Cooperative Multihop Cognitive Networks. In this paper F Zeng, C Li, Z Tian present a cooperative approach to wideband spectrum sensing. Their scheme utilizes a compressive sampling mechanism which exploits the signal sparsity induced by network spectrum under-utilization by enforcing consensus among local spectral estimates.
A Wideband Spectrum Sensing Method for Cognitive Radio using Sub-Nyquist Sampling. In this preprint M Rashidi, K Haghighi, A Owrang and M Viberg present a wideband spectrum sensing scheme that utilizes a sub-Nyquist sampling in order to reconstruct the correlation matrix. This method does not require the knowledge of signal properties mitigating the uncertainty problem. Also by Moslem Rashidi is this long preprint (maybe a book chapter?): Non-uniform sampling and reconstruction of multi-band signals and its application in wideband spectrum sensing of cognitive radio. It may be an useful introduction to the topic.
On the use of Compressive Sampling for Wide-band Spectrum Sensing by D. Sundman, S. Chatterjee and M. Skoglund. For wideband signals sampling at the Nyquist rate is a major challenge. In this work they propose a wideband detection scheme of multiple simultaneous signals using sub-Nyquist sampling rates. This work is extended to incorporate memory from previous slots in slow varying scenarios.
Evidence Theory Based Cooperative Spectrum Sensing with Efficient Quantization Method in Cognitive Radio. In this work N. Nguyen-Thanh and I. Koo study an enhanced scheme for cooperative spectrum sensing based on efficient quantization and the Dempster-Shafer Theory of Evidence. They propose an effective quantizer for the sensing data which takes advantage of special properties of the statistic distribution for different signal-to-noise ratios of the primary signal, hence reducing the required bandwidth for the reporting channel occupancy.
Adaptive Spectrum Sensing and learning in Cognitive Radio Networks by A. Taherpour, S. Gazor and A. Taherpour. This paper proposes an iterative primary user activity detection algorithm for a wideband frequency range using a Markov Model (MM) with two states to model the activity of the primary users.
If you know any additional paper related to wideband sensing which has been recently published you can leave a comment with the link.