Cooperative spectrum sensing based on the limiting eigenvalue ratio distribution in Wishart matrices
IEEE Communications Letters
Eigenvalue-based spectrum sensing algorithms for cognitive radio
IEEE Transactions on Communications
A review on spectrum sensing for cognitive radio: challenges and solutions
EURASIP Journal on Advances in Signal Processing - Special issue on advanced signal processing for cognitive radio networks
Cyclostationary signatures in OFDM-based cognitive radios with cyclic delay diversity
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
A survey of spectrum sensing algorithms for cognitive radio applications
IEEE Communications Surveys & Tutorials
Spatial Capacity of Narrowband vs. Ultra-wideband Cognitive Radio Systems
IEEE Transactions on Wireless Communications - Part 2
Detect and avoid: an ultra-wideband/WiMAX coexistence mechanism [Topics in Radio Communications]
IEEE Communications Magazine
A survey on spectrum management in cognitive radio networks
IEEE Communications Magazine
Fast Primary User Detection during Ongoing Opportunistic Transmission in OFDM-based Cognitive Radio
Wireless Personal Communications: An International Journal
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Energy detection is a simple spectrum sensing technique that compares the energy in the received signal with a threshold to determine whether a primary user signal is present or not. Setting the threshold is very important to the performance of the spectrum sensing. This paper proposes an adaptive spectrum sensing algorithm where an optimal decision threshold of energy detection is derived based on minimizing the weighted sum of probabilities of detection and false alarm. Since the optimal decision threshold is dependent on the noise power and signal power, a simple, practical frequency domain approach is devised to estimate both. The algorithm can be used for the detection of various kinds of signals without any prior knowledge of the signal, channel or noise power, and is able to adapt to noise fluctuation. Simulations for detecting narrow-band and wideband signals (phase shift keying signal, frequency shift keying signal, orthogonal frequency division multiplexing signal) and ultra-wideband (UWB) signals (direct sequence spread spectrum signals) in an IEEE 802.15.3a UWB band are presented. The results show that the proposed algorithm has excellent robustness to noise uncertainty and outperforms the existing spectrum sensing algorithms in the literature.