An introduction to signal detection and estimation (2nd ed.)
An introduction to signal detection and estimation (2nd ed.)
Principles of mobile communication (2nd ed.)
Principles of mobile communication (2nd ed.)
OFDM for Wireless Communications Systems
OFDM for Wireless Communications Systems
Introduction to Probability Models, Ninth Edition
Introduction to Probability Models, Ninth Edition
Cognitive Wireless Networks: Concepts, Methodologies and Visions Inspiring the Age of Enlightenment of Wireless Communications
QoS-constrained opportunistic scheduling for SC-FDMA with iterative multiuser detection
IEEE Communications Letters
Amplitude clipping and iterative reconstruction of MIMO-OFDM signals with optimum equalization
IEEE Transactions on Wireless Communications
Performance of single carrier transmission with cooperative diversity over fast fading channels
IEEE Transactions on Communications
Cognitive Radio: A Communications Engineering View
IEEE Wireless Communications
Cooperative Spectrum Sensing in Cognitive Radio, Part I: Two User Networks
IEEE Transactions on Wireless Communications
Spectrum sensing in cognitive radio networks: requirements, challenges and design trade-offs
IEEE Communications Magazine
Resource allocation for mitigating the effect of sensing errors in cognitive radio networks
IEEE Communications Letters
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Spectrum sensing is a key enabling technology of cognitive radio. Reliable detection increases access opportunity to temporarily unused bands and prevents harmful interference to the licensed users. Due to the receiver noise, signal attenuation, and multi-path fading effect, however, it is usually not possible to determine the existence of primary signal with absolute certainty. By extracting a global decision from shared local sensing results, cooperative sensing achieves high reliability over fading channels. In this paper, we assume that the traffic statistic of primary system is logged into the radio environment map (REM) and can be accessed by the secondary systems. The threshold of each energy detector is dynamically adapted according to the utility values and a priori information from REM. Then, decision results and corresponding operating points are collected by a fusion center, which makes a global decision with high confidence.