Joint optimization of cooperative spectrum sensing and resource allocation in multi-channel cognitive radio sensor networks

N Zhao - Circuits, Systems, and Signal Processing, 2016 - Springer
Cooperative spectrum sensing (CSS) that utilizes multi-user diversity to mitigate channel
instability and noise uncertainty is a promising technique in cognitive radio networks …

Joint Optimization of Cooperative Spectrum Sensing and Resource Allocation in Multi-channel Cognitive Radio Sensor Networks

N Zhao - Circuits, Systems, and Signal Processing, 2016 - dl.acm.org
Cooperative spectrum sensing (CSS) that utilizes multi-user diversity to mitigate channel
instability and noise uncertainty is a promising technique in cognitive radio networks …

Joint Optimization of Cooperative Spectrum Sensing and Resource Allocation in Multi-channel Cognitive Radio Sensor Networks.

N Zhao - Circuits, Systems & Signal Processing, 2016 - search.ebscohost.com
Cooperative spectrum sensing (CSS) that utilizes multi-user diversity to mitigate channel
instability and noise uncertainty is a promising technique in cognitive radio networks …

Joint Optimization of Cooperative Spectrum Sensing and Resource Allocation in Multi-channel Cognitive Radio Sensor Networks

N Zhao - Circuits, Systems, and Signal Processing, 2016 - infona.pl
Cooperative spectrum sensing (CSS) that utilizes multi-user diversity to mitigate channel
instability and noise uncertainty is a promising technique in cognitive radio networks …

Joint Optimization of Cooperative Spectrum Sensing and Resource Allocation in Multi-channel Cognitive Radio Sensor Networks

N Zhao - Circuits, Systems, and Signal Processing, 2016 - search.proquest.com
Cooperative spectrum sensing (CSS) that utilizes multi-user diversity to mitigate channel
instability and noise uncertainty is a promising technique in cognitive radio networks …

[引用][C] Joint Optimization of Cooperative Spectrum Sensing and Resource Allocation in Multi-channel Cognitive Radio Sensor Networks

N Zhao - Circuits, systems, and signal processing, 2016 - Springer