Research Article
An Eigenvalue Based Cooperative Spectrum Sensing for Multiuser MIMO Cognitive Radio Networks Under Correlated Fading Scenario
@INPROCEEDINGS{10.1007/978-3-030-98002-3_7, author={Abhishek Kumar and Rajarshi Bhattacharya and Seemanti Saha and Naveen Gupta}, title={An Eigenvalue Based Cooperative Spectrum Sensing for Multiuser MIMO Cognitive Radio Networks Under Correlated Fading Scenario}, proceedings={Cognitive Radio Oriented Wireless Networks and Wireless Internet. 16th EAI International Conference, CROWNCOM 2021, Virtual Event, December 11, 2021, and 14th EAI International Conference, WiCON 2021, Virtual Event, November 9, 2021, Proceedings}, proceedings_a={CROWNCOM \& WICON}, year={2022}, month={3}, keywords={Cognitive radio Cooperative spectrum sensing Multiple input multiple output Eigenvalue based detection}, doi={10.1007/978-3-030-98002-3_7} }- Abhishek Kumar
Rajarshi Bhattacharya
Seemanti Saha
Naveen Gupta
Year: 2022
An Eigenvalue Based Cooperative Spectrum Sensing for Multiuser MIMO Cognitive Radio Networks Under Correlated Fading Scenario
CROWNCOM & WICON
Springer
DOI: 10.1007/978-3-030-98002-3_7
Abstract
In this work, the performance of an eigenvalue-based cooperative spectrum sensing for multiuser multiple-input multiple-output (MIMO) cognitive radio networks is investigated under a correlated fading scenario. The secondary user (SU) is modeled as a MIMO system to detect the presence of primary user signal under incomplete channel state information (CSI) and Rayleigh faded channel model. At each SU, an energy detector is used to obtain the local decision statistic. Next, SU’s local decision is sent to the fusion center (FC) via numerous transmit antennas in order to get the transmitting diversity gain to combat the hidden node problem. Further, FC received the local decision statistic with multiple antennas under Racine faded correlated channel with perfect CSI. Finally, a global decision is made at FC based on an eigenvalue-based detection algorithm. The closed-form expression for the detection probabilities is derived at both SUs and FC. A simulation study shows that the target detection probability(P_d\ge 0.95)is achieved even at a very low signal to noise ratio value of(-5)dB.
