| Title | Sparse Code Multiple Access based Cooperative Spectrum Sensing in 5G Cognitive Radio Networks |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Shekhawat, G. K., Yadav, R. P. |
| Conference Name | 2020 5th International Conference on Computing, Communication and Security (ICCCS) |
| Date Published | oct |
| Keywords | 5G cognitive radio networks, 5G mobile communication, AWGN channel, AWGN channels, channel coding, cognitive feature spectrum sensing, Cognitive radio, composability, cooperative communication, cooperative spectrum sensing, Detectors, fading channels, fifth-generation network demands, future 5G networks, Log-MPA detector, Log-MPA iterative receiver based log-likelihood ratio soft test statistic, Metrics, multi-access systems, NOMA, Non Orthogonal Multiple Access (NOMA), pubcrawl, radio networks, radio spectrum management, Rayleigh channels, Rayleigh fading channel, Resiliency, SCMA, Sensors, Signal to noise ratio, sparse code multiple access scheme, spectrum efficiency, statistical testing, Testing, Wald-hypothesis test |
| Abstract | Fifth-generation (5G) network demands of higher data rate, massive user connectivity and large spectrum can be achieve using Sparse Code Multiple Access (SCMA) scheme. The integration of cognitive feature spectrum sensing with SCMA can enhance the spectrum efficiency in a heavily dense 5G wireless network. In this paper, we have investigated the primary user detection performance using SCMA in Centralized Cooperative Spectrum Sensing (CCSS). The developed model can support massive user connectivity, lower latency and higher spectrum utilization for future 5G networks. The simulation study is performed for AWGN and Rayleigh fading channel. Log-MPA iterative receiver based Log-Likelihood Ratio (LLR) soft test statistic is passed to Fusion Center (FC). The Wald-hypothesis test is used at FC to finalize the PU decision. |
| DOI | 10.1109/ICCCS49678.2020.9276888 |
| Citation Key | shekhawat_sparse_2020 |
Sparse Code Multiple Access based Cooperative Spectrum Sensing in 5G Cognitive Radio Networks