Abstract
We expect that 5G will support a large volume of data traffic to provide various services with a low latency. This will inevitably require an increased amount of energy. Wireless power transfer needs a higher receiver sensitivity than data decoding. Increased electromagnetic fields may introduce harmful effects on living organisms. Fortunately, massive multiple-input and multiple-output (MIMO) can provide significant gains in radiated energy and spectral efficiencies. Cognitive radio and 5G are emerging technologies. In this paper, we show that cognitive spectrum sensing and power harvesting can be accomplished simultaneously. Energy detection (ED) with energy harvesting has been widely investigated. However, ED may not work at a low signal-to-noise ratio with a harsh signal fluctuation in millimeter-wave in 5G. Therefore, we focus on cyclostationary spectrum sensing in this paper. We show that the maximum likelihood cyclostationary detection that can be used for power harvesting is the power squared. The cyclic power can be conveniently harvested and used for spectrum sensing.
Highlights
Dvices in the 5G Internet of Things (IoT) consume a large amount of energy
It is observed that a larger peakto-average power ratio (PAPR) can exercise a positive influence on power harvesting with cyclostationary spectrum sensing in cognitive radios
We developed the maximum likelihood (ML) detection output of cyclostationary detection and showed that the result is equal to the power squared
Summary
Dvices in the 5G Internet of Things (IoT) consume a large amount of energy. there have been many efforts to create power management policies, the sensor nodes’ lifetimes still remain a performance bottleneck and make the wide-range deployment of IoT challenging [1], [2]. A simultaneous cooperative spectrum sensing and EH model was proposed to improve the transmission performance of the multichannel cognitive radio in [10]. Jang: Simultaneous Power Harvesting and Cyclostationary Spectrum Sensing in CRs are optimized to maximize the cognitive sensor’s throughput and improve the utilization efficiency of the harvested energy. To ameliorate the negative EMF effects of 5G and to avoid WPT, we will show that cognitive spectrum sensing and power harvesting can be made simultaneously. The main contribution of our research is to show that the ML detection output of cyclostationary spectrum sensing can be used for power harvesting.
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