Intelligent reflecting surfaces for cognitive radio networks
by Raed Alhamad
International Journal of Ad Hoc and Ubiquitous Computing (IJAHUC), Vol. 42, No. 3, 2023

Abstract: In this paper, we derive the secondary throughput of cognitive radio networks with energy harvesting and adaptive transmit power. Intelligent reflecting surfaces (IRS) with N reflectors are deployed as a transmitter or a reflector so that all reflections are in phase at secondary destination. The analysis is performed in the absence or presence of interference from primary source. IRS with N = 128 reflectors offers 6, 12, 18, 24 dB gain with respect to N = 64, 32, 16, 8. When the number of reflectors is doubled, we obtain 6 dB gain in throughput. IRS allow 25, 31, 38 and 44 dB gain with respect to the absence of IRS for a number of reflectors N = 8, 16, 32, 64. IRS deployed as a transmitter improves the throughput by 1 dB with respect to IRS deployed as a reflector. We also consider the use of multiple antennas at the secondary destination and evaluate packets' waiting time and total delay.

Online publication date: Tue, 07-Mar-2023

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