Cognitive Radio Networks Using Intelligent Reflecting Surfaces

Abstract

In this article, we optimize harvesting and sensing duration for Cognitive Radio Networks (CRN) using Intelligent Reflecting Surfaces (IRS). The secondary source harvests energy using the received signal from node A. Then, it performs spectrum sensing to detect Primary Source PS activity. When PS activity is not detected, The Secondary Source SS transmits data to Secondary Destination SD where all reflected signals on IRS are in phase at SD. We show that IRS offers 14, 20, 26, 32, 38, 44, 50 dB enhancement in throughput using M = 8, 16, 32, 64, 128, 256, 512 reflectors with respect to CRN without IRS. We also suggested to add a second IRS between A and SS to increase the harvested energy. The use of 2 IRS with M1 = 8 reflectors in the first IRS and M2 = 8 reflectors in the second IRS offers 18 dB gain (respectively 32 dB) gain with respect to a single IRS with M2 = 8 reflectors (respectively without IRS). The use of 2 IRS with M1 = 16 reflectors in the first IRS and M2 = 8 reflectors in the second IRS offers 28 dB gain (respectively 42 dB) gain with respect to a single IRS with M2 = 8 reflectors (respectively without IRS). Our results are valid for Nakagami channels of fading figure m. We also provide the throughput of IRS with energy harvesting. We have studied packet waiting time and total delay in the presence and absence or IRS. At Signal to Noise Ratio (SNR) per bit equal to 0 dB, packet waiting time is 0.9 ms when there is no IRS and 0.5 ms when there is an IRS with M = 8 reflector. At SNR per bit equal to 0 dB, total transmission delay is 54 ms when there is no IRS and 1.5 ms when there is an IRS with M = 8 reflectors. We show that the energy efficiency is larger when both harvesting and sensing durations are optimized. The maximum of energy efficiency is 260 Mbit/s/Hz/J when harvesting and sensing durations are optimized while the maximum is 80 Mbit/s/Hz/J when harvesting and sensing durations are not optimized.