The growth of modern communication systems into 5G deployments has incorporated the ultra-dense network (UDN) concept to provide high-throughput user-centric wireless access. Cognitive Radio (CR) can facilitate the integration of UDNs with legacy systems without the immediate need for allocation of new spectrum which would lead to substantial increase in cost. Thus, the CR-based UDN requires efficient spectrum sensing to correctly identify the unutilized frequency bands. This simulation study emphasizes the strengths and limitations of the most popular algorithm of this kind, energy detection (ED). It is implemented in cognitive access points (CAPs) of an UDN, which determine the spectrum occupancy and allocate the available resource to their mobile users. The applicability of ED-based spectrum sensing is assessed via the primary system’s signal-to-noise ratio (SNR) distribution as measured by the CAPs, and the probability of detection. A prominent probabilistic signal propagation model for communications in UDNs is applied. In addition, the CR-based UDN’s potential throughput gains are evaluated in terms of the CAPs’ deployment density. The performance metrics are estimated via extensive simulations.

• Antoni Ivanov
• Viktor Stoynov
• Dimitriya Mihaylova
• Vladimir Poulkov

AIP Conference Proceedings, Volume 2570

https://aip.scitation.org/doi/abs/10.1063/5.0099506