## 1 Introduction
### Background and Motivation  
The key requirements for 5G technology include near-zero delay, high reliability, device support for heterogeneous networks, spectrum flexibility, and energy efficiency. Spectrum allocation is considered one of the major problems among the mentioned requirements [1; 9]. The static spectrum allocation policies are inefficient for meeting the ever-growing demand of spectrum resources, which are needed for high-speed wireless access in 5G cellular networks [10]. Radio resources have become increasingly scarce because of the static spectrum allocation approaches. The unlicensed users cannot access the licensed bands, making the bands under-utilized [6; 10]. Spectrum allocation flexibility and spectrum utilization efficiency can be achieved with different proposed technologies, such as LTE-WiFi aggregation (LWA) [11], operations in millimeter-wave band [12], LTE over the unlicensed band (LTE-U) [13], multicasting [14; 15], layer-division multiplexing [14; 16], ultra-dense small cells in  
Figure 1: Proposed multi-layer bands and usage scenarios for 5G. 5G architecture [17], non-orthogonal multiple access (NOMA) [18; 19; 20], and software-defined cognitive radio network (SD-CRN) [21; 22; 23; 24; 25]. LTE-U has emerged as an effective way to improve the spectral efficiency and capacity of wireless networks. Using LTE-U along with superior techniques such as carrier aggregation (CA), the performance of wireless networks can be improved significantly. However, an effective coexistence mechanism between LTE-U and Wi-Fi systems is necessary. Millimeter wave communications leverage the large-bandwidth potentially available at mmWave frequency band to provide the high data rates, and is considered to be a promising technology for the next-generation cellular networks. However, the performance evaluation of mmWave mobile communication systems, such as quantitative analysis of system-level propagation performance, and architecture evaluation need to be explored. Multicasting is a popular technique to simultaneously convey data to a group of terminals through point-to-multipoint communications, with positive impact on capacity and spectrum efficiency of the cellular systems. However, multicast traffic over 5G networks does not involve the end-user devices only, but also machine-type communications for IoT. In future broadcasting systems, layer-division multiplexing has been proposed to enable mobile TV on top of conventional terrestrial digital TV services, increasing the efficiency of the spectrum. In 5G systems, vehicular-to-everything (V2X) communications will also gain higher interest considering the ultra-dense and high-load scenarios. NOMA is one of the promising radio access techniques for performance enhancement and greater spectrum efficiency in 5G systems. In NOMA, multiple users are served at the same time and frequency, but are multiplexed based on the power or code domains. The integration of NOMA protocols with CR systems improves the spectral efficiency significantly. However, the performance analysis of a cooperative CR-NOMA schemes requires high computational complexity. Furthermore, in a possible radio-band assignment for 5G networks, different frequency bands will be used for macro cells and ultra-dense small cells. Such a 5G architecture will require intelligent spectrum sensing using CR technology to aggregate the spectrum bandwidths for small and large cells. The software-defined cognitive radio network (SD-CRN) is a promising technology to mitigate the spectrum scarcity and spectrum under-utilization issues in wireless systems. Enabling CR features in dense 5G networks can maximize the spectrum utilization. The users are generally categorized into a multi-tiered hierarchy in CR systems; primary users (PUs) have priority of spectrum access over the secondary users (SUs) [24]. Dynamic spectrum access techniques enable time-division multiple access (TDMA)-based spectrum sharing between the PUs and SUs, without requiring any major modifications in the primary systems [22; 23; 24].