Heterogeneous Statistical QoS Provisioning for Full-Duplex D2D Communications over 5G Wireless Networks

The fifth-generation (5G) communications and wireless networks, which are expected as the next new era of wireless networks, have received much research attention in recent years. The academic and industrial researchers have developed a great deal of 5G candidate techniques to improve the performance of 5G wireless networks, where the most important two metrics are the spectrum efficiency and the quality-of-service (QoS). Jointly using full-duplex (FD) wireless communications and device- to-device (D2D) communications, forming the FD-D2D communications, can significantly increase the spectrum efficiency of 5G wireless networks in frequency/time/space-domains. On the other hand, not only increasing the spectrum efficiency, but also supporting QoS guarantees is very important for 5G wireless networks. However, supporting QoS guarantees for FD-D2D communications imposes the new challenges that we need to provide heterogeneous QoS guarantees for different types of traffics over the same link simultaneously. To overcome the aforementioned problems, in this paper we propose the heterogeneous statistical QoS provisioning framework for FD-D2D communications over 5G wireless networks. In particular, we formulate the optimization problems to maximize the system throughput subject to heterogeneous statistical delay-bound QoS requirements. Then, we convert the resulted non- convex optimization problem into an equivalent convex optimization problem, solving which we can derive the optimal heterogeneous-QoS-driven power allocation scheme to maximize the system throughput while guaranteeing the heterogeneous statistical delay-bound QoS requirements. The extensive simulation results obtained show that our proposed heterogeneous-QoS-driven power allocation scheme can significantly increase the system throughput while guaranteeing heterogeneous statistical delay-bound QoS requirements.