Cost-Reward-based Carrier Aggregation with Differentiating Network Slicing for Optimizing Radio RB Allocation in 5G New Radio Network
Ben‐Jye Chang, Wei-Teng Chang · 2019
In 5G cellular network, to achieve an extremely high data rate and Ultra Reliable Low Latency Communication (uRLLC) by using a limited radio frequency spectrum bands becomes a big challenge. 5G thus specifies the technologies of Carrier Aggregation (CA) and Network Function Virtualization (NFV) to increase the frequency spectrum efficiency and to dynamically allocate the virtualized network component for different classes of network slicing, respectively. CA can aggregate multiple contiguous or non-contiguous Component Carriers (CCs) and to improve frequency spectrum utilization and signal quality. In 5G NR, NFV can dynamically allocate network virtual radio resource for different classes of network slicing, e.g., emergency, uRLLC for Vehicle-to-Everything (V2X), Internet of Vehicles (IoVs), e.g., Autonomous Self Driving Vehicle, Advanced Driving Assistant System, mMTC for sensing-based Internet of Things (IoTs), etc. However, different SINRs of different frequency spectrum bands suffer from the exiting radio nature of CCs. The CA effect and system capacity are thus limited obviously. This paper thus proposes the Cross-Layer NR scheduling with CC Aggregation (CLCA) in 5G NR network. CLCA contributes several algorithms: 1) Markov Decision Process-based cost reward Packet Selection (MDP-PS), 2) Adaptive Packet Scheduling (APS) and 3) Adaptive Component Carrier scheduling (ACC). Numerical results show CLCA outperforms the compared approaches in system capacity, network reward and packet failure rate.