Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results

Abstract

Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared to the social optimum, and demonstrate that the PoA is upper-bounded by 3/2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner's profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner.

GAN-Based Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

“…δ ξ ). Therefore, the training objective of Dirac-WGAN-GP is given by L(θ, ψ) = ψθ − ξψ (16) and the gradient penalty proposed in [35] is given by…”

Toward Operator-to-Waveform 5G Radio Access Network Slicing

“…The above discussion suggests that the RAN slicing problem has diverse and generally opposing requirements. Recent research work has suggested to let MNOs handle the slicing request generation and MU scheduling and transmission phases, while leaving the network slicing generation phase to the IP [14]. Conversely, the network slicing generation phase is left to the IP which possess the global network view required to implement fine-grained RB allocation [13].…”

“…Submission Interface (SI): the slicing requests generated by the Slice Request Generator block (Section III-C) are submitted to the IP through the SI. The design of the SI can rely upon web-based services [14] or client-based software with dedicated GUIs to facilitate the submission process [13].…”

“…As remarked earlier, it is important that this process is autonomously executed by each MNO, so that they can adapt their RAN slice to network changes and lower the computational burden on the IP. Moreover, by granting MNOs access to cumulative metrics such as overall network congestion, interference measurements and total amount of resources allocated to the RAN slice, it is possible to achieve distribute RAN slicing [14]. This eliminates the need for any coordination mechanism among MNOs and preserves their privacy.…”

Aggregated Resource Provisioning for Network Slices

“…This work borrows the slice resource provisioning approach introduced in [28], and adapts it to the joint radio and network infrastructure resource provisioning. Constraints related to the infrastructure network considered in [17,18,27,28] are combined with coverage and radio resource constraints introduced in [29,30,31,32].…”