Interference Minimization in 5G Physical-Layer Network Slicing

Abstract

The interference resulting from densification of access points and the coexistence of different numerologies within the same spectrum severely hinders inter-slice isolation. We propose a slice allocation policy that enforces inter-slice isolation by minimizing the inter-slice interference suffered by each virtual operator. In detail, we design a binary quadratic non-convex optimization problem that minimizes i) the interslice interference generated by interfering base stations and ii) the inter-slice interference generated by the multiplexing of spectrum slices having different numerologies. We also provide a heuristic algorithm to render the solution scalable in practical scenarios. We assess the performance of both approaches by evaluating the signal-to-interference-plus-noise ratio (SINR) associated to each slice through simulations. Results reveal that the heuristic algorithm provides a solution comparable with the optimal one on different minimization scenarios. Moreover, a considerable SINR improvement is observed with respect to a base-line scheme that does not account for inter-slice interference.

LACO: A Latency-Driven Network Slicing Orchestration in Beyond-5G Networks

“…This renders a maximum capacity of ∼ 36 Mb/s with highest SNR. Finally, in accordance with the findings 12 USRP B210 from National Instruments/Ettus Research (https://www. ettus.com/all-products/UB210-KIT/).…”

“…Hence, we define the probability to improve the user channel condition from level g to level g + 1 as p g,g+1 whereas the probability to get a bad channel from level g to level g − 1 as q g,g−1 . As shown in recent works like [12], [13], 6 This assumption can be readily relaxed by considering the convolution of single cumulative distribution functions of every user channel and demand variation [10]. 7 The time scale t of DTMC state switch is much shorter than the decision epoch n used in the MDP described in Section V. 8 Each DTMC is defined within a state space S i .…”

“…In order to illustrate, validate and analyze the performance of our LACO solution, we developed it as a standalone software module running on top of an open source platform that implements the LTE protocol stack, namely srsLTE [23], attached to a USRP 12 Software-Defined Radio (SDR) device as radio front-end. Our testbed is depicted in Fig.…”

An intelligent self-sustained RAN slicing framework for diverse service provisioning in 5G-beyond and 6G networks

“…Furthermore, the network-wide observation of network normally has obvious change on a long-term timescale (in the level of seconds) [25] . SDN controller should adapt the configuration of network slices on a long-term timescale, which can also lower signaling overhead and computation burden [26] . The network-level control decides the network resource assignment among gNodeBs, which includes the following:…”

“…Here, PRBs will be partially reused among gNodeBs to exploit multiplexing gain. Specifically, a set of orthogonal PRBs are assigned to gNodeBs with close distance, and PRB reuse will take place among gNodeBs with far distance, which can mitigate inter-cell interference [26] . Secondly, the bandwidth of front/ backhaul links is also determined by the network-level control policy N [27] .…”