Enhanced Radio Access Procedure in Sliced 5G Networks In this paper, we introduce the concept of Random Access Channel (RACH) resource slicing and investigate the performance of a sliced Radio Access Network (RAN). We consider three generic service types that the fifthgeneration (5G) wireless technology is claimed to support, and refer to them as enhanced mobile broadband (eMBB), massive machinetype communications (mMTC), and ultrareliable low latency communications (URLLC) slices. Each slice can be configured with dedicated and shared subsets of RAN and RACH resources, also known as RACH preambles. We propose an analytic framework that allows us to obtain the blocking probability of each slice in a closedform. We compare different resource allocation policies in sliced radio access system and investigate their impact on a slice performance.

Slicing Resource Allocation for eMBB and URLLC in 5G RAN This paper investigates the network slicing in the virtualized wireless network. We consider a downlink orthogonal frequency division multiple access system in which physical resources of base stations are virtualized and divided into enhanced mobile broadband (eMBB) and ultrareliable low latency communication (URLLC) slices. We take the network slicing technology to solve the problems of network spectral efficiency and URLLC reliability. A mixedinteger programming problem is formulated by maximizing the spectral efficiency of the system in the constraint of usersxe2x80x99 requirements for two slices, i.e., the requirement of the eMBB slice and the requirement of the URLLC slice with a high probability for each user. By transforming and relaxing integer variables, the original problem is approximated to a convex optimization problem. Then, we combine the objective function and the constraint conditions through dual variables to form an augmented Lagrangian function, and the optimal solution of this function is the upper bound of the original problem. In addition, we propose a resource allocation algorithm that allocates the network slicing by applying the Powellxe2x80x93Hestenesxe2x80x93Rockafellar method and the branch and bound method, obtaining the optimal solution. The simulation results show that the proposed resource allocation algorithm can significantly improve the spectral efficiency of the system and URLLC reliability, compared with the adaptive particle swarm optimization (APSO), the equal power allocation (EPA), and the equal subcarrier allocation (ESA) algorithm. Furthermore, we analyze the spectral efficiency of the proposed algorithm with the usersxe2x80x99 requirements change of two slices and get better spectral efficiency performance.