## 2 Related Works  
Optimized Xhaul network planning is an important research topic in centralized and virtualized RANs. A fundamental design problem in this scope concerns the placement of radio processing resources (BBU/DU/CU) and the provisioning of connectivity between the RAN components. Most studies have focused on a BBU placement problem in centralized RAN (C-RAN) network scenarios based on dedicated fronthaul links established over an optical network between RRHs and a pool of BBUs [23; 24; 25; 26; 27]. The problem translates into the service chaining Virtual Network Function (VNF) placement problem if the BBU functions are split and virtualized [28]. The placement of the DU/CU in C-RANs connected using an optical transport network was studied in [29; 30; 31]. Dynamic scenarios concerning the allocation of the DU/CU and transmission resources with the Xhaul connectivity over a passive optical network (PON) were addressed in [32; 33]. The BBU/DU/CU placement/allocation optimization problems were modeled as MILP [23; 24; 25; 29] and nonlinear programming [33] problems, and solved using heuristic [27] and reinforcement learning-based algorithms [30; 31]. The mentioned problem was extended to the functional split selection (FSS) problem concerning the optimal choice of the split of BBU functions in [34; 35; 36; 37; 38]. The FSS problem was formulated as a Virtual Network Embedding (VNE) problem in [38] and solved using both the MILP [35; 36; 37; 38] and heuristic methods [38]. Apart from the resource-allocation problem, other issues were also addressed, including network survivability [26; 27] and energy efficiency [26; 36; 37]. A literature survey on related works was presented in [39]. Whereas the above works assume the use of dedicated fronthaul/midhaul links, usually established over an optical transport network, fewer studies have concerned packet-switched Xhaul transport networks. The authors of [40; 41] focused on the latency-awarerouting of FH flows over a packet-switched network. Two heuristics for the FSS problem with routing FH and BH flows in a convergent packet network, assuming a simplified latency model without buffering delays, were proposed in [42]. The planning of the DU and CU placement with latency-aware routing of Xhaul flows, with buffering latencies considered, was addressed in [20; 21; 22; 43], where both MILP models and heuristic algorithms were developed to solve related optimization problems. The Xhaul network optimization studies have also embraced the problem of network slicing. The authors of [11] discussed the challenges related to the end-to-end (E2E) provisioning of slices, focusing on E2E slice latency monitoring and management. In [44], the optimal allocation of radio resources for eMBB and URLLC slices was studied in the network scenario excluding the Xhaul transport domain. In [45], slice-aware optimization of the DU and CU placement was addressed, assuming fixed propagation latencies in the transport network. In [46], a MILP model was proposed for the problem of the joint selection of the optimal functional split and the routing path, between the connected user equipment to the CU while satisfying each service's SLAs. The authors of [47] formulated an integer linear programming (ILP) model for the problem of joint admission control and MEC/RAN slicing in 5G metropolitan networks under E2E service delay and resource constraints. A deep reinforcement learning-based method was proposed to solve this NP-hard problem. Few works focus on network slicing in packet-switched Xhaul networks. The authors of [15] presented experimental results obtained in a test bed of a TSN-aware Xhaul transport network supporting eMBB and URLLC slices, where latency guarantees were provided for URLLC. Recently, the impact of traffic priorities on the performance of a packet Xhaul network supporting eMBB and URLLC services was analyzed in [48]. To our knowledge, the modeling and optimization of network slicing in packet-switched Xhaul networks have not been addressed widely in the literature.