Optimal Traffic Splitting Policy in LTE-based Heterogeneous Network

Dual Connectivity (DC) is a technique proposed to address the problem of increased handovers in heterogeneous networks. In DC, a foreground User Equipment (UE) with multiple transceivers has a possibility to connect to a Macro eNodeB (MeNB) and a Small cell eNodeB (SeNB) simultaneously. In downlink split bearer architecture of DC, a data radio bearer at MeNB gets divided into two; one part is forwarded to the SeNB through a non-ideal backhaul link to the UE, and the other part is forwarded by the MeNB. This may lead to an increase in the total delay at the UE since different packets corresponding to a single transmission may incur varying amounts of delays in the two different paths. Since the resources in the MeNB are shared by background legacy users and foreground users, DC may increase the blocking probability of background users. Moreover, single connectivity to the small cell may increase the blocking probability of foreground users. Therefore, we target to minimize the average delay of the system subject to a constraint on the blocking probability of background and foreground users. The optimal policy is computed and observed to contain a threshold structure. The variation of average system delay is studied for changes in different system parameters.Comment: Conferenc

Clustering clinical departments for wards to achieve a prespecified blocking probability

When the number of available beds in a hospital is limited and fixed, it can be beneficial to cluster several clinical departments such that the probability of not being able to admit a patient is acceptably small. The clusters are then assigned to the available wards such that enough beds are available to guarantee a blocking probability below a prespecified value. We first give an exact formulation of the problem to be able to achieve optimal solutions. To reduce computation times, we also introduce two heuristic solution methods. The first heuristic is similar to the exact solution method, however, the number of beds needed is approximated by a linear function. The second heuristic uses a local search approach to determine the assignment of clinical departments to clusters and a restricted version of the exact solution method to determine the assignment of clusters to wards