# QoS-Aware Downlink Traffic Scheduling for Cellular Networks with Dual Connectivity
## 2 Related Works  
### Traffic Scheduling in Dual Connectivity Networks  
In the following, we review previous works on cellular networks with dual connectivity capability. The study [10] introduces a framework to facilitate connectivity mode selections for UEs. By the proposed scheme, each UE decides whether to enable the dual connectivity mode based on its energy efficiency. The proposed scheme can reduce congestion and improve the QoS of UEs, but the proposed scheme only focuses on uplink transmissions. In reference [11], the authors use non-orthogonal multiple access (NOMA) technology to improve the energy efficiency of MeNB and SeNB. The authors define a linear programming formulation, whose goal is to minimize power consumption when disseminating downlink data. However, the formulation cannot be used to make traffic dispatching decisions. The authors in [12] design a data splitting scheme for heterogeneous networks. The designed scheme utilizes the concept of water-filling to allocate radio resources to dual-connected UEs. By the scheme, the throughput of UEs can be effectively increased, but the network architecture is not compatible with 3 GPP cellular networks. The constrained Markov decision process to make the traffic splitting decision is discussed in [13]. The designed scheme aims to minimize packet delays. However, UEs' capabilities and signal qualities are not considered when modeling the network, and thus, delays cannot be precisely evaluated. Furthermore, in reference [14], the authors define the gain of the network when UEs receive downlink data from the MeNB and a SeNB simultaneously. Then, based on the estimated signal qualities of UEs and delays of data flows, the proposed scheme maximizes network gain by deciding how to dispatch data to SeNBs. In [15], a downlink data dispatching method is introduced, whose goal is to save the power of the backhaul links. In the proposed scheme, the MeNB dispatches data to SeNBs if energy consumption of the network or receiving qualities of UEs can be improved. In reference [4], each dual-connected UE reports its receiving status to the MeNB every TTI. After collecting UE reports, the MeNB uses predefined functions to make traffic splitting decisions. In reference [5], each UE first decides which SeNB it wants to connect to. After confirming the UE's choice, the MeNB dispatches data to the corresponding SeNB according to the network load and fairness. Furthermore, in [16], the authors present a data dispatching method for LTE-A networks with dual connectivity enhancement. In the proposed scheme, network parameters (such as remaining data volumes and connection statuses) are used to model a linear programming formulation. The MeNB refers to solutions of the linear formulation to dispatch data to SeNBs. However, the proposed formulation does not take into account SeNB's capability. Next, the authors in [17; 18] solve the TCP out-of-order phenomenon in dual connectivity networks. In [18], two splitting algorithms are designed to reduce the probability of out-of-order receptions on the UE sides, but UEs have to report frequently. In [17], the authors utilize the Raptor code concept to resolve an out-of-order problem. By Raptor codes, UEs can decode source data after receiving enough encoded data. However, the proposed scheme cannot be used to support networks with dense traffic loads. The above previous works propose traffic scheduling methods in dual connectivity networks. Table 1 summarizes the comparisons of previous works with the proposed QDD in three aspects. Two previous works (i.e., [10; 13]) are not designed to make downlink traffic dispatching decisions. Although references [12; 17; 18] describe dispatching methods, these schemes do not take QoS parameters into consideration. Furthermore, the other works do not consider the SeNB's capability when making dispatching decisions; as a result, downlink data (that sent to SeNBs) may not be processed in time.