# Optimal User Association Strategy for Large-Scale IoT Sensor Networks with Mobility on Cloud RANs
## 2 Related Work
The authors proposed a simple handover scheme, which differentiates users with respect to their speed, consequently determining whether or not to allow users to connect to a small cell BS or not. However, this strategy does not apply to the conventional C-RAN model. In addition, under some circumstances, where many low-speed users are located close to each other, the nearby small cell BS may experience network congestion or buffer overflow. In [21], the authors proposed a resource optimization method for multi-cell OFDMA systems under the backhaul constraints. By allowing BSs to cooperate and share channel state information (CSI) with each other, their proposed solution allocates network resources to maximize the energy efficiency. The initial non-convex problem is transformed by exploiting the fractional programming, and then, the proposed iterative algorithm is applied to find a sub-optimal solution. However, their proposed solution makes an assumption that CSI is perfectly known and shared among BSs. Such an assumption is hard to guarantee in practice, incurs delay for collecting CSI, and increases computational overhead in resource optimization. Thus, it is not applicable to some real-time applications. In addition, the network setting assumed in [21] cannot be directly applied to C-RAN. In addition, the feasibility of the C-RAN with software-defined network was shown by [PERSON] et al. [22; 23; 24] via empirical experiments. The authors proposed a cloud-based radio over optical fiber network (C-RoFN) architecture with multi-stratum resource optimization (MSRO) [22; 23]. With the OpenFlow, which is the enabler of the software-defined network (SDN), they implemented a testbed to show that the proposed C-RoFN can orchestrate multi-layer resources (i.e., radio frequency, optical spectrum and BBU processing resources) to enhance radio coverage as well as to fulfill the QoS requirements. In [24], the authors studied a multi-dimensional resource integration (MDRI) technique for service provisioning in C-RoFN. Through an empirical study, the authors showed that MDRI can enhance both the end-to-end responsiveness and the radio coverage. In contrast to the previous studies on load balancing and/or handover-aware association strategies, the methods proposed in this work have the following advantages and distinctions. We consider dense C-RAN networks with large-scale mobile IoT devices. As pointed out in [25], it is one of the most important scenarios in the 5G system. In contrast to other studies conducted on user association, which focused only on either load balancing or handovers (or even neither of these two), we jointly consider both tasks. Such approach is important when dense C-RANs with mobile users are considered. In addition to proposing a simple, yet effective technique to reduce the time complexity, we conducted an evaluation to show that the proposed algorithms can be used in real-time under certain types of networks. We also investigated a possible solution to significantly reduce the time complexity. We evaluated and analyzed the performance of the proposed schemes as well other conventional ones under different scenarios (i.e., with different speed or the number of mobile IoT devices) to understand how the proposed methods behave under diverse network settings.