## 1 Introduction  
The internet of things (IoT) is considered to be the next information revolution, where everyday objects equipped with embedded sensors will process and transmit data from its environment to the Internet. The mining of the collected data in IoT is expected to support knowledge-based decisions in healthcare, smart cities, transportation, industrial automation, etc. In this context, cellular communication systems will play a key role in IoT use cases, where mobile nodes (sensing objects) require a wide coverage area, e.g., location and mobility tracking, fleet management, and mobile health IoT applications [1]. Towards supporting IoT devices, the cellular network standards are evolving in order to support the connectivity to resource-constrained machine type communication (MTC) devices from IoT. However, the efficient support of pervasive IoT applications in cellular networks faces different challenges, mainly because HTC traffic requirements have historically driven current network management mechanisms and radio access network (RAN) infrastructure. Because of the fundamentally different characteristics of MTC concerning the existing human type communications(HTC), it is crucial the design of novel resource management mechanisms to efficiently utilize network resources while maintaining a good quality of service (QoS) in IoT cellular scenarios [2]. Unlike HTC involving voice calls, messaging, and web browsing, MTC is characterized by an increased number of IoT devices, traffic direction, message size, transmission periodicity, and power constraints of IoT devices [3]. Taking this into account, we argue that resource management solutions must consider the following aspects as core requirements. First, the RAN evolution towards flat network architectures calls for novel resource allocation schemes to be distributed across base stations (BSs) at the network edge [4; 5; 6; 7]. Second, it is of paramount importance the efficient support of MTC devices, while taking into account IoT application-specific QoS requirements, such as a minimum data rate. Third, the incorporation of massive MTC devices and enhanced broadband services in the existing cellular network infrastructure may lead to congestion situations in different segments of the RAN, including the backhaul and the mobile core network used to interconnect end devices to remote cloud data centers. Hence, backhaul-awareness must be considered in resource allocation processes in order to cope with a possible shortage of backhaul resources [8; 9; 10; 11]. It has been proved that the backhaul network constitutes a new resource bottleneck as more spectral efficient air interface technologies have been developed and deployed in cellular networks [6]. Attending to these arguments, in this paper, we address the BS assignment problem whose aim is to determine the most appropriate BS to transmit/receive data to/from each mobile device. This problem's importance lies in the fact that, if users are not correctly associated with BSs, then the resulting performance could be affected in terms of throughput, interference, energy consumption, and load imbalance in the radio interface. In this context, this paper aims to develop a distributed BS assignment algorithm that is suitable for multi-cell mobile wireless systems for the efficient support of machine-type communication scenarios and assuming limited backhaul conditions. In the following, we briefly analyze the relevant approaches proposed in the literature proposed to solve the BS assignment problem.