## 1 Introduction  
Wireless communications and mobile networks are inherently integrated into the daily activities of every business sector, ranging from academic events to industrial operations. With the paradigm introduced by ITU, known as \"Always Best Connected\" (ABC) [1], the 3 rd generation partnership project (3 GPP) has proposed the coordinated multi-point (CoMP) operation in [2], where coordinated transmission and reception applies between macro cell(s) and micro cell(s) of heterogeneous networks (HetNets) to provide seamless, quality of service (QoS)-aware media services to the active user equipment (UE), including Internet of Things (IoT) devices and/or mobile vehicles therein. Furthermore, dual connectivity (DC) has been proposed in [3], where any arbitrary UE enjoys radio resources provided by access point (AP) with the same/different radio access technology (RAT) under non-ideal backhaul. To further exploit the benefits of DC from the perspectives of user throughput and mobility enhancement within small cell networks (SCNs), multi-radio dual connectivity (MR-DC) [4] grows to become a feasible solution for the cooperation/co-existence of 4G long term evolution (LTE) and 5G new radio (NR), facilitating the convergence of communications and positioning solutions as well as enabling the autonomous function for the connected vehicles. As an extension of DC, MR-DC suggests that the UE can be configured to maintain multiple connections [5] and utilize resources of multi-RAT enabled networks, i.e., the HetNets. In the context of multi-RATs and SCNs, seamlessly handing over to or selecting a network/RAT, which provides the best possible QoS to the UE, remains a crucial enabler of a self-organized communication system, in which the connected vehicles/robots are capable of performing efficient handover in a self-organized manner via the obtained location awareness, such that the throughput as well as the link quality are jointly optimized. Apart from the IEEE 802.21 multimedia-independent handover (MIH) standard that supports a QoS-based handover within the HetNets, several works [6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18] investigated the location-aware handover (LHO) and/or location-aware network selection (LNS) strategy ensuring that the mobile users have access to the required media service via the best available network. The objective of our work is therefore to investigate the feasibility and benefits of such efficient handover decision making schemes (i.e., the LHO) when integrating the positioning solutions. Furthermore, as a result of the proliferation of industrial vehicles [19], we believe that the LHO algorithm will not only be beneficial to the conventional mobile users, but also it will be desirable for vehicle/robot-based industrial Internet of things (IIoT) applications where multi-Gbps throughput is required for data offloading/exchange (e.g., virtual reality [20]) with one or several millimeter wave (mmWave) APs. In this paper, we describe an efficient LHO scheme for a multi-RAT robotic platform in an indoor multi-radio environment. Thereafter, an experimental study is performed to evaluate the concept feasibility and demonstrate the achievable performance. In our measurement setup, one mmWave AP and one centimeter wave (cmWave) AP (WiFi at 2.5 GHz) are deployed and utilized. Furthermore, we construct a 3D line-of-sight (LoS) map for the area of interest where the LHO algorithm is tested. This map indicates the area where the robot has the LoS communications with the mmWave AP. Then, by considering the available location-related measurements (LRMs) (to be discussed in Section 2.2) at the robot side, we formulate a geometry-based positioning (GBP) algorithm and evaluate the corresponding achievable positioning accuracy in theory. Although the theoretical positioning accuracy is shown to be promising, the experimental outcomes with a standalone GBP are hardly satisfactory due to the inaccuracy and instability of LRMs, as we discuss in Section 5.2.