# A Modular Web-Based Software Solution for Mobile Networks Planning, Operation and Optimization
## 1 Introduction  
The massive proliferation of mobile devices and its widespread use, not just for communication purposes but entertaining as well, poses additional challenges to Mobile Network Operators (MNOs). While delivery of regular services (e.g., voice, data services) functioning is expected and somehow taken for granted, users continuously demand even higher standards for existent and future services Quality of Experience (QoE). As a matter of a fact, people nowadays perceive mobile devices as just commodities being part of their lifestyle. As a result, MNOs were forced to not only focus on delivering high network Quality of Service (QoS) but, evermore network QoE, changing the management paradigm of mobile networks; nowadays, Customer Experience Management (CEM) is a critical task for MNOs [1].  
The technological landscape of MNOs is continuously evolving either with the introduction of technological advancements as Software Defined Network (SDN) [2], networkarchitecture advancements such as Cloud Radio Access Network (C-RAN) [3], or even with the deployment of new Radio Access Networks (RANs), as the 5 th Generation (5G). In this context, MNOs have to jointly operate, manage and optimize their networks, balancing the new technological developments and network deployments with the legacy networks and associated dependencies. In this ecosystem, MNOs manage and operate highly complex networks and systems.  
Moreover, the ecosystem of MNOs generates evermore data from several data sources. From the classical QoS data sources, as Drive Tests (DTs), Configuration Management (CM), Performance Management (PM), and Fault Management (FM), to customer-related data as billing, to new data sources as crowdsourcing [4]. Additionally, data fusion techniques are being used to enrich MNOs' data, as pointed out in [5]. It augments an MNO data volume and increases the need to centralize data access and management.  
That being said, an MNO needs to hold a set of efficient systems/solutions and tools to cope with these increasing challenges during a network life cycle. One of the areas that can be particularly troublesome is network Operation and Maintenance (OAM). Indeed, an MNO is constantly asked to monitor and optimize the network in real-time to achieve better QoS and QoE targets. Moreover, current and future systems/solutions should incorporate Artificial Intelligence (AI) as it is a fundamental enabler to handle current and future network complexity [6]. A shift from a reactive-driven operation mode to a proactive and data-driven operation mode is possible with AI enhancing the network OAM. Access to multiple data sources in a single environment that guarantees data integrity is essential to accomplish the reactive to proactive transition [7].  
Within this context, we have designed and implemented a software solution to help MNOs tackling those demands. Its design and implementation is twofold: Firstly, to allow the software solution users to perform their tasks in a friendly and efficient manner. Secondly, to provide access to a set of high-quality RAN oriented algorithms as a backbone for network diagnosis, optimization, and planning.  
The algorithms incorporated in the proposed software solution were previously developed regarding actual data from MNOs and validated in OAM commercial projects. Moreover, the modular architecture of the software solution and open-source dependencies provide high flexibility to incorporate new data sources, new algorithms, and AI-based automation.