Research Projects

Cellular networks, supporting over 1.1 billion mobile subscribers in India as of 2024, form the backbone of the nation’s digital economy, enabling socio-economic development, digital inclusion, and smart city initiatives. Despite significant advancements in network infrastructure, urban areas with complex geographies, such as Aizawl, face persistent connectivity challenges. The city’s hilly terrain creates shadow zones with weak signals (below -90 dBm), resulting in frequent call drops and poor Quality of Service (QoS). Additionally, high-density zones suffer from network congestion due to inadequate infrastructure and the absence of data-driven optimization strategies. Addressing these issues requires innovative approaches that integrate advanced technologies and collaborative efforts with mobile operators. This study proposes a comprehensive AI-driven framework for cellular network optimization and signal mapping, with Aizawl serving as the initial testbed. Real-time data collection from IoT sensors, drone-based field measurements, and operator-provided datasets will generate accurate multi-operator signal maps, identifying weak signal zones and high-traffic congestion areas. Predictive AI/ML models, including Convolutional Neural Networks (CNNs) for spatial analysis and Long Short-Term Memory (LSTM) networks for temporal forecasting, will estimate signal strength in unmeasured regions and optimize infrastructure placement. Reinforcement learning algorithms will recommend optimal locations for cell towers and repeaters to enhance network coverage and minimize shadow zones. The framework includes the development of a mobility-aware and signal-aware proactive content caching system to dynamically preload content on edge servers and end-user devices based on real-time signal conditions and user mobility patterns. This system ensures uninterrupted content delivery, reduces latency, and mitigates network congestion during peak usage. Furthermore, interactive dashboards will provide stakeholders, including telecom operators and urban planners, with real-time visualization tools to support data-driven decision-making. The proposed framework aims to address connectivity challenges in Aizawl and similar urban environments, aligning with the objectives of the Digital India initiative. By leveraging advanced AI/ML techniques, this research contributes to the development of scalable, replicable solutions for optimizing cellular networks, fostering equitable digital inclusion, and advancing sustainable urban transformation.