Smartphones, Internet of Things (IoT) devices, and autonomous systems have dramatically increased the demand for seamless, uninterrupted connectivity. Whether it’s a commuter streaming a video while riding a train, or an autonomous drone transferring real-time telemetry, the underlying networks must support continuous service as devices move across different network areas. This is where mobility management becomes critical.
Mobility management refers to the set of technologies and processes that allow devices to maintain service continuity and quality as they move within and between networks. Traditionally rooted in mobile cellular networks, mobility management has evolved significantly to accommodate the complexities of 5G and beyond, where ultra-low latency, high throughput, and massive device connectivity are expected.
In Africa, the mobile and Mobility-as-a-Service (MaaS) markets accurately reflect the evolution of modern communication networks. According to the latest Mobile Economy 2023 report released by the GSMA, Sub-Saharan Africa is one of the global regions that will see the biggest increase in smartphone adoption and is set to reach 87% by 2030. The mobile industry in Sub-Saharan Africa contributed USD 140 billion to the gross domestic product (GDP) in 2023 (7%) and is projected to reach USD 170 billion by 2030. Total mobile subscriptions in Sub-Saharan Africa will grow at an annual rate of 4%, increasing from 950 million in 2023 to 1.2 billion by 2030.
On the MaaS front, the Middle East and Africa (MEA) market is forecast to reach USD 74.35 billion by 2030, growing at a compound annual growth rate (CAGR) of 21.27%. According to Mordor Intelligence, Africa’s ride-hailing market is anticipated to reach USD 2.53 billion in 2025, growing at a CAGR of 4.5% to reach USD 3.16 billion by 2030, necessitating robust mobility management.
The Evolution of Mobility Management
In 3G and 4G networks, mobility management was relatively straightforward. Devices typically moved between macro cells and required basic handover mechanisms, supported by the core network. However, for 5G and the upcoming 6G networks, the scenario has changed dramatically. Today, networks are composed of a mix of small cells, macro cells, Wi-Fi hotspots, and even satellite links, which devices must navigate seamlessly.
Reflecting this convergence, MTN Group partnered with Lynk Global to conduct Africa’s first satellite voice call via a standard smartphone, showcasing its satellite-mobile integration efforts. Vodacom South Africa is collaborating with Amazon’s Project Kuiper and AST SpaceMobile to extend 4G and 5G services using low Earth orbit (LEO) satellites. Somalia has deployed 5G across over 30 towns using macro and small cells, supplemented by hotspot and portable MiFi devices.
Modern networks now require advanced mobility protocols that go beyond handovers.
These include intelligent routing, dynamic session management, and predictive mobility techniques. The goal is to ensure that users and machines experience minimal latency, no dropped calls, and uninterrupted service, regardless of their movement or environment.
Key Components of Mobility Management
- Handover Management: This is the most visible aspect of mobility management. It involves the transfer of an active session from one access point to another as a user moves. In 5G networks, this includes intra-frequency, inter-frequency, and inter-RAT (radio access technology) handovers.
- Location Management: This involves tracking the device’s location within the network to ensure it can be reached efficiently; it’s crucial for both idle and active modes. Location updates must be timely and efficient to reduce signaling overhead and latency.
- Session Management: Maintaining a continuous data session without interruption is vital. Technologies like mobile IP and proxy mobile IP have been employed to handle IP session continuity. In 5G, the session management function (SMF) plays a central role in maintaining sessions across different access networks.
- Context Awareness and AI: As mobility patterns become more complex, artificial intelligence (AI) and machine learning (ML) are being leveraged to predict user movements and proactively manage resources. Context-aware mobility management considers factors like user behavior, network load, and application requirements to optimize handovers and reduce service disruptions.
Challenges in Modern Mobility Management
Despite technological advancements, several challenges persist. Devices must move between different types of networks, such as 5G NR, LTE, Wi-Fi, and satellite, while applications like augmented reality (AR)/virtual reality (VR), online gaming, and autonomous vehicles (AVs) require ultra-low latency. Even minor disruptions during handovers can degrade the user experience (UX) or lead to safety risks.
Beyond this, mobility management operations, particularly location tracking and frequent handovers, can consume significant power. With billions of connected devices expected in the coming years, mobility management solutions must be scalable and robust, ensuring performance under high traffic loads. During an exclusive autonomous networks panel at the 2024 Telecom Review Leaders’ Summit, Amaru Chavez-Pujol, CTIO, Bayobab, highlighted the need for proactive monitoring through large network operation centers (NOCs) to predict potential service disruptions and adapt offerings using predictive models.
Innovative Approaches to Optimization
To address these challenges, several innovative approaches are being explored. Software-defined networking (SDN) and network function virtualization (NFV) foster greater flexibility in mobility management as mobility functions can be dynamically deployed where needed, reducing latency and improving responsiveness.
By processing data closer to the user or device, edge computing minimizes the need for data to travel long distances. This reduces latency during handovers and enhances overall service continuity. In addition, multi-access edge computing (MEC) integrates mobility functions at the network edge, facilitating faster decision-making during handovers and providing localized services without backhauling to the central core.
Predictive analytics can further forecast user movement and network demand, allowing pre-emptive allocation of resources and smarter handover strategies. Notably, Nokia has integrated AI with radio networks to optimize key parameters, enhancing energy efficiency by shutting down cells based on traffic patterns, delivering up to 15-20% energy savings for operators.
Looking Ahead
As 6G begins to take shape, mobility management will become even more sophisticated.
Concepts like ubiquitous connectivity, intelligent surfaces, and integrated satellite-terrestrial networks will demand new paradigms in mobility control. The focus will shift from simply ensuring connection continuity to optimizing quality of experience (QoE) dynamically.
As Danial Mausoof, VP Technology and Solutions at Nokia MEA, emphasized, the “focus extends to orchestration, software, and transport, including microwave solutions” to “ensure the right elements for connectivity, while delivering substantial end-user benefits in terms of cost, quality, and performance.”
Together, these elements serve as the framework required to optimize mobility management in modern commination networks.
