Enhancing QoS and QoE in IMS Enabled Next Generation Networks

Managing network complexity, accommodating greater numbers of subscribers, improving coverage to support data services (e.g. email, video, and music downloads), keeping up to speed with fast-changing technology, and driving maximum value from existing networks -all while reducing CapEX and OpEX and ensuring Quality of Service (QoS) for the network and Quality of Experience (QoE) for the user. These are just some of the pressing business issues faced by mobileservice providers, summarized by the demand to “achieve more, for less.” The ultimate goal of optimization techniques at the network and application layer is to ensure End-user perceived QoS. The next generation networks (NGN), a composite environment of proven telecommunications and Internet-oriented mechanisms have become generally recognized as the telecommunications environment of the future. However, the nature of the NGN environment presents several complex issues regarding quality assurance that have not existed in the legacy environments (e.g., multi-network, multi-vendor, and multi-operator IP-based telecommunications environment, distributed intelligence, third-party provisioning, fixed-wireless and mobile access, etc.). In this Research Paper, a service aware policy-based approach to NGN quality assurance is presented, taking into account both perceptual quality of experience and technologydependant quality of service issues. The respective procedures, entities, mechanisms, and profiles are discussed. The purpose of the presented approach is in research, development, and discussion of pursuing the end-to-end controllability of the quality of the multimedia NGN-based communications in an environment that is best effort in its nature and promotes end user’s access agnosticism, service agility, and global mobility.

💡 Research Summary

The paper addresses the growing complexity of next‑generation networks (NGN) and the simultaneous need to guarantee both network‑level Quality of Service (QoS) and user‑perceived Quality of Experience (QoE). Mobile operators are pressured to “do more with less,” meaning they must support a larger subscriber base, richer multimedia services, and diverse access technologies (fixed, wireless, mobile) while keeping capital and operational expenditures low. Traditional QoS mechanisms, which were sufficient in legacy, single‑vendor, circuit‑switched environments, fall short in NGN because the environment is inherently multi‑network, multi‑vendor, and multi‑operator, with distributed intelligence, third‑party provisioning, and best‑effort IP transport.

To tackle these challenges, the authors propose a service‑aware, policy‑based quality‑assurance framework built around the IP Multimedia Subsystem (IMS). The core idea is to treat QoS and QoE as two facets of a single policy set that can be dynamically generated, distributed, and refined. The framework consists of four main components:

1. Service Profile – a metadata repository that captures subscriber attributes, device capabilities, and application requirements (e.g., bandwidth, latency sensitivity). Profiles are stored in the IMS Home Subscriber Server (HSS) and can be updated in real time.

2. Policy Engine – consumes service profiles together with real‑time network measurements (available bandwidth, delay, jitter, packet loss). It produces two kinds of rules: traditional QoS parameters (DSCP markings, traffic shaping, queue priorities) and QoE‑oriented directives (target MOS, PSNR thresholds, buffer‑level targets). The engine incorporates machine‑learning models to predict traffic trends and proactively allocate resources.

3. Controller/Provisioning Module – translates the policy rules into concrete configurations on network elements such as SDN switches, MPLS‑TE routers, and wireless access points. Standard interfaces (SIP for session control, Diameter/RADIUS for authentication and authorization, REST‑API for policy push) ensure interoperability across vendors and operators.

4. Feedback Loop – collects QoE metrics from end‑user devices (playback buffer status, user ratings, error logs) and feeds them back to the Policy Engine. This loop enables continuous, closed‑loop optimization, allowing the system to adapt to user mobility, handovers, and changes in access technology.

The signaling plane uses SIP for session establishment and service negotiation, while the control plane relies on Diameter and RADIUS for AAA functions. The data plane combines MPLS‑Traffic Engineering with SDN‑based flow steering to achieve fine‑grained traffic engineering while preserving the best‑effort nature of the underlying IP fabric.

Key insights derived from the analysis include:

• Unified QoS/QoE Management – By integrating QoE targets into the same policy framework that governs QoS, operators can align network resource allocation with actual user satisfaction.
• Dynamic, Service‑Centric Policies – Policies are generated per‑service (e.g., video streaming, email, music download) and can be re‑computed on‑the‑fly as network conditions evolve, providing agility and reducing over‑provisioning.
• Cost Efficiency – The policy‑driven approach, especially when enhanced with predictive analytics, enables more efficient use of existing infrastructure, thereby lowering both CapEx and OpEx.
• Inter‑Operator Interoperability – Because the framework relies on standardized protocols and abstracted policy objects, it can be deployed across heterogeneous vendor equipment and across multiple operators without proprietary lock‑in.
• Mobility and Access‑Agnosticism – The feedback loop and SDN‑based control allow seamless adaptation to user movement between fixed, wireless, and mobile access networks, preserving QoE despite underlying transport changes.

The authors also discuss implementation details such as the mapping of service profiles to SIP/IMS headers, the encoding of policy rules into OpenFlow or MPLS label‑stack modifications, and the use of RESTful APIs for third‑party service providers to inject custom QoE metrics.

Future work outlined includes conflict‑resolution mechanisms for overlapping policies, large‑scale field trials to validate performance gains, and extensions to emerging 5G/6G radio access technologies where ultra‑low latency and massive device density will further stress QoE management.

In summary, the paper presents a comprehensive, standards‑based, and extensible architecture that bridges the gap between network‑level QoS guarantees and user‑perceived QoE in NGN environments. By leveraging IMS, policy‑based control, and closed‑loop feedback, the proposed solution offers a practical roadmap for operators seeking to deliver high‑quality multimedia services while maintaining cost‑effectiveness and operational flexibility.