Traffic Modeling and Network Performance

• Communications Industry Overview
• Air Interface and Front-End Design
• Baseband Signal Processing
• Wireless and Wired Channel Modeling
• Traffic Modeling and Network Performance

Engineering teams use MATLAB and Simulink to model and simulate network traffic behavior and predict network performance – a critical need and a competitive advantage for designing and deploying the next generation of communications services and networks.

Design Networks and Services with Confidence

New communications networks must be able to transmit different services such as audio and video with a consistent level of quality. Network operators use MathWorks products to model and predict network performance measures such as congestion, resource contention, and process delays.

Use Traffic Models to Predict Network Equipment Performance

Network equipment manufacturers use MathWorks products to create accurate and reusable traffic models of communications equipment and protocols to simulate network and channel utilization, as well as the impact of adding new services on existing networks.

Engineers use traffic models to determine latency, blocking, and resource starvation issues inherent in a communications network configuration. These models allow equipment manufacturers to demonstrate and prove the performance and suitability of their products to network planners and service providers. Network planners use the models created by equipment manufacturers to study and compare various network configuration options, and recommend the most efficient solutions to service providers.

Model Physical and Network Layers in One Environment

Engineers need to simulate and verify the network performance while the physical layer is still under development, or independent of the physical layer behavior. To help simulate network performance independently, MATLAB and Simulink support both time-driven and discrete-event modeling including queues, servers, and traffic generators. Engineers also use the tools to model the network performance and the physical layer together. To do this, they combine the network traffic models with physical layer components including state machines, signal processing, and mixed-signal subsystems, simulating both the discrete-event and dynamic system behaviors.