To simulate a Cognitive Ad-Hoc Network (CAN) using OPNET, we need to comprise executing cognitive radio capabilities, which enable nodes to detect the environment, then decision making according to the available spectrum, and actively change its interaction channels to prevent the interference. Following is a general instruction to help replicate a CAN project within OPNET:
Steps to Simulate Cognitive Ad Hoc Network Projects in OPNET
- Define the Cognitive Ad-Hoc Network Architecture
- Cognitive Radio Nodes: Configure nodes using OPNET along with cognitive radio capabilities, which allowing them to detect, adjust, and change channels depends on spectrum availability. Set up nodes to execute the spectrum sensing, decision-making, and frequency hopping.
- Primary and Secondary Users: Design primary users (licensed users of the spectrum) and secondary users (cognitive radio nodes that utilize available spectrum opportunistically). Primary users might be fixed nodes, which periodically utilize particular frequency bands.
- Implement Spectrum Sensing
- Spectrum Sensing Mechanism: Configure spectrum sensing at every cognitive radio node. Train nodes to occasionally scan the obtainable channels for dynamic primary users. In OPNET, we can utilize custom scripts to replicate the channel occupancy detection and signal strength measurement.
- Dynamic Channel Availability: Mimic an active environment in which primary users activate and deactivate that triggering spectrum availability to modify. Train the nodes to identify primary user presence on a provided channel and evacuate it if interference is identified.
- Configure Spectrum Decision-Making
- Channel Selection Algorithm: Execute a channel selection algorithm for cognitive nodes to select the optimal available channel rely on factors such as signal strength, interference, and quality of service (QoS) requirements. Handle the channel switching using OPNET’s decision logic functions or scripting.
- Frequency Hopping: Configure frequency hopping to allow the nodes to rapidly switch channels upon identifying the primary user activity. Cognitive nodes would be capable of seamlessly transition to a new channel without dropping dynamic sessions.
- Configure Cognitive Routing Protocols
- Cognitive Routing Protocols: Utilize routing protocols, which support cognitive capabilities like Cognitive Ad-hoc On-Demand Distance Vector (CAODV) or Cognitive OLSR. We require to script custom alterations of standard ad hoc routing protocols within OPNET to contain spectrum awareness and dynamic routing decisions according to the channel availability.
- Multi-Hop Communication: Make sure the network supports multi-hop communication, which enabling cognitive nodes to send data over several nodes to attain the distant destinations that particularly in cases where few channels probably not available.
- Set Up Communication and Interference Modeling
- Channel Occupancy Simulation: Describe numerous frequency channels within OPNET, some of which are utilized by primary users in random intervals. It makes an environment in which cognitive nodes must adjust to changing the channel availability.
- Interference Detection and Avoidance: For cognitive nodes, execute mechanisms to identify the interference from primary users and switch to an available channel. Configure interference thresholds and train the nodes to prevent any channel more than that threshold.
- Implement Key CAN Use Cases and Traffic Models
- Emergency Response: Design a situation in which nodes actively form a network in response to an emergency by available channels to send critical data. Set up traffic patterns, which reflect high priority and real-time communication requirements.
- Data Collection in Dynamic Environments: Configure a situation in which cognitive nodes occasionally collect and send information within an environment with changing spectrum availability. It replicates IoT applications or observing networks in which spectrum access differs over time.
- Run the Simulation and Adjust Network Conditions
- Scenario Variations: Experiment the CAN under distinct conditions like changing primary user activity, node mobility, and network density. Replicate how cognitive nodes adjust to high and low channel availability.
- Network Load and Traffic Patterns: Test with diverse traffic loads such as constant bit rate for sensor data, bursty traffic for emergency messages to compute how successfully cognitive nodes sustain the connectivity under active spectrum conditions.
- Analyze Key Performance Metrics
- Spectrum Utilization and Efficiency: Calculate how effectively cognitive nodes utilize the available spectrum. Higher spectrum utilization shows good channel sensing and selection.
- Throughput and Delay: Observe the throughput and end-to-end delay to measure the capability of network to sustain the interaction quality while channels turn into unavailable.
- Packet Delivery Ratio (PDR): Track the success rate of data packets reaching their destination. High PDR is essential for applications requiring reliable data transmission.
- Channel Switching Frequency: Monitor how frequently nodes switch channels. Common switches can display the high interference or inadequate spectrum sensing, even though lower switching rates recommend stable channel availability.
- Optimize Cognitive and Routing Algorithms
- Adaptive Sensing Intervals: Test with diverse sensing intervals to stable the requirement for rapid adaptation including energy efficiency. More common sensing enhances the responsiveness however exhausts more power.
- Routing Optimization: Adapt routing protocols to enhance for modifying network topology because of the channel switching, which deliberating route stability, delay, and hop count within routing decisions.
Here, we had illustrated in sequence of simulation steps that useful to you how to approach and replicate the Cognitive Ad-Hoc Network (CAN) utilizing OPNET. We’re ready to offer more detailed process and project ideas if necessary.
