Dynamic Spectrum Sensing Resource Allocation in Cognitive Radio
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Solution Overview
Problem
Current cognitive radio networks lack a systematic method for dynamically allocating spectrum sensing resources, such as sensing time and the number of radios for collaborative sensing, leading to inefficiencies in managing changing radio and network environments.
Innovation Solution
A wireless communication controller with a cognitive engine and dynamic resource allocator that receives inputs on available sensing session time, communication channels, and detection constraints to dynamically allocate spectrum sensing resources among available sensing nodes, optimizing spectrum sensing in cognitive radio networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cooperative sensing is used to improve detection performance, then reliability of primary signal detection is improved, but device complexity and resource management difficulty increase
Solution Approach 1:
The patent implements dynamic resource allocation where the controller adaptively adjusts sensing parameters (sensing time, number of participating radios, channel selection) based on real-time network conditions, traffic load, and channel states. This dynamic approach allows the system to maintain high detection reliability when needed while reducing complexity during low-activity periods, directly resolving the contradiction between reliable detection and management complexity
Solution Approach 2:
The system changes key sensing parameters (sensing duration, number of sensing nodes, channel priority levels) based on detected network conditions and QoS requirements. By dynamically adjusting these parameters, the system optimizes detection performance for critical channels while reducing resource consumption for less important channels, thereby managing complexity effectively
2Measurement precision
If more sensing time is allocated to each channel, then detection precision is improved, but network throughput decreases due to longer sensing duration
Solution Approach 1:
The patent applies different sensing time allocations to different channels based on their priority, traffic load, and interference characteristics. High-priority channels with heavy traffic receive longer sensing times for accurate detection, while low-priority channels receive shorter sensing times. This localized quality approach ensures detection precision where needed while maximizing overall network throughput
Solution Approach 2:
The system performs sensing on only the most critical channels with full sensing time allocation, while using partial sensing or reduced sensing time for less critical channels. This selective approach ensures adequate detection precision for important channels without sacrificing overall network productivity through excessive sensing on all channels
3Reliability
If more radios are included in collaborative sensing, then detection reliability is improved, but loss of time increases due to coordination overhead
Solution Approach 1:
The controller dynamically adjusts the number of radios participating in collaborative sensing based on current network conditions, channel priority, and detection requirements. For critical channels, more radios are coordinated to achieve high reliability. For non-critical channels, fewer radios are involved to minimize coordination time. This dynamic adjustment resolves the contradiction between reliability and time loss
Solution Approach 2:
The sensing process is segmented into different phases and groups, where radios are organized into sensing clusters for different channel groups. This segmentation allows parallel processing of sensing tasks across multiple radio groups, reducing overall coordination time while maintaining detection reliability through distributed collaborative sensing
4Device complexity
If spectrum sensing resources are statically allocated, then device complexity is reduced, but adaptability to changing network environments deteriorates
Solution Approach 1:
The patent implements a dynamic resource allocation framework where the controller continuously monitors network conditions, channel states, and QoS requirements, then adjusts sensing resource allocation accordingly. This dynamic approach provides high adaptability to changing environments while maintaining manageable complexity through automated control algorithms and standardized protocols
Data Source
AI summary
A method, wireless controller, and information processing system are provided to dynamically allocate spectrum sensing resources. A first input (804) including available sensing session time for performing spectrum sensing with respect to one or more primary systems (102) is received. A second input (806) including a set of communication channels to be monitored in the spectrum sensing session is received. A third input (808) including detection constraints associated with a plurality of available sensing nodes (114) in a secondary network (104) for performing the spectrum sensing is received. Spectrum sensing resources are dynamically allocated (814) among a set of the plurality of available sensing nodes (114) based on the first (804), second (806), and third inputs (808).