Distributed Quiet-Period Scheduling for Cognitive Radio Networks
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Solution Overview
Problem
In distributed-control cognitive radio networks, especially those spanning multi-hop distances, efficiently scheduling quiet-periods for channel monitoring is challenging due to the lack of centralized control, leading to inefficiencies and potential cascading interference from secondary user devices.
Innovation Solution
Each secondary user broadcasts its minimum quiet-period sensing demand, and devices adjust their parameters to accommodate the highest demand, negotiating interval and duration to synchronize on a common time base, ensuring optimal efficiency and reliable primary user detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If regularly scheduled quiet-periods are used, then rapid sensing is enabled, but the duration may be too short for some devices or lead to inefficiencies
Solution Approach 1:
The patent implements dynamic quiet-period scheduling where the schedule is adjusted based on network conditions and device requirements. Devices can request on-demand quiet-periods and the system adapts the scheduling to balance rapid sensing with sufficient detection duration, resolving the contradiction between speed and reliability
Solution Approach 2:
The patent changes the parameters of quiet-periods dynamically - adjusting duration, frequency, and timing based on device sensing requirements and network traffic conditions. This allows the system to optimize between rapid sensing and reliable detection by varying parameters rather than using fixed schedules
2Adaptability or versatility
If on-demand sensing is implemented, then device-specific optimal duration is achieved, but coordination complexity increases
Solution Approach 1:
The patent introduces a quiet-period coordinator (which can be a central controller or distributed algorithm) that mediates between devices requesting on-demand sensing and the network traffic requirements. This intermediary manages the coordination complexity centrally while allowing devices to simply request sensing opportunities, reducing individual device complexity
Solution Approach 2:
The patent implements feedback mechanisms where devices report their sensing requirements and the coordinator adjusts quiet-period scheduling based on this feedback. This feedback loop enables device-specific optimization while the coordinator manages the overall coordination, preventing complexity from escalating
3Extent of automation
If distributed control is used, then network autonomy is improved, but scheduling difficulty increases
Solution Approach 1:
The patent segments the scheduling function into distributed components where each device or cluster manages its own quiet-period scheduling independently. This segmentation allows autonomous operation while reducing overall scheduling difficulty by breaking the complex global problem into smaller, manageable local decisions
Solution Approach 2:
The patent enables devices to self-manage their quiet-period scheduling by autonomously requesting and coordinating sensing opportunities based on their own requirements. This self-service approach maintains network autonomy while simplifying the scheduling process for individual devices, as they only need to manage their own sensing needs rather than coordinating with the entire network
4Area of stationary object
If multi-hop network distances are spanned, then network coverage is extended, but synchronization difficulty increases
Solution Approach 1:
The patent introduces intermediary nodes or cluster heads in multi-hop networks that act as local coordinators for quiet-period scheduling. These intermediaries receive sensing requests from remote devices and coordinate with the central scheduler or other intermediaries, extending network coverage while managing synchronization complexity at manageable levels rather than requiring direct end-to-end coordination
Data Source
AI summary
In a distributed-control cognitive radio network, each secondary user (200) in a network broadcasts parameters (125) that indicate the minimum quiet-period sensing demand for regular quiet-periods that the device requires for reliable detection of a primary user (290). Each device (200) in the network adjusts its quiet-period sensing rate to accommodate the highest minimum sensing demand (155, 160), thereby providing optimal efficiency relative to quiet-period support while assuring that all devices (200) in the network are provided at least their minimum quiet-period sensing demand (150). Both the interval between regular quiet-periods and the duration of these quiet-periods are negotiated among the devices on the network (155). A quiet-period index (140) is used to synchronize all of the devices to a common time base. Techniques are also provided for efficient coordination of on-demand quiet-period requests, and for supporting different quiet-period schedules for multiple classes of primary users.