Hybrid Quantum Wireless Network for Dynamic Spectrum Allocation
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Solution Overview
Problem
Current mobile network technologies fail to efficiently detect PHY and MAC signatures of other networks across wide bands of spectrum, leading to interference and underutilization of spectrum, as they lack the capability to dynamically assign frequencies to mobile devices without polling databases or adhering to exclusion zones.
Innovation Solution
A hybrid quantum-conventional computational system that analyzes band capture data to distinguish between polynomial time and NP-hard problems, using a quantum computer to process NP-hard problems and a conventional computer to process polynomial time problems, enabling the detection of network signatures and traffic patterns for dynamic frequency allocation without interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional computing is used to manage spectrum allocation, then the system is easier to implement and operate, but it cannot efficiently detect PHY and MAC signatures across wide bands or dynamically assign frequencies without polling databases
Solution Approach 1:
The patent segments the computational workload by dividing spectrum analysis into distinct functional modules: signature detection unit, traffic pattern recognition unit, and frequency assignment unit. This segmentation allows each module to specialize in specific tasks, improving overall system capability while managing complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary computational layer that acts as a mediator between raw spectrum data and frequency assignment decisions. This intermediary layer processes and interprets PHY and MAC signatures, transforming complex spectral information into actionable frequency allocation decisions without requiring direct database polling.
2Productivity
If database polling is used to determine spectrum availability, then the system operates with simpler logic, but it creates interference and fails to exploit underutilized spectrum efficiently
Solution Approach 1:
The patent implements preliminary action by continuously monitoring and analyzing spectrum signatures in advance of actual communication needs. The system pre-identifies underutilized frequency bands and prepares frequency assignment recommendations before they are needed, allowing efficient spectrum exploitation without reactive database polling that causes interference.
Solution Approach 2:
The patent establishes a feedback mechanism where the system continuously monitors spectrum usage patterns, detects changes in network signatures, and dynamically adjusts frequency assignments based on real-time observations. This closed-loop feedback enables efficient spectrum utilization by automatically adapting to changing conditions without external database queries.
3Reliability
If the system continuously monitors wide bands for network signatures, then it can dynamically assign frequencies without interference, but it requires complex computational processing
Solution Approach 1:
The patent applies local quality by focusing computational resources on specific local characteristics of the spectrum rather than uniformly analyzing all frequencies. The system identifies and concentrates processing effort on detecting specific PHY and MAC signature patterns in regions where underutilized spectrum is likely to exist, reducing overall computational complexity while maintaining reliable interference-free assignment.
Solution Approach 2:
The patent utilizes parameter changes by transforming the computational problem from analyzing raw spectral data to detecting specific signature parameters and traffic patterns. By changing the analysis parameters from comprehensive spectrum scanning to targeted signature detection, the system achieves reliable frequency assignment with reduced computational complexity.
Data Source
AI summary
A wireless communications system includes a feedback processing unit for analyzing captured bandwidth data from a remote radio head, and a problem-type processor in operable communication with the feedback processing unit. The problem-type processor is configured to (i) analyze the captured bandwidth data to determine whether the captured bandwidth data presents one of a computational polynomial time problem and a non-deterministic polynomial-time hard (NP-hard) problem, and (ii) transmit problem-specific data based on the determination. The system further includes a communications processor in operable communication with the problem-type processor. The communications processor is configured to process polynomial time problem data from the transmitted problem-specific data. The system further includes a quantum computer in operable communication with the problem-type processor. The quantum computer is configured to process NP-hard problem data received from the transmitted problem-specific data.