Quantum Resource Allocation for Interference-Aware Wireless Scheduling
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Solution Overview
Problem
Existing resource allocation methods in wireless communication networks, particularly in 6G systems, face challenges in efficiently managing interference and maximizing rewards in spectrum sharing and device-to-device communication, with classical algorithms being inefficient in solving graph coloring problems with preferences.
Innovation Solution
A quantum algorithm is employed to solve resource allocation problems by converting them into graph coloring problems (GCP), utilizing a quantum calculating center to apply preferences and optimize resource allocation based on interference and reward information, incorporating a conditioned oracle operation and phase inversion processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If classical algorithms are used to solve graph coloring problems for resource allocation, then the solution can be obtained, but the computational complexity is high and efficiency is low
Solution Approach 1:
The patent replaces classical computational algorithms with a quantum computing system. The quantum calculating device uses quantum mechanical principles (superposition, entanglement, interference) to solve graph coloring problems, substituting the mechanical/computational system with a quantum physical system that achieves exponential speedup in certain computational tasks.
Solution Approach 2:
The patent changes the fundamental parameter of computation from classical bits to quantum bits (qubits), enabling the system to process multiple states simultaneously through quantum superposition. This parameter change transforms the computational complexity from polynomial to logarithmic or constant time for certain problems.
2Productivity
If quantum algorithm is used to solve resource allocation problems, then the computational efficiency is improved with square root complexity, but the system complexity and implementation difficulty increase
Solution Approach 1:
The patent segments the resource allocation problem into discrete graph coloring subproblems, where each node represents a resource unit and edges represent conflicts. This segmentation allows the quantum algorithm to process the problem in manageable components while maintaining the overall optimization goal.
Solution Approach 2:
The patent introduces a quantum calculating device as an intermediary between the resource allocation problem and the solution. This intermediary translates the classical optimization problem into quantum states, processes it through quantum operations, and returns the optimized allocation, isolating the complexity within the quantum system.
3Measurement precision
If preferences are incorporated into resource allocation optimization, then the allocation accuracy and reward maximization improve, but the problem complexity and calculation burden increase
Solution Approach 1:
The patent incorporates preferences into the graph coloring formulation before the quantum computation begins. By encoding preference information into the graph structure and edge weights in advance, the system prepares the problem in a form that the quantum algorithm can efficiently process, avoiding the need to handle preference complexity during the computational phase.
Data Source
AI summary
The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. A method performed by an apparatus of a wireless communication system is provided. The method includes receiving, from a base station, first information related to interference among a plurality of user equipments (UEs) that are to receive a resource allocation, second information related to a number of available resources, and third information related to a resource allocation reward associated with each of the plurality of user equipments (UEs), selecting a plurality of qubits based on the first information and the second information, and generating, based on the third information, resource allocation information derived from the plurality of qubits, where the resource allocation to the plurality of UEs is based on the resource allocation information.