Coordinated Multiple Access for Ground-to-Air Data Transmission
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Solution Overview
Problem
The existing aeronautical broadband communication systems face challenges in meeting high-capacity demands due to limited spectrum resources and severe inter-cell interference, especially for aircraft at the cell edge.
Innovation Solution
A coordinated multiple access method for multi-cell ground-to-air data transmission is implemented, which includes constructing a model of a coordinated multiple access system, calculating transmission rates, and using a multi-agent deep reinforcement learning algorithm to optimize resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple multi-access methods (SDMA and NOMA) are combined to improve spectral efficiency, then the system capacity increases, but the interference components become complex and the problem complexity increases significantly
Solution Approach 1:
The patent segments the complex joint optimization problem into two separate sub-problems: beamforming optimization and power allocation optimization. This is achieved by introducing an auxiliary variable to represent the effective channel, which decouples the originally coupled problem into two manageable parts that can be solved alternately using alternating minimization. The beamforming problem is solved using zero-forcing methods, while the power allocation problem is solved using dynamic programming, significantly reducing overall complexity.
Solution Approach 2:
The patent introduces an auxiliary variable (effective channel) as an intermediary to decouple the joint optimization problem. This intermediary variable represents the combined effect of beamforming and channel, allowing the separation of beamforming design from power allocation. By using this intermediary, the complex coupled problem becomes two simpler problems that can be solved independently in alternating steps.
2Speed
If aircraft move at high speed requiring real-time resource allocation, then communication timeliness improves, but the algorithm computation time requirement increases
Solution Approach 1:
The patent segments the resource allocation problem into beamforming optimization and power allocation optimization that can be solved alternately. This segmentation allows each sub-problem to be solved more efficiently with lower computational complexity, enabling real-time processing even for high-speed aircraft that require frequent resource reallocation.
Solution Approach 2:
The patent employs dynamic programming for the power allocation problem, which is inherently a dynamic optimization method. This allows the algorithm to adapt to changing channel conditions in real-time as aircraft move at high speeds, optimizing power allocation dynamically without requiring complete re-computation of the entire system.
3Area of stationary object
If aircraft are located at the cell edge to expand coverage area, then the service area increases, but inter-cell interference from ground stations in other cells severely degrades transmission quality
Solution Approach 1:
The patent applies Coordinated Multiple Points (CoMP) technology that merges the transmission resources of multiple ground stations serving the same cell-edge aircraft. By coordinating beamforming across multiple ground stations, the system can jointly serve aircraft at cell edges, transforming the harmful inter-cell interference into useful signal reinforcement through coherent combining of signals from multiple stations.
Solution Approach 2:
The patent converts the harmful inter-cell interference affecting cell-edge aircraft into a benefit by using coordinated beamforming from multiple ground stations. The interference signals from neighboring cells are transformed into constructive signal components through coherent combining, improving transmission quality for cell-edge aircraft while expanding the effective coverage area.
Data Source
AI summary
The present disclosure provides a coordinated multiple access method for multi-cell ground-to-air data transmission, and belongs to the technical field of wireless communication. The method comprises the following steps: S1, constructing a model of a coordinated multiple access system for multi-cell ground-to-air data transmission; S2, calculating a transmission rate of an aircraft, and constructing a multi-cell airspace and power domain resource allocation optimization problem by taking maximizing a system transmission rate as an optimization objective; S3, constructing a Markov decision process model; S4, solving the optimization problem using a multi-agent deep reinforcement learning algorithm. The system transmission rate is maximized under the condition that the aircraft can decode the signal correctly and satisfy the constraint of minimum transmission rate, thereby realizing ground-to-air high-speed data transmission. The present disclosure adopts the coordinated multiple access method for multi-cell ground-to-air data transmission, which can realize fast online decision, satisfying the requirements of ground-to-air high-speed data transmission in the high dynamic flight scenario of the aircraft.