Dynamic Joint Power and Scheduling for Wireless Interference
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Solution Overview
Problem
Existing wireless communication systems face challenges in achieving high spectral efficiency due to inter-cell interference, which is exacerbated by static power allocation and scheduling methods, leading to complexity that hinders optimal performance.
Innovation Solution
A dynamic method and system for joint power and scheduling assignment in wireless communications networks, where a controller uses a randomization algorithm to select mobile stations, determine power allocations, and calculate global utility functions to optimize resource block assignments across cells, thereby mitigating inter-cell interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a centralized joint power control and scheduling scheme is used, then performance is improved (near optimal performance), but device complexity increases (very unlikely to be implemented)
Solution Approach 1:
The patent divides the network into autonomous eNodeBs that independently perform joint power control and scheduling decisions. Each eNodeB segments the centralized control function and makes local decisions based on interference measurements and predefined coordination rules, eliminating the need for a centralized controller while maintaining near-optimal performance.
Solution Approach 2:
The patent implements dynamic power allocation and user scheduling that adapts to changing interference conditions in real-time. Power levels and scheduling decisions are continuously adjusted based on current channel conditions and interference measurements, allowing the system to achieve near-optimal performance without centralized coordination.
2Device complexity
If static power pattern is used for each eNodeB, then device complexity is reduced, but performance deteriorates (inter-cell interference not optimally managed)
Solution Approach 1:
The patent transforms static power patterns into dynamic power allocation schemes where each eNodeB independently adjusts power levels based on real-time interference measurements and channel conditions. This dynamic adaptation enables optimal interference management while maintaining low implementation complexity through distributed decision-making.
Solution Approach 2:
The patent changes power allocation parameters dynamically based on interference conditions and user requirements. Each eNodeB independently modifies transmit power levels, resource block assignments, and user scheduling parameters to optimize spectral efficiency while managing inter-cell interference, avoiding the performance limitations of static patterns.
3Productivity
If joint power control and scheduling is implemented, then spectral efficiency is improved, but computational overhead increases (complexity makes implementation unlikely)
Solution Approach 1:
The patent segments the computationally intensive joint power control and scheduling calculations into independent eNodeB operations. Each eNodeB performs local optimization based on its own interference measurements and user conditions, eliminating the need for network-wide iterative calculations and significantly reducing computational overhead while maintaining spectral efficiency improvements.
Solution Approach 2:
Each eNodeB independently performs power control and scheduling optimizations without requiring centralized computation or extensive inter-node signaling. The eNodeBs self-service by making autonomous decisions based on local measurements and predefined coordination rules, dramatically reducing computational overhead and latency.
Data Source
AI summary
A method for dynamically determining power and scheduling assignments in a communications network includes selecting, by a controller, a mobile station in each cell to define a mobile station set, determining, by the controller, a power allocation for each of the mobile stations in the mobile station set, calculating, by the controller, a global utility function by evaluating a contribution from each of the mobile stations in the mobile station set in accordance with the power allocation, repeating, by the controller, the selecting, the determining, and the calculating steps a predetermined number of times to generate additional ones of the global utility function, and choosing, by the controller, the mobile station set corresponding to the global utility function having a particular value for a resource block of a frame. The method may also include repeatedly dividing a user set into clusters to obtain a best power allocation.