Distributed Non-Convex Beamforming for Inter-Cell Interference
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Solution Overview
Problem
Existing wireless cellular networks face limitations in optimizing wireless communication due to inter-cell interference, which reduces spectral efficiency and throughput, especially when inter-cell interference is not adequately mitigated in current beamforming designs.
Innovation Solution
The system employs distributed non-convex optimization across multiple base stations to determine optimal linear beamforming vectors and precoders that account for inter-cell interference, using Karush-Kuhn-Tucker equations and leakage matrices to maximize weighted sum-rate, while managing power constraints and channel estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed non-convex optimization is used to determine optimal beamforming vectors, then spectral efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent divides the network into multiple cells, each handled by a separate base station performing local optimization. This segmentation allows the global optimization problem to be broken into manageable local problems, reducing computational complexity while maintaining spectral efficiency improvements through coordinated beamforming across cells.
Solution Approach 2:
The patent transforms the non-convex optimization problem into a convex form by changing parameters through successive convex approximation. This allows the use of efficient convex optimization algorithms to achieve near-optimal beamforming vectors, reducing computational complexity while maintaining high spectral efficiency.
2Object-affected harmful factors
If coordinated processing across multiple cells is implemented, then inter-cell interference is reduced, but network infrastructure complexity increases
Solution Approach 1:
The patent segments the coordinated processing into cell-level operations where each base station independently optimizes its beamforming vectors based on local channel state information and interference conditions. This reduces network infrastructure complexity by avoiding centralized coordination while still mitigating inter-cell interference through distributed optimization.
Solution Approach 2:
Each base station performs self-service optimization by locally determining its beamforming vectors to minimize interference to other cells while maximizing its own spectral efficiency. This distributed self-service approach reduces the need for complex centralized coordination infrastructure while effectively managing inter-cell interference.
3Productivity
If beamforming vectors are optimized based on inter-cell channel qualities, then throughput is improved, but information sharing requirements increase
Solution Approach 1:
The patent extracts only the essential information needed for beamforming optimization—channel quality indicators and interference measurements—from the full channel state information. This selective extraction reduces information sharing requirements between cells while maintaining throughput improvements through optimized beamforming vectors.
Solution Approach 2:
The patent transforms detailed channel state information into simplified parameters such as channel quality indicators and signal-to-interference-plus-noise ratios. These transformed parameters require less information sharing bandwidth while still enabling effective beamforming optimization and throughput improvement across cells.
Data Source
AI summary
System and methods are disclosed for optimizing wireless communication for a plurality of mobile wireless devices. The system uses beamforming vectors or precoders having a structure optimal with respect to the weighted sum rate in a multi-cell orthogonal frequency division multiple access (OFDMA) downlink. A plurality of base stations communicate with the mobile devices and all base stations perform a distributed non-convex optimization exploiting the determined structure.