MIMO-OFDMA Resource Allocation via Diagonal Matrix Decomposition
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Solution Overview
Problem
Current radio resource allocation methods for downlink mobile MIMO-OFDMA systems face challenges in balancing capacity and computation complexity, requiring a more efficient approach to allocate transmission power and subcarrier fractions while handling critical mobile channel conditions.
Innovation Solution
A novel method and system that utilize a proposed channel equalization scheme and resource allocation algorithm with linear complexity, involving matrix operations to generate a diagonal matrix, and a modified water-filling optimal power allocation scheme, to maximize sum capacity by determining transmission powers and subcarrier fractions efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional radio resource allocation methods are used to increase system capacity, then capacity improves, but computation complexity increases
Solution Approach 1:
The patent segments the radio resource allocation problem into two independent stages: first allocating subcarrier fractions to users, then allocating transmission powers across subcarriers. This segmentation transforms the complex joint optimization problem into simpler sequential problems, reducing computation complexity while maintaining high system capacity. The diagonal matrix decomposition further simplifies the channel matrix operations in each stage.
Solution Approach 2:
The patent introduces parameter transformations by converting the channel matrix into a diagonal matrix through unitary transformations. This parameter change simplifies the capacity calculation and optimization processes. Additionally, the patent uses water-filling power allocation and linear programming techniques to efficiently determine optimal transmission powers and subcarrier fractions, reducing computational burden while maximizing capacity.
2Productivity
If more sophisticated allocation algorithms are implemented to handle mobile channel conditions, then capacity improves, but computation time increases
Solution Approach 1:
The patent performs preliminary actions by pre-computing the diagonal matrix from the channel matrix and determining subcarrier fractions before final power allocation. This preliminary processing simplifies subsequent computations and reduces overall computation time. The diagonal matrix decomposition is performed once and reused in the power allocation stage, avoiding redundant calculations.
Solution Approach 2:
The patent replaces complex iterative optimization methods with more efficient mathematical techniques. Specifically, it uses diagonal matrix decomposition and water-filling algorithms that have closed-form solutions or converge faster than traditional iterative methods. The linear programming approach for subcarrier fraction allocation also provides more efficient computation compared to conventional methods.
Data Source
AI summary
This patent discloses a method and a system of radio resource allocation for a mobile MIMO-OFDMA system, the method comprising the steps of: generating a diagonal matrix according to a channel matrix; determining a sum capacity function associated with the diagonal matrix, a plurality of transmission powers, and a plurality of subcarrier fractions; performing a first subcarrier fraction allocation by maximizing the sum capacity function according to a predetermined user capacity condition; performing a first transmission power allocation according to the first subcarrier allocation; and performing a second subcarrier fraction allocation by maximizing the sum capacity function according to the first transmission power allocation and the predetermined user capacity condition.