NOMA Power Allocation via KKT Sum Capacity Maximization
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Solution Overview
Problem
Current power allocation algorithms for non-orthogonal multiple access (NOMA) systems, particularly in MIMO-NOMA with two users, face challenges in achieving high efficiency and performance due to high computational complexity and performance loss, lacking an ideal evaluation criterion.
Innovation Solution
A method for power allocation in a base station that sets transmit powers for user equipment based on maximizing sum capacity using Karush-Kuhn-Tucker (KKT) conditions, ensuring one user's system capacity meets a minimum rate requirement while maximizing the other's, with specific parameters for power allocation factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bisection search method is used for power allocation, then optimal performance is achieved, but computational complexity increases
Solution Approach 1:
The patent transforms the power allocation problem from an iterative optimization approach to a direct calculation method by changing the parameter representation. Instead of using power values directly in iterative search, the patent introduces power allocation factors as intermediate parameters, enabling closed-form solution through KKT conditions while maintaining optimal performance.
2Device complexity
If suboptimal method with lower bound is used, then computational complexity is reduced, but performance loss occurs
Solution Approach 1:
The patent introduces power allocation factors as intermediary variables that bridge the gap between total power constraint and individual user power requirements. These factors serve as mediators that enable direct calculation of optimal power distribution without iterative search or approximation, thus avoiding both high complexity and performance loss.
3Reliability
If power allocation is optimized for one user, then that user's capacity is maximized, but system sum capacity may not be maximized
Solution Approach 1:
The patent changes the optimization parameters from individual user power values to power allocation factors that inherently represent the distribution proportion. By formulating the objective function in terms of sum capacity maximization with KKT conditions, the solution automatically balances individual user capacities with overall system efficiency, eliminating the need to choose between individual and system optimization.
Data Source
AI summary
The disclosure proposes a method of power allocation and a base station using the method. The method is applicable to a base station for transmitting information signals to at least two user equipments in a non-orthogonal multiple access (NOMA) system. The method includes: setting a first transmit power of a first user equipment to be smaller than a second transmit power of a second user equipment, where a channel gain of the first user equipment is larger than that of the second user equipment; calculating a first system capacity of the first user equipment according to the first transmit power, and calculating a second system capacity of the second user equipment according to the second transmit power; summing the first system capacity and the second system capacity to obtain a sum capacity; and calculating the first transmit power and the second transmit power based on maximizing the sum capacity.