Discrete Power Allocation for NOMA Systems

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Existing NOMA systems face challenges in optimizing discrete power allocation, which affects energy efficiency and fairness among users due to inter-user interference and the complexity of solving non-convex combinatorial formulations.

Innovation Solution

A fairness-aware power allocation algorithm that maximizes energy efficiency by imposing a throughput-fairness constraint using a weighted Jain's fairness index, while constraining power levels to discrete values, thereby reducing computational complexity and enabling practical implementation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by moving object

If continuous power allocation is used to optimize NOMA system performance, then energy efficiency is improved, but hardware implementation complexity increases and cost increases

Engineering Contradiction:
Improveenergy efficiencyVSAvoidhardware implementation complexity
Core Design Contradiction:
Use of energy by moving objectVSDevice complexity

Solution Approach 1:

The patent transforms the continuous power allocation parameter into discrete power levels. By changing the parameter domain from continuous to discrete, the system achieves near-optimal energy efficiency while enabling practical hardware implementation with reduced complexity and cost.

Inventive Principle:
Principle #35Parameter changes

Solution Approach 2:

The patent adopts discrete power levels that are easier and cheaper to implement in practical hardware. Instead of requiring precise continuous power control, the system uses aĉœ‰é™ set of discrete power levels that can be implemented with simpler circuitry, reducing hardware cost and complexity.

Inventive Principle:
Principle #27Cheap short-living objects (Disposable)

2Device complexity

If discrete power allocation is used to simplify hardware design, then device complexity is reduced, but energy efficiency optimization capability deteriorates

Engineering Contradiction:
Improvehardware implementation complexityVSAvoidenergy efficiency
Core Design Contradiction:
Device complexityVSUse of energy by moving object

Solution Approach 1:

The patent carefully selects discrete power levels that are strategically chosen to maximize energy efficiency within the discrete domain. By optimizing the discrete power level selection rather than simply rounding continuous solutions, the system recovers most of the energy efficiency performance while maintaining hardware simplicity.

Inventive Principle:
Principle #35Parameter changes

3Measurement precision

If exhaustive search is used to solve discrete power allocation optimization, then optimality is achieved, but computational complexity increases

Engineering Contradiction:
ImproveoptimalityVSAvoidcomputational complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the power allocation problem by fixing the power levels and optimizing only the power distribution among users. This segmentation transforms the combinatorial optimization problem into a more tractable form that can be solved efficiently while still achieving optimal or near-optimal results.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent applies partial optimization by focusing on optimizing power allocation given fixed discrete power levels, rather than exhaustively searching all possible discrete power level combinations. This partial action approach achieves sufficient optimality with much reduced computational complexity.

Inventive Principle:
Principle #16Partial or excessive action

4Ease of manufacture

If rounding is used to convert continuous power solutions to discrete values, then implementation simplicity is improved, but power allocation accuracy deteriorates

Engineering Contradiction:
Improveimplementation simplicityVSAvoidpower allocation accuracy
Core Design Contradiction:
Ease of manufactureVSManufacturing precision

Solution Approach 1:

The patent changes the optimization approach from rounding continuous solutions to directly optimizing discrete power levels. By formulating the optimization problem in the discrete domain from the beginning, the system avoids accuracy loss while maintaining implementation simplicity.

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP3847855B1Discrete power allocation for non-orthogonal multiple access systems
Publication Date: 2025.04.16 TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)
  • EP3847855B1 patent drawingFigure 1
  • EP3847855B1 patent drawingFigure 2
  • EP3847855B1 patent drawingFigure 3

AI summary

Apparatuses and corresponding methods for discrete power allocation for a non-orthogonal multiple access, NOMA, system are provided. A set of discrete power allocation values is determined. Each power allocation value is assigned to a particular wireless device, WD, in a set of WDs. The determining includes subjecting the power allocation values to at least one constraint to reduce a number of power allocation value combinations. A plurality of superimposed data signals are transmitted to the WDs in the set. Each data signal is intended for a different one of the WDs in the set and has a different power allocation value. Each WD in the set receives all the plurality of superimposed data signals. A different control signal is transmitted to each WD in the set of WDs. The control signal includes an indication of the power level allocation values of the set of discrete power allocation values.