Massive MIMO Antenna Configuration for Energy Efficiency

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Solution Overview

Problem

Conventional methods for determining the optimal number of antennas in Massive MIMO systems are resource-intensive and time-consuming, hindering the maximization of total energy efficiency.

Innovation Solution

A central node calculates and dynamically adjusts the number of active antennas at each base station based on wireless network parameters such as fading characteristics and traffic loading, ensuring consistent energy efficiency across the network by averaging the calculated optimal numbers across multiple base stations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of energy

If brute-force search is used to determine the optimal number of antennas, then the total energy efficiency of the Massive MIMO system is maximized, but the time and computational resources consumed increase significantly

Engineering Contradiction:

Improvetotal energy efficiencyVSAvoidtime and resources for search

Core Design Contradiction:

Loss of energyVSLoss of time

Solution Approach 1:

The patent derives closed-form mathematical expressions for the optimal number of antennas based on system parameters (number of users, channel statistics, power constraints) before actual operation. This preliminary analytical solution eliminates the need for time-consuming brute-force searches during runtime, directly resolving the contradiction between energy efficiency optimization and computational time consumption

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces the mechanical iterative brute-force search process with an analytical mathematical formulation. By substituting the computational search mechanism with a closed-form solution based on channel statistics and system parameters, the method achieves energy efficiency optimization without the associated time and resource overhead

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of energy

If different numbers of antennas are activated at different base stations to optimize individual cell performance, then local energy efficiency is improved, but network-wide consistency and coordination deteriorate

Engineering Contradiction:

Improvecell energy efficiencyVSAvoidnetwork consistency

Core Design Contradiction:

Loss of energyVSStability of the object's composition

Solution Approach 1:

The patent formulates a unified network-wide optimization framework where the same analytical method is applied across all base stations. The closed-form solution uses universal system parameters (channel statistics, power constraints, user distribution) that can be consistently evaluated at each base station, ensuring network-wide consistency while optimizing energy efficiency for each cell

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent dynamically adjusts the number of active antennas at each base station based on changing system parameters such as user distribution, channel conditions, and traffic load. By using parameter-based adaptive control rather than fixed configurations, the system maintains both local energy efficiency optimization and network-wide consistency as parameters evolve

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS9781668B2Methods and apparatuses for configuring number of antennas for massive MIMO communication

Publication Date: 2017.10.03 NOKIA OF AMERICA CORP

AI summary

A central node of a Massive Multiple-Input-Multiple-Output (MIMO) system includes a processor and a transceiver. The processor is configured to determine a number of active antennas to be used to serve users in at least one cell of the Massive MIMO system based on wireless network parameters for the Massive MIMO system. The transceiver is configured to transmit the determined number of active antennas to a Massive MIMO base station in the at least one cell.