AAS

Active Antenna System

Radio Access Network →
Introduced in Rel-11 Also in: Management

AAS is a base station architecture where integrated antenna elements and active radio components allow individual control for advanced beamforming and MIMO, which is fundamental for 4G LTE-Advanced and 5G NR networks.

Category
Radio Access Network
Introduced
Rel-11
Where
Radio Access Network › NG-RAN (5G)
Also touches
1 segments
Specifications
27 specs
AAS Description Purpose Related Classification Detected Changes Specifications

Description

An Active Antenna System (AAS) represents a fundamental architectural shift in base station design, moving from traditional passive antenna arrays connected to remote radio units via coaxial cables to a fully integrated system where radiating elements, transceivers, and signal processing components are co-located within a single antenna enclosure. Unlike conventional base stations where antenna elements are passive and beamforming is performed at the baseband unit, AAS performs beamforming in the radio frequency (RF) domain through precise control of phase and amplitude at each antenna element. This integration eliminates feeder losses, reduces site footprint, and enables dynamic three-dimensional beamforming capabilities that adapt to user distribution and radio conditions in real-time.

The core architecture of an AAS consists of multiple antenna elements arranged in a two-dimensional array (typically 8x8, 16x16, or larger configurations), each connected to its own transceiver chain. Each transceiver chain includes a power amplifier (PA) for transmission, a low-noise amplifier (LNA) for reception, analog-to-digital/digital-to-analog converters (ADC/DAC), and digital front-end processing. The digital beamforming unit calculates complex weight vectors for each antenna element based on channel state information, user location, and traffic patterns. These weights adjust the phase and amplitude of signals transmitted or received by each element, creating constructive interference in desired directions and destructive interference elsewhere to form highly directional beams.

AAS operates through sophisticated signal processing algorithms that continuously optimize beam patterns. During transmission, the base station applies precoding matrices to user data streams, mapping them to specific antenna ports with calculated phase shifts. For reception, it applies combining weights to signals from multiple antenna elements to maximize signal-to-interference-plus-noise ratio (SINR). The system supports both analog beamforming (where phase shifters operate on RF signals) and hybrid beamforming (combining analog beamforming with digital precoding), with 5G implementations favoring hybrid approaches for balancing performance and complexity. Key operational modes include cell-specific beamforming for broadcast channels, user-specific beamforming for dedicated traffic, and multi-user MIMO where multiple beams serve different users simultaneously on the same time-frequency resources.

The role of AAS in modern networks extends beyond basic beamforming to enable massive MIMO (mMIMO) deployments with dozens to hundreds of antenna elements. By creating narrow, adaptive beams, AAS dramatically improves network capacity through spatial multiplexing, enhances coverage by focusing energy toward users, and reduces interference through spatial filtering. In 5G NR, AAS supports both sub-6 GHz and millimeter wave frequency bands, with different implementations optimized for each: sub-6 GHz AAS typically uses moderate element counts (32-64) for sector coverage, while mmWave AAS employs hundreds of elements to overcome high path loss through extremely directional beams. The system's digital architecture also enables advanced features like full-dimension MIMO (FD-MIMO) for elevation beamforming, beam management procedures for mobile users, and support for ultra-reliable low-latency communications through rapid beam switching.

Purpose & Motivation

AAS was developed to address critical limitations of traditional base station architectures that were becoming increasingly problematic as mobile networks evolved toward 4G and 5G. Conventional systems used passive antenna arrays with fixed radiation patterns and limited beamforming capabilities, typically supporting only 2-8 antenna ports with coarse beam tilt adjustments. These systems suffered from significant feeder losses between radio units and antennas, limited spatial processing flexibility, and inability to dynamically adapt to changing user distributions and traffic patterns. As spectral efficiency requirements increased with LTE-Advanced and network densification became necessary to meet capacity demands, these limitations became major bottlenecks for network performance.

The primary motivation for AAS creation was to enable advanced multi-antenna techniques that could dramatically improve spectral efficiency through spatial multiplexing. By integrating active components directly with antenna elements, AAS eliminates feeder losses that typically account for 2-3 dB signal degradation, directly improving coverage and energy efficiency. More importantly, it enables precise electronic control of each antenna element's radiation pattern, allowing base stations to form multiple simultaneous beams that can track individual users or user groups. This capability is essential for implementing massive MIMO systems, which theoretical studies showed could multiply network capacity by an order of magnitude through spatial domain multiplexing.

Historically, AAS development was driven by the need to support LTE-Advanced features like 8-layer spatial multiplexing and coordinated multipoint transmission, which required more sophisticated antenna systems than traditional passive arrays. The technology gained further importance with 5G NR, which relies on beam-based operations especially in millimeter wave bands where high path loss necessitates highly directional beams for adequate coverage. AAS solves the practical deployment challenges of massive MIMO by integrating all necessary components into compact, energy-efficient units that can be deployed on existing sites without requiring extensive additional space or structural modifications. It also addresses operational complexity through self-calibration and self-optimization capabilities that maintain beamforming accuracy over temperature variations and component aging.

Classification

Part ofMIMO
Specific typesCSAPTFRCSATABULA

Release Timeline

Detected Changes Across Releases

from 3GPP Change Requests

Specific changes extracted from the „Change history“ tables of 3GPP specifications (28 CRs across 5 releases). Complements the general historical overview above with the evidence-based evolution of this function.

Rel-15 11 changes

In Release 15, the AAS function introduced new Self-Optimization (SON) capabilities to manage AAS operations like Cell Splitting, Cell Merging, and Cell Shaping with minimal human intervention. Specifically, it defined requirements for the OAM system to automatically configure, pre-allocate identifiers like ECGI and PCI, and notify the operator of newly created or merged cells. This enabled automated and adaptive network optimization through software reconfiguration of the Active Antenna System.

  • Add SON for AAS management requirements TS 28.627CR0014
  • Add SON for AAS deployment management description and attributes TS 28.628CR0016
  • CR to TS 37.105: AAS RF specification, v15.0.0 TS 37.105CR0073
  • CR to TS 37.114: NR introduction into AAS EMC specification TS 37.114CR0067
  • Correction of AAS IP Throughput load rate definition TS 28.628CR0017
  • Corrections to AAS receiver requirements for NR TS 37.105CR0099

+ 5 more changes

Rel-16 4 changes

In Release 16, the new AAS function introduced Self-Optimization for AAS (SO_AAS_F) to automate key Active Antenna System operations like Cell Splitting, Cell Merging, and Cell Shaping. It specified new management capabilities for the IRPAgent, such as allowing the IRPManager to pre-configure ECGI and PCI ranges for potential split or merged cells and to receive automatic notifications upon their creation. This enabled automated, software-driven reconfiguration of base station coverage with minimal human intervention.

  • CR to TS 37.105: Rel-15 non-AAS CRs mirroring, Rel-15 TS 37.105CR0197
  • CR to TS 37.105: Rel-13 non-AAS CRs mirroring, Rel-16 TS 37.105CR0191
  • CR to TS 37.105: Rel-14 non-AAS CRs mirroring, Rel-16 TS 37.105CR0194
  • CR to TS 37.105: Rel-15 non-AAS CRs mirroring, Rel-16 TS 37.105CR0196
Rel-17 2 changes

In Release 17, the AAS function introduced new Self-Optimization Network (SON) management requirements for automated AAS operations like Cell Splitting, Cell Merging, and Cell Shaping. Key enhancements included the ability for an operator to pre-configure ECGI and PCI ranges for potential split/merged cells and to be notified automatically upon their creation. Additionally, the release specified that AAS Base Station (BS) testing, including Over-The-Air (OTA) and spurious emissions limits for co-existence, was updated.

  • CR to TS 37.114 AAS BS test configuration R15 TS 37.114CR0100
  • CR to 37.145-2 to modify AAS BS OTA Spurious emissions limits for co-existence with systems operating in other frequency bands in R17 TS 37.145CR0302
Rel-18 8 changes

In Release 18, the key new AAS function introduced was the Self-Optimization for AAS Function (SO_AAS_F), which automates AAS operations like Cell Splitting, Cell Merging, and Cell Shaping with minimal human intervention. This function provides specific OAM capabilities, allowing an operator to pre-configure parameters such as ECGI and PCI ranges for potential cells and to receive automatic notifications upon cell creation. Additionally, the release included updates to testing and declaration frameworks in TS 37.114 and corrections to requirements in TS 37.105 and TS 37.145-2.

  • CR to TS 37.114: Implementation of AAS BS testing simplifications, Rel-18 TS 37.114CR0109
  • (AAS_BS_LTE_UTRA-Core) Correction of reference to Suspended version of ITU-R SM.329 Recommendation TS 37.105CR0297
  • [AAS_BS_LTE_UTRA-Core, TEI18] CR to TS 37.114: framework for the EMC-specific manufacturer's declarations, Rel-18 TS 37.114CR0108
  • (AAS_BS_LTE_UTRA-Core) Correction of reference to Suspended version of ITU-R SM.329 Recommendation TS 37.114CR0113
  • (AAS_BS_LTE_UTRA-Perf) Correction of reference to Suspended version of ITU-R SM.329 Recommendation TS 37.145CR0392
  • (AAS_BS_LTE_UTRA-Core) CR to TS 37.105: Correction of OBUE requirement applicability in Table 6.6.5.2.2-0 TS 37.105CR0286

+ 2 more changes

Rel-19 3 changes

In Release 19, the AAS function introduced new Self-Optimization (SON) management requirements to automate operations like Cell Splitting, Cell Merging, and Cell Shaping. Specifically, it defined capabilities for an IRPAgent to allow an IRPManager to pre-configure parameters like ECGI and PCI ranges for potential cells and to switch these AAS operations on or off. Concurrently, the release removed specifications related to UTRA TDD from the Multi-Standard Radio (MSR) Base Station specifications for AAS.

  • (AAS_BS_LTE_UTRA-Core,TEI17) CR to 37.105: Removal of UTRA TDD from MSR BS specifications TS 37.105CR0316
  • (AAS_BS_LTE_UTRA,TEI17) CR to 37.145-2: Removal of UTRA TDD from MSR BS specifications TS 37.145CR0414
  • (AAS_BS_LTE_UTRA-Perf) CR to TS 37.145-2: removal of outstanding FFS TS 37.145CR0397

Explore further

Broader topics and technologies where AAS plays a role.

Defining Specifications

3GPP specifications that define or reference AAS, with the latest known release. Sourced from the 3GPP document catalog — see methodology.

SpecificationTitleRelease
TS 28.627 vj00 SON Policy NRM IRP: Requirements Rel-19
TS 28.628 vj00 SON Policy NRM IRP Information Service Rel-19
TS 28.861 vg00 SON for 5G Networks Management Rel-16
TS 32.865 vf00 OAM Aspects of SON for AAS-Based Deployments Rel-15
TS 36.181 vj30 E-UTRA RF Test Methods for Satellite Access Node Rel-19
TS 37.105 vj10 AAS Base Station Transmission & Reception Requirements Rel-19
TS 37.114 vj00 EMC for Active Antenna System Base Stations Rel-19
TS 37.145 vj10 AAS Base Station Conducted Conformance Testing Rel-19
TS 37.808 vc00 PIM Handling for Base Stations Study Rel-12
TS 37.810 vc20 Study on Base Station Specification Structure Rel-12
TS 37.816 vg00 RAN-centric Data Collection & Utilization Study Rel-16
TS 37.822 vc10 SON Enhancements for UE Types and Active Antennas Rel-12
TS 37.840 vc10 RF & EMC Requirements for Active Antenna Systems Rel-12
TS 37.842 vd30 BS RF Requirements for Active Antenna Systems Rel-13
TR 37.843 vf70 AAS BS Radiated RF Requirement Background Rel-15
TR 37.941 vj20 RF Conformance Testing Background for Radiated BS Requirements Rel-19
TS 38.104 vj20 NR Base Station RF Requirements Rel-19
TS 38.141 vj20 NR Base Station RF Conformance Testing Part 1 Rel-19
TS 38.181 vj10 NR Satellite Access Node RF Testing Rel-19
TS 38.817 3GPP TR 38.817 Rel-11
TR 38.820 vg10 NR; 7-24 GHz Frequency Range Study Rel-16
TR 38.852 vh50 1900MHz NR band for European Rail Mobile Radio Rel-17
TR 38.853 vh50 900MHz NR Band for European Rail Mobile Radio Rel-17
TR 38.877 vi10 Technical Report Rel-18
TR 38.912 vj00 Study on New Radio Access Technology Rel-19
TR 38.921 vj00 IMT Parameters Study for 6.4-7.1 & 10-10.5 GHz Rel-19
TR 38.922 vj20 Study on IMT Parameters for NR in Higher Bands Rel-19
Patrick Zandl

About the author: Patrick Zandl (b. 1974)

Telecommunications specialist, technology journalist (founder of the Mobil server), and developer who has been running since 2025 — the largest Czech-language resource on AI-assisted programming. Formerly Chief Wizard Architect at Prusa3D and head of development for Turris at CZ.NIC; currently a consultant and instructor on AI implementation in companies.