SS-RSRQ

Synchronization Signal Reference Signal Received Quality

Physical Layer →
Introduced in Rel-15

SS-RSRQ is a 5G NR radio measurement indicating synchronization signal quality, calculated as the ratio of SS-RSRP to total received power, which provides a signal-to-interference-plus-noise metric for cell reselection and handover.

Category
Physical Layer
Introduced
Rel-15
Where
Radio Access Network › NG-RAN (5G)
Specifications
3 specs
SS-RSRQ Description Purpose Related Classification Detected Changes Specifications

Description

SS-RSRQ (Synchronization Signal Reference Signal Received Quality) is a derived radio resource management measurement in 5G NR that quantifies the quality of the received synchronization signal block. It is defined as the ratio N * SS-RSRP / (NR carrier RSSI), where N is the number of resource blocks (RBs) of the NR carrier Received Signal Strength Indicator (RSSI) measurement bandwidth. The RSSI represents the total wideband received power within the specified measurement bandwidth, including co-channel serving and non-serving cell signals, adjacent channel interference, and thermal noise. Therefore, SS-RSRQ provides a measure of how much the desired SS signal power (SS-RSRP) stands out against the total interference and noise in the channel.

From an architectural perspective, SS-RSRQ calculation occurs within the UE's physical layer and Layer 3 RRM functions. The UE first measures the SS-RSRP for a specific SSB as described in its own entry. Concurrently, or over a configured measurement period, the UE measures the total RSSI over the same carrier bandwidth used for the SS-RSRP measurement. The RSSI measurement involves sampling the total power across the entire configured measurement bandwidth. The ratio is then computed, typically resulting in a negative dB value, as the SS-RSRP (a portion of the total power) is divided by the total RSSI. This computed SS-RSRQ value is filtered to average out short-term fluctuations.

The role of SS-RSRQ in the network is complementary to SS-RSRP. While SS-RSRP indicates absolute signal strength, SS-RSRQ indicates the 'cleanness' or quality of that signal. This is particularly important in dense network deployments, such as urban macro cells or indoor small cells, where interference from neighboring cells can be significant. During cell reselection in idle mode, the UE uses criteria that can incorporate both SS-RSRP and SS-RSRQ (parameters like Qqualmeas and Qqualmin) to select the best cell, not just the strongest one. For connected mode mobility, the network can configure handover events (e.g., A5 event) that trigger based on SS-RSRQ thresholds, allowing handovers from a cell with acceptable signal strength but poor quality (high interference) to a cell with better quality. It is a key input for load balancing and interference coordination algorithms run by the RAN.

Purpose & Motivation

SS-RSRQ was introduced in 3GPP Release 15 alongside SS-RSRP to provide a standardized measure of signal quality in 5G NR. In LTE, RSRQ served a similar purpose, calculated as N * RSRP / (E-UTRA carrier RSSI). The motivation for defining an SS-based RSRQ in NR stemmed from the same architectural shift that motivated SS-RSRP: the move away from always-on CRS. Since the primary signals for initial access and mobility became the periodically transmitted SSBs, the quality measurement also needed to be based on these signals to maintain consistency and accuracy.

SS-RSRQ addresses the critical problem of interference assessment in cellular networks. A cell might have a strong SS-RSRP, but if the surrounding interference (from other cells or noise) is also very high, the actual quality of the communication link can be poor, leading to low throughput and high error rates. Relying solely on signal strength (SS-RSRP) for mobility decisions could cause a UE to camp on or handover to a heavily interfered cell. SS-RSRQ provides the necessary additional dimension to make more intelligent decisions. It solves the limitation of having only a power metric by incorporating the interference-plus-noise floor, enabling the network and UE to differentiate between a truly good cell and a strong-but-congested one. This is especially vital for the success of 5G networks, which aim for ultra-dense deployments and high spectral efficiency, where interference management is paramount.

Classification

Part ofRSSI
Related approachesSS-RSRPSS-SINR

Release Timeline

Detected Changes Across Releases

from 3GPP Change Requests

Specific changes extracted from the „Change history“ tables of 3GPP specifications (2 CRs across 2 releases). Complements the general historical overview above with the evidence-based evolution of this function.

Studied in Rel-15, normative work from Rel-17.

Rel-17 1 change

In Release 17, the primary change for SS-RSRQ involved corrections to its measurement definition alongside that of RSSI. These corrections provided greater clarity by specifying that, for measurement purposes, the UE can assume a constant downlink energy per resource element (EPRE) across the bandwidth and across different SS/PBCH blocks.

  • Corrections to SS-RSRQ and RSSI measurement definitions TS 38.215CR0043
Rel-18 1 change

In Release 18, the main update for the SS-RSRQ function was the addition of missing applicability to new test cases for Reduced Capability (RedCap) UEs. This change ensures that the standardized testing framework properly covers SS-RSRQ measurements for these new device types. The underlying technical assumptions for SS-RSRQ measurements, such as the constant EPRE across the bandwidth and the 0 dB ratio between SSS and PBCH DM-RS EPRE, remained unchanged from the previous specification.

  • Addition of missing applicability to new SS-RSRQ RedCap test cases TS 38.522CR0393

Explore further

Broader topics and technologies where SS-RSRQ plays a role.

Defining Specifications

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

SpecificationTitleRelease
TS 38.214 vj10 NR Physical Layer Procedures for Data Rel-19
TS 38.215 vj10 NR Physical Layer Measurements Rel-19
TS 38.522 vj11 UE Conformance Test Applicability Statement 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.