OFDM numerology is the configuration of subcarrier spacing (SCS) and cyclic prefix (CP) length that defines the fundamental time-frequency grid of a 5G NR transmission. Unlike LTE's fixed 15 kHz SCS, 5G NR introduces a scalable numerology with SCS values derived by multiplying 15 kHz by powers of two (15, 30, 60, 120, and 240 kHz), enabling the waveform to adapt to diverse spectrum allocations from sub-1 GHz to millimeter-wave bands.
Glossary
OFDM Numerology

What is OFDM Numerology?
OFDM numerology defines the scalable set of physical-layer parameters—specifically subcarrier spacing and cyclic prefix duration—that determine the frame structure of a 5G New Radio (NR) waveform for different frequency ranges and deployment scenarios.
The choice of numerology directly governs the slot duration, symbol length, and cyclic prefix overhead, creating a trade-off between latency and spectral efficiency. Wider subcarrier spacings produce shorter symbol periods, reducing latency for ultra-reliable low-latency communication (URLLC) but increasing CP overhead. Narrower spacings maximize efficiency for enhanced mobile broadband (eMBB) in macro-cell deployments. Multiple numerologies can coexist on the same carrier through bandwidth parts (BWPs).
5G NR Numerology Configurations (μ Values)
Comparison of physical-layer parameters for each 5G NR numerology index (μ), defining subcarrier spacing, slot duration, and cyclic prefix characteristics across frequency ranges and use cases.
| Parameter | μ = 0 | μ = 1 | μ = 2 | μ = 3 | μ = 4 |
|---|---|---|---|---|---|
Subcarrier Spacing (Δf) | 15 kHz | 30 kHz | 60 kHz | 120 kHz | 240 kHz |
OFDM Symbol Duration (useful part) | 66.67 μs | 33.33 μs | 16.67 μs | 8.33 μs | 4.17 μs |
Slot Duration | 1 ms | 0.5 ms | 0.25 ms | 0.125 ms | 0.0625 ms |
Slots per Subframe (1 ms) | 1 | 2 | 4 | 8 | 16 |
Slots per Radio Frame (10 ms) | 10 | 20 | 40 | 80 | 160 |
OFDM Symbols per Slot | 14 | 14 | 14 | 14 | 14 |
Normal CP Length (symbol 0) | 5.2 μs | 2.86 μs | 1.69 μs | 1.11 μs | 0.81 μs |
Normal CP Length (symbols 1-6) | 4.69 μs | 2.34 μs | 1.17 μs | 0.59 μs | 0.29 μs |
Maximum Carrier Bandwidth | 50 MHz | 100 MHz | 200 MHz | 400 MHz | 400 MHz |
Applicable Frequency Range | FR1 (sub-6 GHz) | FR1 (sub-6 GHz) | FR1 & FR2 | FR2 (mmWave) | FR2 (mmWave) |
Extended CP Supported | |||||
Typical Use Case | Wide-area coverage, LTE coexistence | Urban macro, enhanced MBB | Dense urban, low-latency URLLC | mmWave hotspots, fixed wireless | Ultra-low latency, short-range |
Phase Noise Sensitivity | Low | Low | Moderate | High | Very High |
Doppler Resilience | Low | Moderate | High | Very High | Very High |
How OFDM Numerology Scaling Works
OFDM numerology defines the scalable physical-layer parameters—subcarrier spacing and cyclic prefix duration—that allow a unified waveform to adapt to diverse 5G NR frequency ranges and service requirements.
OFDM numerology scaling is the mechanism by which 5G NR adapts a single waveform framework across sub-1 GHz to millimeter-wave bands. The fundamental scaling principle is $\Delta f = 2^\mu \cdot 15$ kHz, where $\mu \in {0,1,2,3,4}$ is the numerology index. As subcarrier spacing doubles, the OFDM symbol duration halves proportionally, preserving the time-frequency resource grid structure while enabling latency reduction for higher frequencies.
Each numerology pairs a specific subcarrier spacing with a corresponding cyclic prefix (CP) length to maintain multipath resilience. Wider subcarrier spacings use shorter CPs, suited for small-cell deployments with limited delay spread. This scaling also determines the slot duration—from 1 ms at 15 kHz to 0.0625 ms at 240 kHz—allowing the frame structure to support both enhanced mobile broadband and ultra-reliable low-latency communication services within a single radio interface.
Key Characteristics of OFDM Numerology
OFDM numerology defines the scalable physical-layer parameters—subcarrier spacing and cyclic prefix—that adapt the 5G NR air interface to diverse spectrum and use cases.
Frequently Asked Questions
Clear answers to common questions about the scalable physical-layer parameters that define 5G NR frame structures, subcarrier spacing, and cyclic prefix configurations.
OFDM numerology defines the set of scalable physical-layer parameters—primarily subcarrier spacing (SCS) and cyclic prefix (CP) duration—that determine the frame structure of an Orthogonal Frequency-Division Multiplexing transmission. In 5G New Radio (NR), numerology is the foundational design principle that enables a single air interface to support diverse use cases across vastly different frequency ranges. Unlike 4G LTE, which uses a fixed 15 kHz SCS, 5G NR introduces a scalable numerology indexed by μ (mu), where SCS = 15 × 2^μ kHz. This scaling allows the OFDM symbol duration to halve with each increment of μ, making the waveform adaptable: lower numerologies (μ=0, 15 kHz) provide long symbol durations ideal for wide-area coverage, while higher numerologies (μ=3, 120 kHz) produce short symbols suited for low-latency applications in millimeter-wave bands. The cyclic prefix scales inversely, maintaining a consistent CP overhead of approximately 7% per slot. This parametric flexibility is what allows 5G NR to simultaneously serve enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC) on a unified waveform.
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Related Terms
The 5G NR scalable numerology framework is defined by its interaction with synchronization, resource allocation, and waveform generation parameters. These related concepts form the operational context for subcarrier spacing and cyclic prefix selection.
Bandwidth Part (BWP)
A contiguous subset of carrier resource blocks configured in 5G NR to enable bandwidth adaptation. Each BWP can have its own numerology, allowing a UE to switch between wideband operation with high subcarrier spacing for data and narrowband operation with lower subcarrier spacing for power saving.
- Up to 4 BWPs per serving cell
- Each BWP independently configures μ and CP type
- Enables dynamic numerology switching without re-establishment
Resource Block Grid
The two-dimensional time-frequency lattice that materializes the numerology. One resource block spans 12 subcarriers in frequency and 14 OFDM symbols in time (for normal CP). The absolute bandwidth of an RB scales inversely with subcarrier spacing:
- μ=0 (15 kHz): 180 kHz RB bandwidth, 1 ms slot
- μ=1 (30 kHz): 360 kHz RB bandwidth, 0.5 ms slot
- μ=3 (120 kHz): 1440 kHz RB bandwidth, 0.125 ms slot
Synchronization Signal Block (SSB)
The 5G NR downlink burst composed of PSS, SSS, and PBCH DMRS transmitted in a beam-swept manner. SSB periodicity and time-domain mapping are defined relative to the numerology, with the SSB pattern within a half-frame varying by subcarrier spacing to ensure compatibility across frequency ranges.
- FR1 (μ=0,1): SSB mapped to specific OFDM symbol indices
- FR2 (μ=2,3): Different mapping to accommodate wider beams
- SSB detection is the first step in deriving cell numerology
CP-OFDM vs DFT-s-OFDM
The two waveform variants governed by numerology selection. CP-OFDM is the baseline downlink waveform supporting MIMO and high spectral efficiency. DFT-s-OFDM applies a discrete Fourier transform precoding step to reduce peak-to-average power ratio (PAPR) for uplink coverage-limited scenarios.
- Both waveforms share the same numerology structure
- DFT-s-OFDM restricted to single-layer transmission
- Transform precoding enabled/disabled per BWP configuration
Phase Tracking Reference Signal (PTRS)
A 5G NR reference signal specifically designed to compensate for phase noise from local oscillators at high carrier frequencies. PTRS density in time and frequency is a function of the scheduled MCS and the configured subcarrier spacing, with denser patterns at higher numerologies (μ≥2) to track rapid phase variations in millimeter wave bands.
- Time density: every 1, 2, or 4 OFDM symbols
- Frequency density: every 2 or 4 resource blocks
- Critical for FR2 operation above 24 GHz

About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
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