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Toward Native ISAC Support in O-RAN Architectures for 6G

Eduardo Baena, Rajesh Krishnan, Mai Vu, Gil Zussman, Dimitrios Koutsonikolas

TL;DR

This article proposes three extensions to O-RAN for monostatic sensing, where transmission and reception are co-located at the base station and defines E2SM-SENS, a service model enabling xApps to subscribe to sensing telemetry with configurable periodicity.

Abstract

ISAC is an emerging paradigm in 6G networks that enables environmental sensing using wireless communication infrastructure. Current O-RAN specifications lack the architectural primitives for sensing integration: no service models expose physical-layer observables, no execution frameworks support sub-millisecond sensing tasks, and fronthaul interfaces cannot correlate transmitted waveforms with their reflections. This article proposes three extensions to O-RAN for monostatic sensing, where transmission and reception are co-located at the base station. First, we specify sensing dApps at the O-DU that process IQ samples to extract delay, Doppler, and angular features. Second, we define E2SM-SENS, a service model enabling xApps to subscribe to sensing telemetry with configurable periodicity. Third, we identify required Open Fronthaul metadata for waveform-echo association. We validate the architecture through a prototype implementation using beamforming and Full-Duplex operation, demonstrating closed-loop control with median end-to-end latency suitable for near-real-time sensing applications. While focused on monostatic configurations, the proposed interfaces extend to bistatic and cooperative sensing scenarios.

Toward Native ISAC Support in O-RAN Architectures for 6G

TL;DR

This article proposes three extensions to O-RAN for monostatic sensing, where transmission and reception are co-located at the base station and defines E2SM-SENS, a service model enabling xApps to subscribe to sensing telemetry with configurable periodicity.

Abstract

ISAC is an emerging paradigm in 6G networks that enables environmental sensing using wireless communication infrastructure. Current O-RAN specifications lack the architectural primitives for sensing integration: no service models expose physical-layer observables, no execution frameworks support sub-millisecond sensing tasks, and fronthaul interfaces cannot correlate transmitted waveforms with their reflections. This article proposes three extensions to O-RAN for monostatic sensing, where transmission and reception are co-located at the base station. First, we specify sensing dApps at the O-DU that process IQ samples to extract delay, Doppler, and angular features. Second, we define E2SM-SENS, a service model enabling xApps to subscribe to sensing telemetry with configurable periodicity. Third, we identify required Open Fronthaul metadata for waveform-echo association. We validate the architecture through a prototype implementation using beamforming and Full-Duplex operation, demonstrating closed-loop control with median end-to-end latency suitable for near-real-time sensing applications. While focused on monostatic configurations, the proposed interfaces extend to bistatic and cooperative sensing scenarios.
Paper Structure (20 sections, 4 figures, 2 tables)

This paper contains 20 sections, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Background and Related Work
  3. ISAC Sensing Configurations
  4. O-RAN Architecture Overview
  5. Related Work
  6. Challenges and Use Cases
  7. Challenges
  8. Use Cases and Requirements
  9. Architectural Integration of ISAC in O-RAN
  10. Real-Time Execution at the DU: dApps for ISAC
  11. Control Plane Models: E2SM-SENS and A1 ISAC Policies
  12. Data Plane and O-FH Requirements for Sensing
  13. Multi-Layer Control Integration
  14. Conceptual Example: ISAC with MU-MIMO Beamforming and Full-Duplex
  15. Implementation and Evaluation
  16. ...and 5 more sections

Figures (4)

  • Figure 1: Closed-loop sensing control via E2SM-SENS: upward KPI telemetry and downward configuration commands.
  • Figure 2: Hierarchical ISAC control integration in O-RAN.
  • Figure 3: PAAM dApp coordination with FD-enabled RU under the ISAC xApp.
  • Figure 4: Experimental validation ( 35k samples): (a) on-demand periodicity control showing 100$\rightarrow$20$\rightarrow$10 ms transitions; (b) telemetry latency ($t_1 - t_0$) CDF at 10 ms period vs. use case thresholds; (c) closed-loop latency breakdown showing telemetry and control components.