PaperlayerView exact revision on arXiv

Source-linked AI summary

From Open RAN to Open Spectrum: A Programmable, Intelligent Architecture for Multi-Service Spectrum Coexistence

Michele Polese, Minh Dat Nguyen, Paolo Testolina, Tommaso Melodia

arXiv:2609.11843v1cs.NIeess.SP

TL;DR

Spectrum-sharing frameworks often allocate spectrum without coordinating the infrastructure and service requirements that spectrum-enabled systems also need. Open Spectrum combines spectrum, services, and infrastructure in a common pool coordinated by the SIC, with sApps and DT-based RFI modeling. Simulations report infrastructure-sharing incentives and up to 12 dB improvement in median SINR for services with cellular-like RF parameters.

  • Problem

    Spectrum-only sharing frameworks do not coordinate the infrastructure and service requirements needed by diverse services, while unlicensed access does not guarantee protection for services sensitive to RFI.

    Source: §I · p. 1

  • Method

    Open Spectrum jointly shares spectrum, services, and infrastructure through a programmable SIC, modular sApps, and DT-based RFI modeling.

    Source: §I · p. 2, A. Spectrum Intelligence Controller · p. 3

  • Results

    Services with cellular-like RF parameters gain up to 12 dB in median SINR, and coordinated scheduling reclaims idle time-frequency resources without degrading incumbent QoS.

    Source: §I · p. 2

  • Takeaways & Limitations

    Sparse services can gain access to dense infrastructure, while telecom operators can dynamically extend their spectrum footprint through sharing.

    Source: §I · p. 2

    The simulations validate quantitative premises using the SIC's DT component, not end-to-end operation of the SIC, sApps, or DT feedback loop.

    Source: §V · p. 4

Abstract

from arXiv · show

Considering sharing or coexistence from the perspective of spectrum alone fails to recognize that any spectrum-enabled service also requires (i) radio and processing infrastructure and (ii) a protocol stack, including waveforms and signal processing pipelines. The efficiency of spectrum coexistence frameworks such as Citizen Broadband Radio Service (CBRS) is thus limited to optimizing resource allocation across a single dimension. How to address this limitation, however, remains an open challenge, especially considering the diversity of requirements and operational modes across spectrum services (e.g., sensing, communications, navigation, or positioning). This article introduces Open Spectrum, an architecture that brings softwarization, programmability, and open interfaces to heterogeneous spectrum services, extending the open Radio Access Network (RAN) principles beyond wireless networking. We propose to combine spectrum, services, and infrastructure in a common pool. Its resources are shared and orchestrated by a Spectrum Intelligent Controller (SIC), with plug-and-play spectrum applications, i.e., Spectrum Applications (sApps), and data-driven Radio-Frequency Interference (RFI) modeling using Digital Twins (DTs). We describe the Open Spectrum architecture, shared infrastructure pool, and operational workflows for tenant onboarding and incentives, conflict resolution, and service sharing across sensing, radionavigation, radiolocation, and cellular systems. System-level simulations using the BostonTwin urban DT and Sionna ray tracing show that there exist performance-driven incentives in sharing infrastructure and sharing across multiple services, enabling increased access to spectrum and improvement in median Signal to Interference plus Noise Ratio (SINR) of up to 12 dB.

I. INTRODUCTION

Open Spectrum addresses the limits of spectrum-only sharing by jointly coordinating spectrum, infrastructure, and services. The article reports gains from joint sharing and situates the architecture against prior work limited by pairwise coordination, spectrum-only sharing, and incompatible service-specific resource models.

I. INTRODUCTION

  • Exclusive licensing and unlicensed access inadequately serve dynamic spectrum needs and services sensitive to RFI, while spectrum-only frameworks cannot coordinate the infrastructure and services that use spectrum.For example, a CBRS SAS can grant frequency access but cannot provide a radar operator with dense infrastructure or coordinate shared radio hardware.Source: §I · p. 1
  • Open Spectrum extends common-pool governance to spectrum, infrastructure, and waveform sharing, creating incentives for sparse services and telecom operators to share resources.Sparse services gain access to dense infrastructure, while telecom operators can dynamically extend their spectrum footprint.Source: §I · p. 2
  • A closed control loop exposes spectrum and infrastructure telemetry, generates service-level policies beyond RFI, and enforces allocations on programmable radio infrastructure.The shared infrastructure also supports granular conflict resolution and simultaneous delivery of multiple spectrum services on the same hardware and programmable basebands.Source: §I · p. 2
  • Services with cellular-like RF parameters gain up to 12 dB in median SINR, while coordinated scheduling reclaims idle time-frequency resources without degrading incumbent QoS.The article also reports that sparse and cellular services have orders-of-magnitude duty-cycle differences.Source: §I · p. 2

II. RELATED WORK

  • Prior work commonly studies pairwise coexistence, while database-driven systems make largely grant-or-deny spectrum decisions with limited QoS awareness.Multi-service upper-midband work addresses band-specific allocation but lacks a unified cross-service controller and joint infrastructure sharing.Source: §II · p. 2
  • Prior sharing approaches lack infrastructure or service sharing, and service-specific resource models encode incompatible interference, time-frequency, and protection criteria.These differences impede unified optimization across communications, sensing, navigation, and radiolocation.Source: §II · p. 2

III. OPEN SPECTRUM ARCHITECTURE

Open Spectrum coordinates heterogeneous service requests through the SIC, modular sApps, and a shared pool of physical infrastructure. A DT provides site-specific propagation intelligence for allocation decisions.

III. OPEN SPECTRUM ARCHITECTURE

  • The SIC processes tenant coexistence or frequency requests for access with guarantees, while accepted best-effort requests carry no guarantee that RFI requirements will be satisfied.Requests can specify coexistence or frequency requirements, time, bandwidth, and other relevant parameters.Source: §III · p. 2
  • Plug-and-play sApps implement modular spectrum policies, and the shared infrastructure pool supplies the compute, radio hardware, and sensors accessed through SIC coordination.A DT module feeds site-specific propagation intelligence into the SIC decision engine.Source: §III · p. 2, Figure 2 · p. 3
  • The architecture combines heterogeneous-service coordination through the SIC with DT-based RFI modeling and a shared infrastructure pool.Source: §III · p. 2, Figure 2 · p. 3

A. Spectrum Intelligence Controller

The SIC coordinates spectrum access across heterogeneous services, extending O-RAN control to service-specific data and operating across timescales from milliseconds to hours. Modular sApps and DT-based propagation modeling support policy enforcement and allocation decisions.

A. Spectrum Intelligence Controller

  • The SIC extends O-RAN RIC control to service-specific data such as radar pulse schedules, navigation beacon timing, and sensing duty cycles, on timescales from milliseconds to hours.It can also interface with O-RAN components to enforce policies involving cellular user load balancing or handover.Source: A. Spectrum Intelligence Controller · p. 3
  • Neighboring SICs coordinate boundary-region conflicts peer-to-peer, evaluating shared access priorities while maintaining local autonomy under a common national framework.The approach is described as enabling scalability and low latency for cross-boundary interactions compared with a hierarchical approach.Source: A. Spectrum Intelligence Controller · p. 3
  • Third parties can independently deploy and update plug-and-play sApps, including a duty-cycle policy that checks whether co-channel tenants' duty cycles sum to at most 1.If the condition is violated, the policy uses a priority table to reduce a tenant's duty cycle; the SIC arbitration layer resolves conflicts between sApps using configurable precedence.Source: A. Spectrum Intelligence Controller · p. 3
  • A site-specific DT precomputes propagation maps and predicts SINR at affected receivers to support QoS-aware allocations that account for geometry, materials, and multipath.The evaluation uses the DT offline; closing the real-time feedback loop between the DT and SIC remains ongoing work.Source: A. Spectrum Intelligence Controller · p. 3

B. Shared Infrastructure Pool

The shared infrastructure pool combines resources that sparse services may not afford to deploy with capacity and spectrum needs of cellular operators. It supports scheduled reservations and best-effort allocation of remaining capacity.

B. Shared Infrastructure Pool

  • The pool shares compute, radio hardware, and RF sensors, including programmable servers, reassignable radios, and distributed spectrum-monitoring devices.These resources support software-based signal processing, dynamically reassigned radio platforms, and compliance monitoring or conflict detection.Source: B. Shared Infrastructure Pool · pp. 3–4
  • Sparse sensing, radar, and navigation services lack the scale to build dense deployments, while cellular operators have excess off-peak infrastructure capacity and peak-hour spectrum needs.Joint sharing creates value for both sides.Source: B. Shared Infrastructure Pool · p. 3
  • Scheduled mode reserves resources in advance using a precomputed conflict-free time-frequency plan, while best-effort mode allocates remaining capacity to services that tolerate variable access.The examples are radar with predictable pulse schedules and IoT sensors able to defer measurements by seconds.Source: B. Shared Infrastructure Pool · p. 4

C. Spectrum Monitoring

Open Spectrum combines spectrum monitoring with Digital Twin (DT) calibration and conflict detection. The SIC resolves conflicts through configurable scheduling and allocation actions, illustrated by a radar–5G sharing scenario.

C. Spectrum Monitoring

  • Dedicated sensors and infrastructure-reported signal characteristics provide spectral measurements and spatial coverage, triggering conflict detection and calibrating DT propagation models.Observed interference above tenant thresholds can trigger short-term conflict detection; monitoring data also improves predictive allocation over time.Source: C. Spectrum Monitoring · p. 4

A. Conflict Detection and Resolution

  • When interference violates coexistence criteria, the SIC selects temporal, spatial, or frequency separation, or priority-based preemption, using regulatory priority tables.The SIC can resolve conflicts on timescales of tens to hundreds of milliseconds, with direct control of shared infrastructure enabling sensing-to-enforcement.Source: A. Conflict Detection and Resolution · p. 4
  • For a weather radar and 5G base station, the SIC first schedules non-overlapping slots when feasible, then can reassign the cellular carrier to an adjacent channel.The DT evaluates candidate strategies before enforcement; temporal separation may be infeasible when another service occupies the complementary slots.Source: A. Conflict Detection and Resolution · p. 4

B. Service Sharing

Open Spectrum supports non-cellular services on cellular infrastructure through three sharing modes, with the SIC selecting a mode based on QoS requirements and DT compatibility. The evaluation validates quantitative premises through simulation, not end-to-end operation of the SIC, sApps, or DT feedback loop.

B. Service Sharing

  • The SIC selects site-only sharing, full RF-chain sharing, or spectrum pooling with duty-cycle coordination based on QoS requirements and DT compatibility.Benefits depend on how native RF parameters match the host: cellular-like services see the greatest gains, while high-power services may suffer increased interference under site-only sharing unless managed.Source: B. Service Sharing · p. 4

V. SYSTEM-LEVEL EVALUATION

  • System-level simulations characterize sharing benefits and tradeoffs but do not validate the SIC, sApps, or DT feedback loop end to end.Such validation requires a full-stack prototype and remains ongoing work.Source: §V · p. 4

A. Simulation Setup and Evaluation Scenarios

The evaluation combines BostonTwin geometry with Sionna ray tracing to model a shared spectrum pool and compare dedicated deployments with infrastructure-sharing configurations. It models cross-service interference and per-service SINR under specified deployment densities and RF assumptions.

A. Simulation Setup and Evaluation Scenarios

  • Fig. 3 depicts the BostonTwin multi-service deployment, marking base stations as triangles, user equipment as dots, and services by color.The realization illustrates the deployments used in the simulation scenarios.Source: Figure 3 · p. 5, A. Simulation Setup and Evaluation… · p. 5
  • BostonTwin supplies 3D geometry for a 2.3 km2 urban tile; simulations average 50 Monte Carlo iterations with uniformly sampled user locations.The model assigns building radio-material properties and uses antenna patterns specified by 3GPP TR 38.901.Source: A. Simulation Setup and Evaluation… · pp. 4–5
  • Cellular deploys 50 base stations per 1 km2, while each sparse service uses 10 baseline nodes; full-RF-chain sharing sets sparse-service power to cellular levels.This density asymmetry matters for site-only sharing, where higher-power sparse services on the denser cellular grid generate more aggregate interference.Source: A. Simulation Setup and Evaluation… · p. 5
  • The model includes aggregate co-channel interference across services and calculates SINR using service-specific receiver models.Cellular downlink uses a linear receiver, active sensing uses the two-way radar equation, and navigation and radiolocation use post-correlation SINR at the strongest-beacon receiver.Source: A. Simulation Setup and Evaluation… · p. 5
  • The 400 MHz shared pool is centered around 3.5 GHz, and the scenarios compare dedicated-band baselines with site-only and full-RF-chain infrastructure sharing.In the baseline, services use separate center frequencies and cross-service interference is absent by construction; sharing reuses cellular sites at 3.5 GHz under the stated coordination assumption.Source: A. Simulation Setup and Evaluation… · p. 5, Table I · p. 5

B. SINR Performance under Infrastructure Sharing

Full-RF-chain sharing aligns cellular SINR with other services, with a median improvement of 12 dB under increased density and tuned RF parameters. The results also show that site-only sharing can raise interference and that the reported SINR focuses on downlink receivers.

B. SINR Performance under Infrastructure Sharing

  • Baseline sensing, radionavigation, and radiolocation SINR medians fall within −9 and −8 dB; site-only sharing increases interference when higher-power services use the denser cellular grid.The passage contrasts this with full-RF-chain sharing, which removes the interference penalty.Source: B. SINR Performance under… · pp. 5–6
  • 12 dB median improvement aligns cellular SINR with other services under increased density and fine-tuned RF parameters.Full-RF-chain sharing removes the interference penalty described for site-only sharing.Source: B. SINR Performance under… · p. 6
  • Access to high-density infrastructure can improve sparse-service SINR when RF parameters are properly tuned, creating an incentive to join the common pool.The DT can simulate candidate configurations against BostonTwin geometry to predict which mode meets a tenant’s QoS target before deployment.Source: B. SINR Performance under… · p. 6
  • These results concern downlink SINR; passive sensing experiences interference at its receiver and depends on SIC scheduling of active transmitters around observation windows.Passive receivers cannot adjust transmit power, and the duty-cycle enforcement sApp is suited to this scheduling role.Source: B. SINR Performance under… · p. 6

C. Effective Rate vs. Duty Cycle and Bandwidth

This section evaluates cellular effective rate as sparse services share infrastructure under SIC-coordinated scheduling. It relates service duty cycles and bandwidths to available cellular resources and sharing opportunities.

C. Effective Rate vs. Duty Cycle and Bandwidth

  • Effective rate is Reff = δ ·B ·C, with C defined as median spectral efficiency from the ray-traced SINR distribution.Figure 5 varies duty cycle δ and bandwidth B under SIC-coordinated non-overlapping scheduling.Source: C. Effective Rate vs. Duty Cycle and… · p. 6
  • Sparse services use less than 10%, and often less than 1%, of available time-frequency resources, with sensing at δ ∼0.1 and B ∼400 MHz.The nominal radionavigation point is δ ∼0.01 and B ∼210 MHz; radiolocation is δ ∼0.01 and B ∼400 MHz.Source: C. Effective Rate vs. Duty Cycle and… · p. 6
  • When duty-cycle budgets permit synchronized non-overlapping slots, SIC scheduling enables interference-free spectrum sharing.Incompatible duty cycles or inflexible timing can require frequency- or spatial-domain separation.Source: C. Effective Rate vs. Duty Cycle and… · p. 6
  • Allocating idle slots to other tenants can increase aggregate spectral efficiency without degrading existing services.The rate surface indicates diminishing returns at wider bandwidths for low-duty-cycle services, motivating maximum bandwidth–duty-cycle products rather than fixed band allocations.Source: C. Effective Rate vs. Duty Cycle and… · p. 6

VI. DISCUSSION

The discussion identifies temporal complementarity as a sharing opportunity while emphasizing that compatibility, service requirements, and validated propagation models constrain deployment. The SIC must coordinate sharing across these conditions while preserving service quality.

VI. DISCUSSION

  • The SIC must act as a matchmaker, assessing power, gain, duty cycle, antenna pattern, location, and height rather than allocating by frequency alone.The assessment reflects that infrastructure-sharing incentives and performance gains differ across heterogeneous services.Source: §VI · p. 6
  • Most non-cellular services use less than 1–10% of available time-frequency resources, enabling SIC-coordinated timedomain access for interference-free coexistence.This can avoid the power reductions or geographic exclusion zones used in current sharing frameworks.Source: §VI · p. 6
  • Full-RF-chain sharing is currently viable only for sensing-like services because radar and navigation waveform requirements can conflict with cellular radio parameters.Radar amplifiers may exceed the ∼46 dBm ceiling of cellular radio units, while navigation beacons use narrowband waveforms that may conflict with NR subcarrier spacing.Source: §VI · pp. 6–7
  • Cellular operators’ participation depends on hosting additional services without triggering QoS violations or customer complaints.The discussion identifies tight interaction between the SIC and shared infrastructure as a key enabler of cellular and passive-sensing QoS preservation.Source: §VI · p. 7
  • Site-specific propagation models can tighten conservative exclusion-zone margins, but require validation and continuous calibration.The transition to dynamic, model-driven sharing boundaries is described as gradual rather than a binary switch.Source: §VI · p. 7

VII. CONCLUSIONS

The conclusion presents Open Spectrum as a joint-sharing architecture and reports simulation evidence for infrastructure-sharing incentives and duty-cycle-based coexistence. It identifies integration, prototyping, scalability, and policy work as remaining steps.

VII. CONCLUSIONS

  • Open Spectrum jointly shares spectrum, services, and infrastructure through a shared pool, SIC, plug-and-play sApps, and DT-based coordination.The architecture addresses pairwise-only coexistence, binary grant/deny decisions, and spectrum-only sharing.Source: §VII · p. 7
  • System-level simulations show infrastructure-sharing incentives and SIC-coordinated duty-cycle complementarity enabling interference-free coexistence with cellular QoS preserved.Source: §VII · p. 7
  • Realizing the vision requires integrating existing building blocks alongside standardization and policy efforts; prototyping and evaluations of scalability, resource allocation, security, and techno-economic implications remain future work.The conclusion also calls for service-agnostic grant structures based on interference constraints rather than technology-specific operating rules.Source: §VII · p. 7
Loading 2609.11843v1…