SDRs and AI at the Tower Edge: Turning Passive Infrastructure into Active Defenders

Introduction: From Listening Posts to Digital Sentries

Telecom towers are often described as the backbone of digital society, but they are still mostly passive infrastructure — hosting antennas, providing power, and enabling backhaul.What if they could actively listen, think, and respond to threats?

This is the promise of software-defined radios (SDRs) combined with edge artificial intelligence (AI). Together, they can convert 18,000 cell sites into a nationwide sensing and protection grid, capable of spotting hostile signals, drone telemetry, and even coordinated jamming campaigns in real time.

What Software-Defined Radios Bring to the Table

Traditional radios are “hard-wired” for a specific frequency or modulation. SDRs, by contrast, are programmable in software, which means they can:

• Scan multiple bands dynamically — from VHF/UHF used by drones to 5G mid-band spectrum used by rogue BTSs.

• Retune on demand to follow suspicious emitters across frequencies.

• Detect spectrum anomalies — unusual power spikes, spoofed GNSS signals, or coordinated jamming sweeps.

• Switch to alternative waveforms in emergencies, supporting fallback communications for military and emergency responders.

This agility makes SDRs a perfect fit for a distributed defence wall: they can turn every tower into a multi-band spectrum watchdog.

Edge AI: Thinking at the Tower

Raw spectrum data is massive — terabytes per hour if you try to capture everything.This is where edge AI comes in:

• Signal Classification: AI models can recognise known signal types (Wi-Fi, 4G, GNSS, drone telemetry) and flag unknowns.

• Anomaly Detection: Machine learning can identify patterns that deviate from baseline — e.g., sudden power increases, sweeping jammers.

• Threat Scoring: Local inference models can prioritise alerts so only genuine threats are escalated to central SOCs.

• Autonomous Response: Towers can automatically switch to backup timing sources, alert nearby sites, or trigger counter-UAS systems — all without human latency.

The result is real-time situational awareness, even in areas where connectivity to the core network is intermittent or degraded.

Architectural Considerations

Deploying SDRs and AI at scale raises several architectural questions boards must grapple with:

1. Compute Footprint:

   • MEC (Multi-access Edge Compute) nodes are ideal, but not every tower has one.

   • Boards must plan phased capex to bring compute closer to the edge.

2. Backhaul Capacity:

   • Spectrum monitoring data must be filtered locally to avoid saturating links.

   • AI inference at the tower helps ensure only actionable intelligence is sent upstream.

3. Power & Resilience:

   • Sites may need upgraded backup power to keep SDRs running during blackouts.

   • Solar + battery hybrid solutions may be needed for rural or off-grid towers.

4. Interoperability:

   • Defence, civil protection, and MNO stakeholders must agree on data-sharing protocols.

   • Federated models may be preferable to centralised ones to reduce attack surface.

Threats This Architecture Could Detect

An SDR + AI-enabled tower could act as an early warning system for:

• Rogue Base Stations: IMSI catchers, fake 5G cells used for spying or intercept.

• GNSS Spoofing: Distinguishing genuine satellite signals from ground-based fakes.

• Drone Swarms: Detecting telemetry signals before drones are visually spotted.

• Spectrum Sabotage: Identifying coordinated jamming of critical frequency bands.

• Covert Military Activity: Picking up unusual RF activity near borders or critical assets.

With enough towers deployed, this creates a continuous, overlapping coverage map — effectively a “RF radar net” for the nation.

Cost and Feasibility

Contrary to popular belief, the costs are manageable:

• Commodity SDRs have dropped below $500 per channel.

• AI inference chips can run at sub-10W power envelopes.

• Many towers already have spare rack space and power margin for small add-ons.

Governments could co-fund this upgrade as part of national resilience programmes, sharing both capex and opex with TowerCos.

Board-Level Opportunity

This is not merely a technical upgrade — it is a strategic repositioning:

• From landlord to defender: TowerCos become partners in national security.

• New revenue models: Defence-as-a-Service (DaaS), spectrum monitoring subscriptions, compliance reporting for regulators.

• Valuation uplift: Infrastructure funds could re-rate TowerCos that host critical resilience assets as “strategic infrastructure” — attracting sovereign wealth capital.

Risks and Mitigations

Boards should also be aware of:

• Privacy Concerns: SDRs must avoid capturing payload data — focus on metadata and RF signatures.

• Regulatory Approval: National spectrum regulators may need to licence monitoring activities.

• Operational Complexity: Training and incident-response procedures must be defined upfront.

These risks are manageable with the right governance frameworks — and far outweighed by the strategic benefits.

Board Conclusion: Time to Pilot

The time to move is now. Boards should commission pilot deployments in high-priority regions:

1. Select 20–50 towers near borders, airports, or critical power plants.

2. Equip with SDRs, edge compute, and AI anomaly detection.

3. Integrate alerts with national SOCs and defence command centres.

4. Measure detection latency, false positives, and cost per site.

A successful pilot can then be scaled nationwide, creating a living shield around national critical infrastructure.

“Software-defined radios are the new radar — and you already have 18,000 places to put them.”