⚡ electrical engineering

Radar-Assisted Beam Management Framework for mmWave NTNs: Overhead Reduction and Physical Layer Security Application

This paper proposes a radar-assisted beam management framework for millimeter-wave non-terrestrial networks that reduces selection overhead by utilizing spatial sensing information and enhances physical-layer security by suppressing unintended users while improving legitimate user signal gain.

Original authors: Bora Bozkurt, Cevdet Tosun, Mehmet Nuri Akinci, Ali Gorcin, Ibrahim Hokelek, Mehmet Kemal Ozdemir

Published 2026-06-02

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CC BY 4.0

Original authors: Bora Bozkurt, Cevdet Tosun, Mehmet Nuri Akinci, Ali Gorcin, Ibrahim Hokelek, Mehmet Kemal Ozdemir

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine you are trying to find a specific friend in a massive, dark stadium filled with thousands of people. You have a flashlight, but it's a very narrow beam. To find your friend, you could sweep the light slowly across the entire stadium, checking every single seat. This would take a long time and waste a lot of battery power. This is essentially what current wireless networks do when they try to connect to devices in the sky (like drones or high-altitude balloons). They have to "sweep" through many possible directions to find the best signal, which is slow and inefficient.

This paper proposes a smarter way to do this using a radar as a guide. Here is the breakdown of their idea using simple analogies:

1. The Problem: The "Flashlight Sweep"

In traditional systems, the base station (the "flashlight") doesn't know exactly where the user is. It has to test many narrow beams one by one until it finds the one that gives the strongest signal. This is like walking through a dark maze, trying every door until you find the exit. It works, but it's slow and uses up a lot of resources (overhead).

2. The Solution: The "Radar Spotter"

The authors suggest adding a radar to the base station. Think of the radar as a "spotter" with a wide-angle lens.

The Wide Beam: Before the narrow flashlight starts its slow sweep, the radar sends out a wide, coarse beam. It quickly scans the sky and says, "Hey, I see a user over there, roughly in that corner, and they are about 500 meters away."
The Narrow Beam: Now, instead of searching the whole stadium, the narrow flashlight only needs to search that specific corner. This saves a massive amount of time and energy.

3. The "Early Exit" Trick

The paper introduces a clever shortcut called an "early stopping condition."

How it works: The base station knows roughly how far away the user is (thanks to the radar). It can calculate, "If the user is 500 meters away, the signal should be at least this strong."
The Shortcut: As the narrow flashlight sweeps through the "corner" identified by the radar, it stops immediately once it finds a beam that is strong enough. It doesn't need to check the rest of the beams in that corner.
The Analogy: Imagine you are looking for a specific book on a shelf. You know the book is thick and heavy. Instead of checking every single book, you pick up the first one that feels heavy enough and say, "This is it!" You stop searching. This paper proves mathematically that this shortcut works well and significantly reduces the time spent searching.

4. The Security Bonus: "Spotting the Eavesdropper"

The paper also shows how this radar system can act as a security guard.

The Scenario: Imagine you are talking to your friend, but there is a stranger (an eavesdropper) standing nearby trying to listen in.
The Radar's Role: The radar can detect the stranger even if they are just standing there silently (passive). It knows exactly where they are.
The Counter-Move: The base station can then shape its signal beam to be very loud for your friend but create a "dead zone" (a null) right where the stranger is standing. It's like shining a spotlight on your friend while simultaneously putting a shadow over the stranger so they can't see or hear anything.
The Result: The simulation in the paper shows that this method successfully blocks the stranger's ability to hear the signal (suppressing their power to almost nothing) while actually making the signal for the legitimate friend slightly stronger.

Summary of Claims

The paper claims that by using radar to get a "rough idea" of where users are, the system can:

Skip the slow search: It doesn't need to check every possible direction, only the ones the radar pointed to.
Stop early: It stops searching as soon as it finds a "good enough" signal, saving more time.
Keep secrets: It can use the radar's knowledge of where "unwanted" listeners are to block signals from reaching them, making the connection more secure.

The authors tested this with computer simulations and found that it works effectively, reducing the time needed to connect and successfully blocking unwanted listeners. They conclude that this is a practical, low-cost way to make high-speed wireless networks in the sky faster and more secure.

Technical Summary: Radar-Assisted Beam Management Framework for mmWave NTNs

Problem Statement
The practical deployment of Non-Terrestrial Networks (NTNs) operating at millimeter-wave (mmWave) and higher frequencies faces a critical challenge: the need for fast and low-overhead beam management. While Integrated Sensing and Communication (ISAC) and sensing-assisted communication (SAC) have been explored to optimize beamforming, existing approaches often rely on complex machine learning techniques or multi-modal data fusion. Furthermore, sensing-assisted beam management for NTNs remains underexplored, particularly regarding the initial access stage and architectures that rely exclusively on radar as the sensing modality. Traditional beam selection involves exhaustive sweeping of candidate beams, which incurs significant latency and signaling overhead, a bottleneck for dynamic NTN environments.

Methodology
The authors propose a novel radar-assisted beam selection framework designed specifically for the initial access stage of mmWave NTNs. The system model features an aerial 5G mmWave base station (gNB) equipped with two co-located Uniform Rectangular Arrays (URAs): one dedicated to radar sensing and the other to communication.

The methodology operates in two primary phases:

Coarse Sensing and Estimation: The radar array utilizes wide digital beams to detect potential User Equipments (UEs) and passive targets. It estimates the Angle of Departure (AoD) and the distance for each detected target. The system assumes the gNB can associate these spatial estimates with temporary network identifiers.
Restricted Beam Sweeping with Early Stopping: Instead of sweeping the entire codebook, the communication array restricts its search to a subset of beams ( $C$ $C$ ) corresponding to the coarse AoD region detected by the radar.
- Distance-Aware Early Stopping: To further reduce overhead, the framework introduces a threshold-based stopping criterion. Using the radar-estimated distance, the gNB calculates a received power threshold ( $P_{th}$ ). During the beam sweep, the UE provides feedback only when a beam yields a received power greater than or equal to $P_{th}$ . The first beam meeting this condition is selected, terminating the search early.
- Physical Layer Security (PLS): The framework leverages the radar's ability to detect passive targets (potential eavesdroppers). If such targets are identified, the gNB employs Regularized Zero Forcing (RZF) to null the beam in the direction of the unintended user, thereby suppressing signal leakage while enhancing the beamforming gain for legitimate users.

Key Contributions
The paper outlines three main contributions:

Radar-Assisted Framework: A novel beam selection scheme for NTN initial access that utilizes radar-derived AoD and distance to narrow the search space and enforce an early stopping condition, significantly reducing beam search overhead while maintaining narrow communication beams.
Theoretical Overhead Analysis: A probabilistic analysis of the worst-case beam selection overhead under a suboptimal, naive distance-based search strategy. The authors derive an approximation for this worst-case overhead and characterize its statistics under Gaussian estimation error, providing a theoretical benchmark for sensing-assisted schemes.
PLS Extension: An extension of the framework to Physical Layer Security applications. By detecting passive targets via radar, the system actively suppresses unintended users through beam nulling, evaluated through comprehensive simulations.

Results
Simulation results validate the proposed framework in a scenario involving an aerial gNB at 500m altitude and multiple UEs:

Overhead Reduction: The distance-based early stopping mechanism effectively reduces the number of beams required for selection. Theoretical analysis confirms that the approximation for worst-case overhead ( $\tilde{L}_s$ ) aligns accurately with actual overhead values across various antenna configurations.
Security Performance: In the PLS scenario, the proposed scheme successfully suppresses the power of an unintended user (eavesdropper) to below −135 dBm.
Legitimate User Gain: Simultaneously, the legitimate users experience an additional beamforming gain of approximately 2 dB (specifically 2.218 dB and 2.174 dB for two tested users) due to the nulling of interference directions.
Robustness: Analysis of beam index selection across different Signal-to-Noise Ratios (SNR) demonstrates that the system maintains robust alignment with the target beam even under low-SNR conditions, though the distribution of selected indices broadens as noise increases.

Significance and Claims
The paper claims to provide a viable, low-overhead solution for beam management in practical NTN systems operating at mmWave and higher frequencies. By relying exclusively on radar for sensing assistance, the framework avoids the complexity of full waveform-level integration or heavy AI-based training, making it suitable for model-based NTN channels which are typically Line-of-Sight (LoS) dominated. The work establishes a theoretical benchmark for overhead reduction and demonstrates a dual benefit: improving system efficiency through early stopping and enhancing security through radar-enabled passive target suppression. The authors note that future work will address dynamic environments, hybrid precoding, and hardware validation.