⚡ electrical engineering

On the Performance of Dual-Antenna Repeater Assisted Bi-Static MIMO ISAC

This paper proposes a dual-antenna repeater-assisted bi-static MIMO ISAC framework that optimizes the trade-off between sensing and communication performance through base station precoding, demonstrating that strategic repeater deployment significantly enhances target detection probability while mitigating coverage holes and interference.

Original authors: Anubhab Chowdhury, Erik G. Larsson

Published 2026-03-10

📖 4 min read☕ Coffee break read

CC BY 4.0

Original authors: Anubhab Chowdhury, Erik G. Larsson

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 do two things at once in a busy city: talk to your friends (Communication) and spot a hidden spy (Sensing/Radar).

Usually, doing both is tricky. If you shout too loud to be heard, you might scare the spy away or create too much noise to hear their footsteps. If you whisper to be stealthy, your friends can't hear you.

This paper introduces a clever new tool to solve this problem: a "Super-Echo Box" (called a Repeater).

Here is the breakdown of how it works, using simple analogies:

1. The Problem: The "Dead Zone" and the "Blind Spot"

The Communication Problem: Imagine you are in a building with thick walls. Your phone signal gets blocked, creating a "dead zone" where you can't talk to anyone.
The Sensing Problem: You are trying to use radar to find a target (like a drone) in a specific area. But the target is small, or there are too many trees and buildings (clutter) reflecting noise, making it hard to see the target.

2. The Solution: The "Super-Echo Box" (The Repeater)

The authors propose placing a special device called a Repeater in the "hot spot" (the area where the target is likely to be).

Think of this Repeater as a super-charged mirror with a microphone and a speaker:

It listens: It hears the signal coming from the main tower (the Base Station).
It amplifies: It turns the volume up (amplifies the signal).
It shouts back: It immediately re-transmits that signal.

How this helps:

For Talking (Communication): If a user is in a dead zone, the Repeater catches the signal and boosts it, filling the hole so they can talk clearly.
For Spotting (Sensing): When the radar signal hits the hidden target, the echo is usually weak. The Repeater catches that weak echo, boosts it, and sends it back to the radar station. It's like using a megaphone to hear a whisper from a mile away.

3. The Catch: The "Party Noise" Problem

There is a downside. Because the Repeater is so loud and active, it creates some side effects:

The "Shouting" Issue: When the Repeater boosts the signal for the radar, it might accidentally blast that same signal at the people trying to talk, drowning out their conversation.
The "Static" Issue: The Repeater isn't perfect; it adds its own background static (noise) to the radar's ears, which can make it harder to distinguish the target from the noise.

4. The Magic Trick: The "Smart Director" (The Precoder)

The paper's main discovery is how to fix the "Party Noise" problem. The main tower (Base Station) uses a Smart Director (a mathematical algorithm called a precoder).

Think of the Smart Director as a conductor at an orchestra:

The conductor knows exactly where the "talkers" (users) are sitting and where the "spy" (target) is hiding.
The conductor tells the orchestra (the signal): "Hey, send the loud music toward the spy, but make sure the volume is zero in the direction of the talkers."
This way, the Repeater can boost the signal for the spy without disturbing the conversation.

5. The Big Finding: Location Matters!

The researchers ran simulations (computer tests) and found a golden rule:

Where you put the Repeater is everything.
If you put the Repeater right next to the "Spy Hotspot," you can detect even very small, quiet targets with high accuracy.
If you put the Repeater far away, the signal gets lost in the distance, and it doesn't help much.

Summary

This paper is like a blueprint for a super-efficient city.

Old Way: You need separate systems for talking and watching, and they often get in each other's way.
New Way: Use a Repeater to act as a bridge. It amplifies signals to fix dead zones and boost radar detection.
The Secret Sauce: By using a Smart Director at the main tower, you can make sure the Repeater helps the radar without annoying the people trying to talk.

The Bottom Line: By placing these "Super-Echo Boxes" in the right spots and using smart math to control the volume, we can build wireless networks that are faster, clearer, and much better at spotting things (like self-driving cars spotting pedestrians or drones spotting intruders) all at the same time.

1. Problem Statement

The paper addresses the integration of Integrated Sensing and Communication (ISAC) systems with repeater-assisted networks. Specifically, it investigates a bi-static setup where a transmitting Base Station (BS) sends signals for both downlink (DL) data transmission and target detection, while a separate receiving BS performs sensing based on reflected echoes.

The core problem is the trade-off introduced by deploying an active repeater (a full-duplex relay) in this environment:

Benefits: The repeater amplifies echoes from targets (improving sensing) and fills coverage holes for DL users (improving communication).
Drawbacks: The repeater introduces additional noise and amplifies interference. Specifically, amplified sensing signals can interfere with DL users, and amplified DL signals can overwhelm the weak target echoes at the sensing receiver, degrading detection performance.

The paper aims to quantify these trade-offs and propose a framework to optimize the system, specifically focusing on precoder design at the transmit BS to mitigate interference while leveraging the repeater's benefits.

2. Methodology and System Model

System Architecture

Bi-Static MIMO ISAC: A transmit BS ( $N_t$ antennas) serves $K$ single-antenna users and targets a specific "hot-spot" area. A receive BS ( $N_r$ antennas) detects targets.
Dual-Antenna Repeater: An active scatterer with two antennas (one receive, one transmit) that instantaneously retransmits incoming signals with a complex gain $\nu$ .
Channels: The model accounts for direct links, target-to-repeater links, repeater-to-user/BS links, and composite clutter channels.

Signaling Scheme

Transmit Signal: The BS transmits a superposition of precoded DL data symbols ( $s_n$ ) and a dedicated sensing signal ( $s_T$ ).
Repeater Operation: The repeater receives the signal, adds its own internal noise ( $w_R$ ), amplifies it by $\nu$ , and retransmits it.
Received Signals:
- At the Receive BS (Sensing): The signal contains the direct target echo, the repeater-amplified target echo, direct BS-to-BS interference, and repeater-amplified interference. The authors formulate the received signal to separate the target component (dependent on Radar Cross-Section, $\alpha$ ) from clutter and noise.
- At the DL Users (Communication): The signal includes the direct path from the BS and the repeater-amplified path. The target reflection is treated as part of the multipath environment (clutter) since users are unaware of the target.

Detection Framework (GLRT)

The authors propose a Generalized Likelihood Ratio Test (GLRT) for target detection.
Hypothesis Testing:
- $H_0$ : No target (only clutter and noise).
- $H_1$ : Target present (clutter, noise, and target echo).
Estimation: The framework jointly estimates the unknown Radar Cross-Section ( $\alpha$ ) and the clutter channel parameters.
Complexity: The computational complexity is dominated by a matrix inversion of size $(N_t N_r + 1) \times (N_t N_r + 1)$ , scaling as $O((N_t N_r)^3)$ .
Noise Modeling: The sensing noise covariance explicitly includes the repeater's internal noise amplified by the gain factor ( $|\nu|^2 \sigma_R^2$ ).

Precoding Strategies

To manage the interference between sensing and communication, the paper analyzes two precoding approaches for the transmit BS:

Target-Centric: The sensing precoder ( $p_T$ ) is beamformed directly toward the target. This maximizes sensing gain but causes significant interference to DL users.
Communication-Centric: The sensing precoder is projected onto the nullspace of the users' effective channels (including the repeater path). This eliminates interference to users but may reduce sensing gain.

3. Key Contributions

Novel Framework: Development of a mathematical framework for bi-static ISAC with active repeaters, explicitly modeling the dual role of the repeater as both a signal amplifier and a noise/interference source.
GLRT Derivation: Derivation of a robust GLRT detector that accounts for the repeater's noise and the composite channel effects (target echo via repeater vs. direct path).
Interference Mitigation Analysis: Demonstration that precoder design is critical. The paper shows that "Communication-Centric" precoding can nullify the interference caused by the sensing signal to DL users, whereas "Target-Centric" precoding degrades user performance.
Deployment Insights: Identification that placing repeaters near target hot-spots yields the highest Probability of Detection (PoD) even for targets with low Radar Cross-Section (RCS), whereas placing them near users primarily benefits communication.

4. Numerical Results

The authors validated their framework using simulations with 3GPP Urban Microcell models:

Target Detection (PoD vs. RCS):
- Repeater-assisted systems achieve a significantly higher Probability of Detection (PoD) at lower RCS values compared to systems without repeaters.
- The system is robust to increased clutter variance; the repeater helps overcome the degradation caused by clutter.
Downlink Spectral Efficiency (SE):
- Target-Centric Precoding: Results in a noticeable drop in DL SE for users due to interference from the dedicated sensing signal.
- Communication-Centric Precoding: Successfully nullifies this interference, maintaining high DL SE comparable to systems without sensing signals, while still utilizing the repeater for coverage.
Repeater Location Trade-off:
- Moving the repeater closer to the target hot-spot maximizes sensing performance (PoD).
- Moving the repeater closer to users maximizes communication performance (SE).
- There is a distinct trade-off curve: optimizing for one metric often requires sacrificing the other, depending on the repeater's physical location.

5. Significance and Future Outlook

Standardization Relevance: The paper highlights that repeaters are already included in 3GPP Release 18 and are being pushed for ISAC in Release 19. This work provides the theoretical underpinning for their deployment in 5G-Advanced/6G.
Comparison with RIS: The authors distinguish repeaters from Reconfigurable Intelligent Surfaces (RIS). Unlike RIS, repeaters are band-selective (can filter out-of-band interference) and active (amplify signals), making them suitable for multi-operator environments where RIS might reflect unwanted interference.
Future Directions: The paper suggests extending the framework to swarm-repeater systems (multiple repeaters) and investigating time-varying channel estimation, which are critical for dynamic real-world deployments.

Conclusion:
The paper demonstrates that while repeaters introduce complexity regarding noise and interference in bi-static ISAC, they offer substantial performance gains. By carefully designing the transmit precoder (specifically using null-space projection for communication) and strategically placing the repeater near target hot-spots, operators can achieve a balanced system that significantly improves both target detection capabilities and downlink coverage.