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Monostatic ISAC Without Full Buffers: Revisiting Spatial Trade-Offs Under Bursty Traffic

Mauro Marchese, Musa Furkan Keskin, Pietro Savazzi, Henk Wymeersch

TL;DR

The paper analyzes spatial trade-offs in a monostatic ISAC system under bursty traffic, relaxing the full-buffer assumption to reveal how data availability interacts with sensing performance. It compares Pure Communication, Time Sharing, and Concurrent Transmission policies, and introduces a GLRT-based coherent integration detector for multi-target sensing. The main contributions include a bursty-traffic problem formulation, a GLRT-based sensing method, and numerical design guidelines that depend on traffic, geometry, and sensing requirements. The findings offer practical guidelines for precoder design and sensing strategy in realistic ISAC deployments, highlighting when data-based sensing can outperform dedicated pilots and when non-full-buffer effects dominate performance.

Abstract

This work investigates the spatial trade-offs arising from the design of the transmit beamformer in a monostatic integrated sensing and communication (ISAC) base station (BS) under bursty traffic, a crucial aspect necessitated by the integration of communication and sensing functionalities in next-generation wireless systems. In this setting, the BS does not always have data available for transmission. This study compares different ISAC policies and reveals the presence of multiple effects influencing ISAC performance: signal-to-noise ratio (SNR) boosting of data-aided strategies compared to pilot-based ones, saturation of the probability of detection in data-aided strategies due to the non-full-buffer assumption, and, finally, directional masking of sensing targets due to the relative position between target and user. Simulation results demonstrate varying impact of these effects on ISAC trade-offs under different operating conditions, thus guiding the design of efficient ISAC transmission strategies.

Monostatic ISAC Without Full Buffers: Revisiting Spatial Trade-Offs Under Bursty Traffic

TL;DR

The paper analyzes spatial trade-offs in a monostatic ISAC system under bursty traffic, relaxing the full-buffer assumption to reveal how data availability interacts with sensing performance. It compares Pure Communication, Time Sharing, and Concurrent Transmission policies, and introduces a GLRT-based coherent integration detector for multi-target sensing. The main contributions include a bursty-traffic problem formulation, a GLRT-based sensing method, and numerical design guidelines that depend on traffic, geometry, and sensing requirements. The findings offer practical guidelines for precoder design and sensing strategy in realistic ISAC deployments, highlighting when data-based sensing can outperform dedicated pilots and when non-full-buffer effects dominate performance.

Abstract

This work investigates the spatial trade-offs arising from the design of the transmit beamformer in a monostatic integrated sensing and communication (ISAC) base station (BS) under bursty traffic, a crucial aspect necessitated by the integration of communication and sensing functionalities in next-generation wireless systems. In this setting, the BS does not always have data available for transmission. This study compares different ISAC policies and reveals the presence of multiple effects influencing ISAC performance: signal-to-noise ratio (SNR) boosting of data-aided strategies compared to pilot-based ones, saturation of the probability of detection in data-aided strategies due to the non-full-buffer assumption, and, finally, directional masking of sensing targets due to the relative position between target and user. Simulation results demonstrate varying impact of these effects on ISAC trade-offs under different operating conditions, thus guiding the design of efficient ISAC transmission strategies.
Paper Structure (17 sections, 13 equations, 5 figures, 2 tables)

This paper contains 17 sections, 13 equations, 5 figures, 2 tables.

Table of Contents

  1. Introduction
  2. System Model
  3. ISAC Scenario under Bursty Traffic Paradigm
  4. ISAC Requirements
  5. Precoder Design and Sensing Algorithm
  6. ISAC Policies
  7. Pure Communication
  8. Time Sharing
  9. Concurrent Transmission
  10. GLRT Detector with Coherent Integration
  11. Single-Target Case
  12. Multi-Target Case
  13. Simulation Results
  14. Simulation Scenario
  15. Sensing Performance under Bursty Traffic
  16. ...and 2 more sections

Figures (5)

  • Figure 1: The considered ISAC scenario including a BS performing monostatic sensing, one UE and one target.
  • Figure 2: Sensing performance of ISAC policies against target RCS in the strict sensing requirement scenario ($T_s=0.3$ ms).
  • Figure 3: Sensing performance of ISAC policies against target RCS in the loose sensing requirement scenario ($T_s=5$ ms) with low-$\Delta\theta$.
  • Figure 4: Sensing performance of ISAC policies against sensing requirement ($T_s$). The target RCS is fixed and the strong target scenario is considered.
  • Figure 5: trade-off curves in different scenarios obtained for different values of $\rho\in[0,1]$ and $\beta\in[0,200]$ for concurrent transmission and time sharing policies, respectively.