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Hybrid Resource Allocation Scheme for Bistatic ISAC with Data Channels

Marcus Henninger, Lucas Giroto, Ahmed Elkelesh, Silvio Mandelli

TL;DR

This work tackles resource allocation in bistatic ISAC by embedding low-order, easily decodable symbols as pseudo-pilots on a sensing grid within the data channel. The hybrid scheme balances sensing gains with communication efficiency by decoding lower-MO symbols at the bistatic receiver, enabling improved estimation of the sensing matrix and a higher range-Doppler resolution without fully sacrificing throughput. Through a complete processing pipeline and simulations, the authors demonstrate improved bistatic sensing performance over a comm-centric baseline, quantify the spectral efficiency trade-off (≈3%), and provide insights on how decoding errors influence sensing quality. The approach offers practical guidance for jointly optimizing sensing requirements (unambiguous range/Doppler, SNR) and data throughput in future ISAC networks, with room for further tuning of grid density and coding strategies.

Abstract

Bistatic integrated sensing and communication (ISAC) enables efficient reuse of the existing cellular infrastructure and is likely to play an important role in future sensing networks. In this context, ISAC using the data channel is a promising approach to improve the bistatic sensing performance compared to relying solely on pilots. One of the challenges associated with this approach is resource allocation: the communication link aims to transmit higher modulation order (MO) symbols to maximize the throughput, whereas a lower MO is preferable for sensing to achieve a higher signal-to-noise ratio in the radar image. To address this conflict, this paper introduces a hybrid resource allocation scheme. By placing lower MO symbols as pseudo-pilots on a suitable sensing grid, we enhance the bistatic sensing performance while only slightly reducing the spectral efficiency of the communication link. Simulation results validate our approach against different baselines and provide practical insights into how decoding errors affect the sensing performance.

Hybrid Resource Allocation Scheme for Bistatic ISAC with Data Channels

TL;DR

This work tackles resource allocation in bistatic ISAC by embedding low-order, easily decodable symbols as pseudo-pilots on a sensing grid within the data channel. The hybrid scheme balances sensing gains with communication efficiency by decoding lower-MO symbols at the bistatic receiver, enabling improved estimation of the sensing matrix and a higher range-Doppler resolution without fully sacrificing throughput. Through a complete processing pipeline and simulations, the authors demonstrate improved bistatic sensing performance over a comm-centric baseline, quantify the spectral efficiency trade-off (≈3%), and provide insights on how decoding errors influence sensing quality. The approach offers practical guidance for jointly optimizing sensing requirements (unambiguous range/Doppler, SNR) and data throughput in future ISAC networks, with room for further tuning of grid density and coding strategies.

Abstract

Bistatic integrated sensing and communication (ISAC) enables efficient reuse of the existing cellular infrastructure and is likely to play an important role in future sensing networks. In this context, ISAC using the data channel is a promising approach to improve the bistatic sensing performance compared to relying solely on pilots. One of the challenges associated with this approach is resource allocation: the communication link aims to transmit higher modulation order (MO) symbols to maximize the throughput, whereas a lower MO is preferable for sensing to achieve a higher signal-to-noise ratio in the radar image. To address this conflict, this paper introduces a hybrid resource allocation scheme. By placing lower MO symbols as pseudo-pilots on a suitable sensing grid, we enhance the bistatic sensing performance while only slightly reducing the spectral efficiency of the communication link. Simulation results validate our approach against different baselines and provide practical insights into how decoding errors affect the sensing performance.
Paper Structure (9 sections, 9 equations, 5 figures, 1 table)

This paper contains 9 sections, 9 equations, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. System Model
  3. Hybrid Resource Allocation Scheme
  4. Bistatic Sensing Processing
  5. Results and Discussion
  6. Bistatic Sensing Scenario
  7. Bistatic Sensing Performance
  8. Impact of decoding errors on sensing performance
  9. Conclusion

Figures (5)

  • Figure 1: Bistatic ISAC system model. In this example, a static reference path labeled as $p=0$ and a path $p=1$ associated with a radar target that is opportunistically illuminated by a transmission originally intended to an UE are shown. Here, $r_p=r^\text{TX--T}_p+r^\text{T--Rx}_p$ is the bistatic range resulting from the sum of the range $r^\text{Tx--T}_p$ between TX and target and the range $r^\text{T--RX}_p$ between target and RX. In addition, a Doppler shift $f_{\mathrm{D},p}=f^\text{TX---T}_{\mathrm{D},p}+f^\text{T---RX}_{\mathrm{D},p}$ is experienced.
  • Figure 2: Example of a hybrid resource allocation scheme, illustrated using one prb spanning $N=12$ subcarriers and $M=14$ symbols. A lower is used on every $K_\text{F} = K_\text{T} = 4$th (blue squares). The remaining grey use a higher .
  • Figure 3: Processing pipeline for bistatic sensing.
  • Figure 4: Target SNR in the periodogram and probability of detection for our proposal "Hybrid Scheme" (red), "Comm-centric" (green), "Pilots" (grey), and "Genie-aided" (blue), both as functions of the receive SNR before radar processing.
  • Figure 5: ser at the bistatic for our proposal "Hybrid Scheme" (red) and "Comm-centric" (green) as function of the receive SNR before radar processing.

Theorems & Definitions (1)

  • Remark 1