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CISSIR: Beam Codebooks with Self-Interference Reduction Guarantees for Integrated Sensing and Communication Beyond 5G

Rodrigo Hernangómez, Jochen Fink, Renato L. G. Cavalcante, Sławomir Stańczak

TL;DR

The paper addresses SI challenges in ISAC by proposing CISSIR, a multipath-aware beam codebook design that reduces SI and supports sensing guarantees while remaining compatible with 5G-NR codebooks. It develops a decoupled optimization framework that yields either semi-closed-form solutions for tapered beamforming or SDP-based solutions for phased arrays, together with analytical bounds that connect SI to ADC quantization and saturation. The approach demonstrably improves sensing SNR and provides acceptable, tunable trade-offs in communication performance, validated through link-level simulations and ray-tracing. This work offers a practical, interpretable, and performance-guaranteed path toward ISAC beyond 5G, with ready-to-implement design methodologies and public code for reproducibility.

Abstract

We propose a beam codebook design for integrated sensing and communication (ISAC) that reduces self-interference (SI) to alleviate analog distortion. Our optimization framework, which considers either tapered beamforming or phased arrays for both analog and hybrid schemes, modifies given reference codebooks such that a certain SI power level is achieved. In contrast to other low-SI codebooks, which often rely on hardly interpretable optimization parameters, we provide design guidelines to obtain sensing performance guarantees by deriving analytical bounds on saturation and analog-to-digital quantization in relation to the multipath SI level. By selecting standard reference codebooks in our simulations, we show how our method substantially improves the signal-to-noise ratio for sensing with little impact on 5G-NR communication.

CISSIR: Beam Codebooks with Self-Interference Reduction Guarantees for Integrated Sensing and Communication Beyond 5G

TL;DR

The paper addresses SI challenges in ISAC by proposing CISSIR, a multipath-aware beam codebook design that reduces SI and supports sensing guarantees while remaining compatible with 5G-NR codebooks. It develops a decoupled optimization framework that yields either semi-closed-form solutions for tapered beamforming or SDP-based solutions for phased arrays, together with analytical bounds that connect SI to ADC quantization and saturation. The approach demonstrably improves sensing SNR and provides acceptable, tunable trade-offs in communication performance, validated through link-level simulations and ray-tracing. This work offers a practical, interpretable, and performance-guaranteed path toward ISAC beyond 5G, with ready-to-implement design methodologies and public code for reproducibility.

Abstract

We propose a beam codebook design for integrated sensing and communication (ISAC) that reduces self-interference (SI) to alleviate analog distortion. Our optimization framework, which considers either tapered beamforming or phased arrays for both analog and hybrid schemes, modifies given reference codebooks such that a certain SI power level is achieved. In contrast to other low-SI codebooks, which often rely on hardly interpretable optimization parameters, we provide design guidelines to obtain sensing performance guarantees by deriving analytical bounds on saturation and analog-to-digital quantization in relation to the multipath SI level. By selecting standard reference codebooks in our simulations, we show how our method substantially improves the signal-to-noise ratio for sensing with little impact on 5G-NR communication.

Paper Structure

This paper contains 25 sections, 7 theorems, 60 equations, 7 figures, 2 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Notation and preliminaries
  3. System model and problem formulation
  4. System model
  5. The optimization problem
  6. Proposed scheme
  7. Problem decoupling
  8. Tapered beamforming
  9. Phased-array optimization
  10. Performance bounds and parameter selection
  11. Self-interference impact at the ADC
  12. Signal-to-noise ratio for analog OFDM radar
  13. Selection of the target self-interference
  14. Matched optimization
  15. Average optimization
  16. ...and 10 more sections

Key Result

Proposition 1

Let ${\mathbf G}_{\mathrm{tx}}\in{\mathbb S}^N_+$ and ${\mathbf G}_{\mathrm{rx}}\in{\mathbb S}^M_+$ be the integral split (see def:svd) of ${\mathbf S}(t)$ in eq:maxsi, and consider the quantity ($\forall\,{\mathbf C}\in\mathcal{C}^{K'},\,\forall\,{\mathbf W}\in\mathcal{W}^{L'}$):

Figures (7)

  • Figure 1: System model: beam codebooks in the face of multipath si. Amplifiers and filters are omitted for simplicity.
  • Figure 2: range profiles with reference and -optimized / analog beamformers pointing towards a target at -39°.
  • Figure 3: Simulated sensing and (symbol-averaged noise and 99% interval), with approximate bound for high , in function of the target $\varepsilon$.
  • Figure 4: Orthogonal beams from the reference ${\mathbf A}$ ($\varepsilon=$-54.5dB) and from ${\mathbf W}$ ($\varepsilon=$-100.5dB), with color-matched nominal beam direction.
  • Figure 5: bler for different analog and hybrid codebooks. The solid lines correspond to the reference codebook.
  • ...and 2 more figures

Theorems & Definitions (17)

  • Definition 1: Integral split
  • Proposition 1
  • proof
  • Remark 1
  • Remark 2
  • Proposition 2
  • proof
  • Proposition 3
  • proof
  • Lemma 1
  • ...and 7 more