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Beamforming Design for ISAC Systems with Suppressed Range-Angle Sidelobes

Meihui Liu, Shu Sun, Ruifeng Gao, Meixia Tao

TL;DR

This work tackles the challenge of joint sensing and communication in ISAC by introducing a beamforming design that suppresses range-angle sidelobes in the ambiguity function (AF). It formulates a non-convex optimization to minimize the integrated sidelobe level ratio (ISLR) of the AF under transmit power, communication SINR, and sensing-gain constraints, and solves it using semidefinite relaxation (SDR) to obtain a convex reformulation (P2). The approach leverages MIMO DoFs to shape the transmit beampattern while preserving downlink performance, with complexity analyzed for the convex solver and high-rank solutions handled via standard randomization techniques. Numerical results show substantial range sidelobe suppression (up to ~33 dB) and robust sensing performance across SINR levels, outperforming baselines and indicating strong potential for practical ISAC deployments.

Abstract

Integrated sensing and communication (ISAC) represents a pivotal advancement for future wireless networks. This paper introduces a novel ISAC beamforming method for enhancing sensing performance while preserving communication quality by leveraging the ambiguity function (AF). We formulate an optimization problem to minimize the integrated sidelobe level ratio (ISLR) of the AF subject to the constraints of transmission power, communication signalto-interference-plus-noise ratio, and sensing gain. To address the non-convexity of the optimization problem, semidefinite relaxation is adopted. Numerical results show that our method significantly reduces range sidelobes and achieves a lower ISLR in the rangeangle domain compared to other approaches.

Beamforming Design for ISAC Systems with Suppressed Range-Angle Sidelobes

TL;DR

This work tackles the challenge of joint sensing and communication in ISAC by introducing a beamforming design that suppresses range-angle sidelobes in the ambiguity function (AF). It formulates a non-convex optimization to minimize the integrated sidelobe level ratio (ISLR) of the AF under transmit power, communication SINR, and sensing-gain constraints, and solves it using semidefinite relaxation (SDR) to obtain a convex reformulation (P2). The approach leverages MIMO DoFs to shape the transmit beampattern while preserving downlink performance, with complexity analyzed for the convex solver and high-rank solutions handled via standard randomization techniques. Numerical results show substantial range sidelobe suppression (up to ~33 dB) and robust sensing performance across SINR levels, outperforming baselines and indicating strong potential for practical ISAC deployments.

Abstract

Integrated sensing and communication (ISAC) represents a pivotal advancement for future wireless networks. This paper introduces a novel ISAC beamforming method for enhancing sensing performance while preserving communication quality by leveraging the ambiguity function (AF). We formulate an optimization problem to minimize the integrated sidelobe level ratio (ISLR) of the AF subject to the constraints of transmission power, communication signalto-interference-plus-noise ratio, and sensing gain. To address the non-convexity of the optimization problem, semidefinite relaxation is adopted. Numerical results show that our method significantly reduces range sidelobes and achieves a lower ISLR in the rangeangle domain compared to other approaches.

Paper Structure

This paper contains 10 sections, 24 equations, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. System Model
  3. Communication Model
  4. Sensing Model
  5. Ambiguity Function
  6. Beamforming Design for Sidelobes Surppression
  7. Problem Formulation
  8. Complexity Analysis
  9. Simulation Results
  10. Conclusion

Figures (5)

  • Figure 1: Range-angle AF for different designs. (a) proposed; (b) only sensing: min ISL, s.t. M1 & M3; (c) only communication: max-min M2, s.t. M1; (d) joint design 1: max M3, s.t. M1 & M2; (e)-(f) joint design 2, 3: {beampattern matching, minimum weighted beam gain maximization}, s.t. M1 & M2 in 10086626. (M1, M2, and M3 correspond to equations (17a), (4), and (16) in this paper, respectively.)
  • Figure 2: Range cut of the AF for proposed design.
  • Figure 3: Angle cut of the AF for proposed design.
  • Figure 4: Beampattern for proposed design.
  • Figure 5: ISL ratio with communication SINR for different designs