[Paper Review] ISAC-Enabled Beam Alignment for Terahertz Networks: Scheme Design and Coverage Analysis

Wenrong Chen, Lingxiang Li+4 more|arXiv (Cornell University)|Dec 4, 2022

Millimeter-Wave Propagation and Modeling40 references4 citations

TL;DR

This paper proposes a joint SSB and reference signal (JSRS)-based sensing scheme for terahertz (THz) networks to mitigate beam misalignment caused by blockage and mobility. By leveraging ISAC-enabled sensing with optimized signal patterns, the scheme reduces beam misalignment by ~80% and boosts coverage probability by ~75% compared to 5G-only positioning, while maintaining compatibility with 5G beam management.

ABSTRACT

As a key pillar technology for the future 6G networks, Terahertz (THz) communications can provide high-capacity transmissions, but suffers from severe propagation loss and line-of-sight (LoS) blockage that limits the network coverage. Narrow beams are required to compensate for the loss, but they in turn bring in beam misalignment challenge and degrade the THz network coverage. The high sensing resolution of THz signals enables integrated sensing and communications (ISAC) technology to assist the LoS blockage and user mobility-induced beam misalignment, enhancing THz network coverage. Based on the 5G beam management, we propose a joint synchronization signal block (SSB) and reference signal (RS)-based sensing (JSRS) scheme to assist beam alignment. JSRS enables a predict-and-prevent procedure that provides early interventions for timely beam switches. To maximize performance of JSRS, we provide an optimal sensing signal insertion and time-to-frequency allocation to improve the joint range and velocity resolutions. We derive the coverage probability of the JSRS-enabled network to evaluate its abilities in beam misalignment reduction and coverage enhancement. The expression also instructs the network density deployment and beamwidth selection. Numerical results show that the JSRS scheme is effective and highly compatible with the 5G air interface. Averaged in the tested urban use cases, JSRS achieves near-ideal performance and reduces around 80% of beam misalignment, and enhances the coverage probability by about 75%, compared to the network with 5G-required positioning ability.

Motivation & Objective

• To address beam misalignment in THz networks caused by severe path loss and line-of-sight (LoS) blockage.
• To design a sensing-aided beam alignment scheme compatible with 5G beam management procedures.
• To optimize sensing signal configuration under fixed resource constraints for minimal beam misalignment.
• To derive network-level performance metrics—coverage probability and spatial throughput—for ISAC-THz networks.
• To evaluate the performance gain of sensing assistance in real-world urban deployment scenarios.

Proposed method

• Proposes a joint SSB and reference signal (JSRS)-based sensing scheme to predict beam switch needs and prevent misalignment.
• Designs an optimal sensing signal pattern that minimizes beam misalignment under fixed sensing resource constraints, revealing time-to-frequency allocation insights.
• Uses stochastic geometry to model BS and user distributions, enabling tractable coverage and throughput analysis.
• Derives the Laplace transform of interference power using probability generating functional (PGFL) of a PPP point process.
• Applies Euler’s formula and conjugate symmetry to decompose complex-valued interference Laplace functional into real and imaginary parts for integration.
• Integrates sensing-based beam misalignment probability into coverage probability and spatial throughput expressions using derived Laplace transforms.

Experimental results

Research questions

• RQ1 How can ISAC be leveraged to reduce beam misalignment in THz networks under LoS blockage and mobility?
• RQ2 What is the optimal configuration of sensing signals (time and frequency allocation) that minimizes beam misalignment with fixed resources?
• RQ3 To what extent does ISAC improve network-level coverage probability and spatial throughput in THz systems?
• RQ4 How compatible is the proposed ISAC-aided beam alignment scheme with existing 5G beam management procedures?
• RQ5 What is the performance gain of ISAC over conventional 5G positioning in urban deployment scenarios?

Key findings

• The JSRS scheme reduces beam misalignment by approximately 80% compared to a 5G network with only positioning capability.
• Coverage probability improves by about 75% when using the JSRS scheme versus the 5G-only positioning baseline in tested urban scenarios.
• The proposed scheme achieves near-ideal performance in urban use cases, demonstrating strong practical feasibility.
• The derived coverage probability and spatial throughput expressions provide actionable design guidelines for ISAC-THz network deployment.
• The optimal sensing signal pattern design reveals that time and frequency resource allocation significantly impacts beam misalignment mitigation.
• The ISAC-THz network achieves high spectral efficiency and low-latency beam management due to shared waveform and hardware between sensing and communication.