[Paper Review] A Shared Cluster-based Stochastic Channel Model for Integrated Sensing and Communication Systems

Yameng Liu, Jianhua Zhang+3 more|arXiv (Cornell University)|Nov 12, 2022

Indoor and Outdoor Localization Technologies4 citations

TL;DR

This paper proposes a shared cluster-based stochastic channel model for joint communication and sensing (JCAS) systems, jointly generating communication and sensing channels by superimposing shared and non-shared clusters to reflect real-world hardware and propagation resource sharing. The model is validated via 28 GHz measurements and simulations, demonstrating realistic clustering features and controllable sharing degrees (SDs of 0.54–0.65), with a novel KPM-JCA clustering algorithm enabling accurate extraction of shared scatterers.

ABSTRACT

Integrated Sensing And Communication (ISAC) has been recognized as a promising technology in the 6G communication. A realistic channel model is a prerequisite for designing ISAC systems. Most existing channel models independently generate the communication and sensing channels under the same framework. However, due to the multiplexing of hardware resources and the same environment, signals enabled for communication and sensing may experience shared propagation scatterers. This practical sharing feature necessities the joint generation of communication and sensing channels for realistic modeling, where the shared clusters (contributed by the shared scatterers) should be reconstructed.In this paper, we first conduct communication and sensing channel measurements for an indoor scenario at 28 GHz. The power-angular-delay profiles of multipath components are obtained, and the shared scatterers by communication and sensing channels are intuitively observed. Then, a stochastic ISAC channel model is proposed to capture the sharing feature, where shared and non-shared clusters by the two channels are dfined and superimposed. To extract those clusters from measured ISAC channels, a KPowerMeans-based joint clustering algorithm is novelly introduced. Finally, stochastic channel characteristics are analyzed, and empirical simulations validate that the channel Sharing Degree (SD) increases with more shared clusters. The proposed model can realistically capture the sharing feature of ISAC channels and is able to evaluate and simulate the channel SD values, which is valuable for the design and deployment of ISAC systems.

Motivation & Objective

• To address the lack of realistic JCAS channel models that account for shared propagation scatterers between communication and sensing.
• To model the joint generation of communication and sensing channels by incorporating shared clusters derived from common scatterers.
• To develop a clustering algorithm capable of extracting shared and non-shared clusters from measured JCAS channels.
• To validate the model’s practicality and controllability using real-world 28 GHz measurements and empirical simulations.

Proposed method

• Conducts a 28 GHz indoor channel measurement campaign in LOS and NLOS scenarios using horn antenna rotation to capture communication and sensing multipath components (MPCs).
• Analyzes power-angular-delay profiles (PADPs) to visually identify shared scatterers between communication and sensing channels.
• Proposes a stochastic JCAS channel model based on superimposed shared and non-shared clusters, with shared clusters representing common scatterers.
• Introduces a novel KPowerMeans-based joint clustering algorithm (KPM-JCA) to jointly extract shared and non-shared clusters from joint communication and sensing channels.
• Parameterizes the model using inter-cluster angular spread (AS), delay spread (DS), and sharing degree (SD), derived from measured clustering results.
• Validates the model through simulations by controlling the number of shared clusters (N₀) to match empirical SD values and assess angular distribution similarity.

Experimental results

Research questions

• RQ1 How do shared scatterers manifest in the power-angular-delay profiles of jointly measured communication and sensing channels?
• RQ2 To what extent do communication and sensing channels share common propagation clusters in real indoor environments at 28 GHz?
• RQ3 Can a stochastic JCAS channel model effectively capture the joint clustering behavior of communication and sensing signals through shared and non-shared cluster superposition?
• RQ4 How can a joint clustering algorithm extract shared and non-shared clusters from combined communication and sensing channel data?
• RQ5 To what degree can the model’s parameters be controlled to reproduce realistic sharing degrees (SD) observed in measurements?

Key findings

• The measurement campaign revealed shared scatterers in both LOS and NLOS scenarios, with shared MPCs showing stronger clustering in the angular domain than in the delay domain.
• The sharing degree (SD) of shared clusters was quantified as 0.65 and 0.64 in two LOS measurements, and 0.54 in one NLOS measurement.
• Simulations confirmed that increasing the number of shared clusters (N₀) increases the SD, with N₀ = 10 yielding a mean SD of 0.66, closely matching measured values.
• The communication channel clusters were found to be more concentrated and sparse in angular distribution, while sensing clusters were more discretely distributed.
• The KPM-JCA algorithm successfully extracted shared and non-shared clusters, enabling accurate joint modeling of communication and sensing channels.
• The model demonstrated practicality and controllability, as it could reproduce realistic channel characteristics by tuning N₀ to match empirical SD values.