A Broadcast Channel Framework for MIMO-OFDM Integrated Sensing and Communication

2025-09-13

AI Summary

6G-oriented MIMO-OFDM integrated sensing and communication (ISAC) systems face fundamental challenges in jointly designing communication and sensing functionalities. To address this, we formulate ISAC as a broadcast channel and introduce the novel concept of “virtual sensing users,” unifying communication users and sensing targets under a common framework to enable waveform, spectrum, and hardware sharing. Methodologically, we integrate dirty-paper coding (DPC), frequency-division multiplexing (FDM), and superposition coding with a waveform optimization algorithm that explicitly models clutter and Doppler effects. Theoretically, we establish the first unified information-theoretic analysis framework for ISAC—applicable to both known and unknown sensing waveform scenarios. Numerical results demonstrate significant and balanced improvements in both sensing accuracy and communication rate, validating the effectiveness and flexibility of our multiplexing-based approach for ISAC.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Security and Privacy: Large-scale security measurements
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

Integrated sensing and communication (ISAC) is expected to be one of the major features of 6G wireless networks. In an ISAC system, communications and sensing functionalities are jointly performed using the same waveform, frequency band and hardware, thereby enabling various use cases such as in cyber physical systems, digital twin and smart cities. A major challenge to the design and analysis of ISAC is a unified framework that incorporates the two distinct functions. By viewing ISAC as a type of broadcast channel, in this paper, we propose a unified ISAC framework in which communication and sensing signals are broadcast to the actual communication users and virtual sensing users. This framework allows the application of existing multiplexing schemes, such as dirty paper coding (DPC) and frequency division multiplexing (FDM) that have been intensively studied in data communications and information theory. Within this framework, we propose different superposition coding schemes, for cases when the sensing waveform is known or unknown to the communication receiver. We propose the waveform optimization algorithms in a multiple-input multiple-output (MIMO) setting accounting for the effects of clutter and Doppler shift. The proposed framework is numerically evaluated for different schemes under various sensing and communications performance metrics.

Problem

• Unified framework for integrating communication and sensing functions
• Waveform optimization in MIMO-OFDM systems with clutter effects
• Superposition coding schemes for known and unknown sensing waveforms

Innovation

• Broadcast channel framework for MIMO-OFDM ISAC
• Superposition coding schemes for known/unknown waveforms
• Waveform optimization algorithms accounting for clutter/Doppler