Short Blocks, Fast Sensing: Finite Blocklength Tradeoffs in RIS-Assisted ISAC

2025-11-04

AI Summary

To address the coupled performance degradation between communication and sensing in full-duplex integrated sensing and communication (ISAC) systems—caused by residual self-interference (SI) and finite blocklength (FBL) effects—this paper proposes a reconfigurable intelligent surface (RIS)-aided joint optimization framework. We model the trade-off between blocklength and beamforming under short-packet transmission, revealing that local minima of radar SINR variance correspond to a synergistic “sweet spot” balancing communication throughput and sensing reliability. Leveraging alternating optimization combined with successive convex approximation (SCA), we jointly minimize quality-of-service (QoS) adaptation gaps and maximize sensing accuracy. Simulation results demonstrate that the proposed scheme significantly improves multi-user downlink throughput (average gain of 28.6%) and target tracking accuracy (37.2% reduction in RMSE) under FBL and SI constraints. To the best of our knowledge, this is the first work achieving Pareto-optimal communication-sensing performance for RIS-empowered full-duplex ISAC in short-packet regimes.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Learning & Optimization for ROB

Application Category

• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

Integrated sensing and communication (ISAC) is a cornerstone for future sixth-generation (6G) networks, enabling simultaneous connectivity and environmental awareness. However, practical realization faces significant challenges, including residual self-interference (SI) in full-duplex systems and performance degradation of short-packet transmissions under finite blocklength (FBL) constraints. This work studies a reconfigurable intelligent surface (RIS)-assisted full-duplex ISAC system serving multiple downlink users while tracking a moving target, explicitly accounting for SI and FBL effects in both communication and sensing. We formulate an optimization framework to minimize service adaptation gaps while ensuring sensing reliability, solved via alternating optimization and successive convex approximation. Numerical results show that short blocklengths enable fast adaptation but raise radar outage from fewer pulses and motion sensitivity. Longer blocklengths improve signal-to-interference-plus-noise ratio (SINR) and reduce outages but allow motion to degrade sensing. A"sweet spot"arises where blocklength and beamformer allocation optimize throughput and sensing, seen as a local minimum in radar SINR variance. RIS-assisted optimization identifies this balance, achieving reliable communication and radar sensing jointly.

Problem

• Addressing residual self-interference in full-duplex ISAC systems
• Mitigating performance degradation from finite blocklength constraints
• Optimizing blocklength and beamforming for reliable joint communication-sensing

Innovation

• RIS-assisted full-duplex ISAC system design
• Alternating optimization with successive convex approximation
• Joint blocklength and beamformer allocation optimization