Fundamental Limits of Random Downlink Integrated Sensing and Communication over Rician Channels

2026-07-01

AI Summary

This study addresses the impact of deterministic line-of-sight (LoS) components on communication and sensing performance in downlink MIMO integrated sensing and communication systems operating over Rician fading channels. The authors propose and analyze two beamforming strategies—subspace joint beamforming (SJB) and linear beamforming (LB)—and, for the first time, derive outage probabilities under arbitrary and potentially correlated angular distributions of users and targets by leveraging the Cramér–Rao bound and random matrix theory to establish fundamental performance limits. Theoretical and simulation results reveal that the Rician K-factor affects communication reliability more significantly than sensing performance, with overall system performance exhibiting a non-monotonic dependence on K. LB combined with dirty-paper coding achieves optimal overall performance under strong LoS conditions and is the only scheme capable of supporting ultra-high communication reliability in Rayleigh fading, whereas SJB offers a low-complexity and robust alternative.

Abstract

This paper studies the stochastic performance of a downlink multiple-input multiple-output integrated sensing and communication (ISAC) system over Rician fading channels. Rician fading is important in line-of-sight (LoS)-dominated deployments, where a deterministic propagation component can strongly affect sensing and communication reliability. The base station (BS) simultaneously serves a user and senses a target. The BS-user channel contains LoS and non-line-of-sight components. The user LoS angle may be fixed or random, and the target angle may follow an arbitrary distribution potentially correlated with the user angle. Compared with Rayleigh fading, the deterministic LoS component introduces angle-dependent terms and leads to generally independent but non-identically distributed random vectors, requiring new analysis. We analyze two beamforming strategies: subspace joint beamforming (SJB), optimal for the shared waveform structure, and linear beamforming (LB), a practical alternative using separate sensing and communication beamformers. For both schemes, we derive communication outage probability (OP) and sensing OP based on the Cramer--Rao bound (CRB). We also identify special cases with simpler expressions. For LB, we derive upper and lower bounds on sensing OP and a tractable approximation. We characterize large-system and high-power scaling laws. LB without dirty paper coding (DPC) is interference-limited at high power due to radar self-interference. Results show the Rician K-factor affects communication more strongly than sensing, with non-monotonic behavior across regimes. LB with DPC achieves the best overall performance in strong LoS environments and is the only scheme achieving ultra-high communication reliability in Rayleigh fading, while SJB provides a robust lower-complexity alternative across operating conditions.

Problem

• Integrated Sensing and Communication
• Rician Fading
• Downlink MIMO
• Outage Probability
• Line-of-Sight

Innovation

• Integrated Sensing and Communication (ISAC)
• Rician fading
• Beamforming
• Cramér–Rao bound (CRB)
• Outage probability