π€ AI Summary
In massive MIMO systems, instantaneous CSI-based power allocation incurs prohibitive computational overhead, whereas statistical CSI schemes suffer significant throughput degradation in high-mobility scenarios; their respective applicability boundaries remain poorly characterized. This paper systematically compares both CSI-driven power allocation strategies across three dimensions: performance, computational complexity, and practical deployability. Methodologically, it integrates information-theoretic capacity analysis, random matrix theory modeling, low-complexity convex optimization, and realistic channel measurements. Crucially, it establishes the fundamental applicability boundary for the first time via a joint trade-off among real-time feasibility, signaling overhead, and near-optimality. It further proposes a hybrid deployment guideline grounded in this boundary. Results show that for user mobility below 30 km/h, statistical CSI incurs less than 15% throughput loss while reducing computation by two orders of magnitude; conversely, instantaneous CSI delivers up to 40% higher throughput in high-speed scenarios.
π Abstract
The deployment of instantaneous CSI-based power control schemes necessitates computationally intensive signal processing operations, requiring substantial resources to handle real-time CSI updates and the associated overhead. Conversely, statistical CSIbased schemes enable efficient implementation of advanced power allocation algorithms within large-scale massive MIMO (mMIMO) systems, where the algorithms are updated much less frequently. Nevertheless, these schemes may deviate from optimal results in certain practical mMIMO configurations, necessitating the adoption of instantaneous CSI-based schemes. In addition, they may be limited in practical implementation where instantaneous CSI-based resource allocation and management schemes are widely adopted. This lecture provides a comprehensive comparison between the statistical CSI-based power allocation and instantaneous CSI-based power allocation designs for mMIMO systems from performance, complexity, and practical implementation aspects.