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Indrakshi Dey

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Preprint Aug 2026

Degeneracy-Aware Resource Allocation for Resilient 6G RAN

Heterogeneous 6G radio access networks (RANs) must allocate resources reliably under interference, latency limits, imperfect channel state information (CSI), and architectural diversity. We propose a degeneracy-aware resource allocation (DG-RA) framework that casts multi-architecture orchestration as a probabilistic game and, unlike single-solution optimization, deliberately favors allocations realizable by many structurally distinct yet performance-equivalent strategy profiles. Resilience is quantified across three layers through Degeneracy-Weighted Path Robustness (DWPR), Functional Substitution Score (FSS), and an Algorithmic Resilience Quotient (ARQ). Across centralized (C-RAN), open (O-RAN), virtualized (V-RAN), and hybrid RAN architectures, and benchmarked against a fractional-programming optimizer, DG-RA matches the state-of-the-art throughput and outage at the static operating point, then exploits its equivalence set to recover $\sim$$99\%$ of throughput from a resource-unit failure with a single switch, where a single-solution optimizer needs tens of iterations to re-converge. The results recast degeneracy not as a rate booster but as a precomputed resilience reserve for disruption-tolerant 6G orchestration.

Sayan Ghosh, Indrakshi Dey, Nicola Marchetti · 0 citations
Preprint Aug 2026

Certifying Collective Reasoning in Multi-Agent Systems via Koopman Spectral Analysis

A novel framework based on Koopman operator theory is developed and validates its theoretical guarantees on multi-agent consensus dynamics, making spectral certification a practical layer for trustworthy collective reasoning.

N. Khan, Indrakshi Dey · 0 citations

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