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Zhiquan Liu

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2026

Joint Power and Location Design for Energy-Efficient Covert UAV Communications

—Unmanned aerial vehicles (UAVs) have been extensively deployed in wireless communication scenario. However, UAV communication faces the challenges of information leakage and energy limitation. Therefore, this paper studies energy-efficient covert communication in adversarial UAV-enabled wireless systems, where a UAV covertly delivers information to a legitimate ground receiver under the detection of a malicious detector with noise uncertainty. Our objective is to maximize covert energy efficiency, defined as the achievable covert throughput per unit of energy consumption, via the joint design of transmit power and flying location. To this end, we derive the detector’s minimum detection error probability to establish a covertness constraint. Based on this model, we formulate a three-dimensional joint optimization problem for transmit power and two-dimensional location, capturing the fundamental tradeoff among covertness, communication reliability, and energy efficiency. Through sys-tem geometric exploration, metric monotonicity analysis, and theoretical derivation, the original three-dimensional problem is reduced to a one-dimensional search over the flying angle, which enables efficient computation of the optimal UAV configuration via vectorized computation. Numerical results verify the theoretical derivations and illustrate the superiority of the joint design as well as the impact of system parameters on energy efficiency performance.

Yang-Fan Xu, Bin Yang, Yulong Shen et al. · 0 citations
Preprint Jul 2026

RT-SHCUA: Real-Time Self-Hosted Computer-Use Agent for UAV Control

This paper proposes a real-time and security-oriented restructuring of SHCUA-based UAV control, which transforms its outputs into contract-bound UAV skill invocations with explicit timing, state, authority, fallback, and evidence semantics.

Di Lu, Bo Zhang, Xiyuan Li et al. · 0 citations
#edge computing Sep 2026

Utility-Aware Resource Allocation for Hybrid NOMA in MEC: A Matching-Coalition Game Approach

The massive influx of uplink task offloading in Multi-access Edge Computing (MEC) systems poses a significant challenge to the capacity of wireless networks. This challenge highlights a fundamental trade-off between Orthogonal Multiple Access (OMA), which provides interference-free but spectrally inefficient communication, and Non-Orthogonal Multiple Access (NOMA), which enhances capacity at the cost of significant inter-user interference. To navigate this trade-off, we introduce a novel Hybrid NOMA (H-NOMA) framework that offers differentiated communication services. The framework allows users to choose between premium OMA channels for latency-sensitive tasks and shared NOMA channels for others, creating an economy where performance can be traded for cost. Within this framework, we formulate the resource allocation problem with the objective of maximizing the total system utility, defined as the sum of all individual user utilities, under budget, computation, and communication constraints. To solve this NP-hard problem, we devise a novel multi-stage game-theoretic algorithm, the Matching-Coalition Game with Coordinate Descent (MCGCD). Our approach synergistically combines matching theory for a fast and initial channel assignment, a cooperative coalition game to refine allocations by explicitly managing NOMA externalities, and a coordinate-descent-based algorithm for optimal power control. Extensive simulations demonstrate that our proposed algorithm significantly outperforms benchmark methods in improving system utility, reducing average task completion latency, and increasing the number of admitted tasks.

Haolin Liu, Hao Yin, Haibo Zhou et al. · 0 citations