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Mingxu Yang

Publications and source records attributed to Mingxu Yang.

3 recordsLinked to original sources

Grid-Interactive Operation of Solar-Integrated Data Centers for Coordinated Local and System-Level Decarbonization

The exponential growth of AI is accelerating the deployment of data centers (DCs), placing unprecedented strain on power infrastructures. In response, major IT corporations are increasingly adopting on-site solar generation to reduce grid dependence and meet sustainability targets. However, the true impacts of this strategy remain ambiguous. While DCs are flexible assets capable of temporal load-shifting, anchoring them to self-generated power may inadvertently constrain their grid responsiveness. To evaluate these trade-offs, we propose a receding-horizon optimization (RHO) framework coordinating job scheduling, grid interactions, and on-site solar generation for a stand-alone DC. Our findings reveal a critical paradox: although solar integration increases energy self-sufficiency and reduces overall DC emissions, it inherently limits the facility's capacity to absorb low-cost, low-carbon electricity from the grid. This implies a fundamental tension between individual corporate sustainability goals and system-wide grid decarbonization.

math.OC

Secure Offloading in NOMA-Aided Aerial MEC Systems Based on Deep Reinforcement Learning

Mobile edge computing (MEC) technology can reduce user latency and energy consumption by offloading computationally intensive tasks to the edge servers. Unmanned aerial vehicles (UAVs) and non-orthogonal multiple access (NOMA) technology enable the MEC networks to provide offloaded computing services for massively accessed terrestrial users conveniently. However, the broadcast nature of signal propagation in NOMA-based UAV-MEC networks makes it vulnerable to eavesdropping by malicious eavesdroppers. In this work, a secure offload scheme is proposed for NOMA-based UAV-MEC systems with the existence of an aerial eavesdropper. The long-term average network computational cost is minimized by jointly designing the UAV's trajectory, the terrestrial users' transmit power, and computational frequency while ensuring the security of users' offloaded data. Due to the eavesdropper's location uncertainty, the worst-case security scenario is considered through the estimated eavesdropping range. Due to the high-dimensional continuous action space, the deep deterministic policy gradient algorithm is utilized to solve the non-convex optimization problem. Simulation results validate the effectiveness of the proposed scheme.

cs.IT

Dynamic Resource Management in CDRT Systems through Adaptive NOMA

This paper introduces a novel adaptive transmission scheme to amplify the prowess of coordinated direct and relay transmission (CDRT) systems rooted in non-orthogonal multiple access principles. Leveraging the maximum ratio transmission scheme, we seamlessly meet the prerequisites of CDRT while harnessing the potential of dynamic power allocation and directional antennas to elevate the system's operational efficiency. Through meticulous derivations, we unveil closed-form expressions depicting the exact effective sum throughput. Our simulation results adeptly validate the theoretical analysis and vividly showcase the effectiveness of the proposed scheme.

cs.IT