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Wenpeng Jing

Publications and source records attributed to Wenpeng Jing.

2 recordsLinked to original sources

Reconfigurable Intelligent Surface-Enhanced Satellite Networks: Deployment Strategies, Key Capabilities, Practical Solutions, and Future Directions

Satellite networks promise wide-area 6G coverage but face two persistent barriers: blockage-induced service discontinuities and increasingly stringent spectrum coexistence across satellite layers and with terrestrial systems. Reconfigurable intelligent surfaces (RISs) act as low-power programmable apertures that redirect energy without the cost and power consumption of fully active arrays. We develop a deployment-first, operations-aware view of RIS-enabled satellite networking that treats RIS as both satellite/terminal antennas and inter-satellite or space-ground relays. We show that system-level gains are governed by two unifying mechanisms: connectivity restoration via virtual line-of-sight links that preserve connectivity under blockage and mobility, and angular selectivity that reshapes interference to enlarge spectrum reuse. We further discuss practical operation under high mobility, highlighting Delay-Doppler channel acquisition, predictive beam tracking, and control designs that budget overhead and latency, and summarize hardware considerations for reliable operation in space. Finally, we outline forward-looking opportunities in the generative artificial intelligence paradigm, multifunctional RIS architectures, ubiquitous satellite integrated sensing and communication, and sustainable satellite Internet-of-Things.

eess.SP

Eco-friendly Power Cost Minimization for Geo-distributed Data Centers Considering Workload Scheduling

The rapid development of renewable energy in the energy Internet is expected to alleviate the increasingly severe power problem in data centers, such as the huge power costs and pollution. This paper focuses on the eco-friendly power cost minimization for geo-distributed data centers supplied by multi-source power, where the geographical scheduling of workload and temporal scheduling of batteries' charging and discharging are both considered. Especially, we innovatively propose the Pollution Index Function to model the pollution of different kinds of power, which can encourage the use of cleaner power and improve power savings. We first formulate the eco-friendly power cost minimization problem as a multi-objective and mixed-integer programming problem, and then simplify it as a single-objective problem with integer constraints. Secondly, we propose a Sequential Convex Programming (SCP) algorithm to find the globally optimal non-integer solution of the simplified problem, which is non-convex, and then propose a low-complexity searching method to seek for the quasi-optimal mixed-integer solution of it. Finally, simulation results reveal that our method can improve the clean energy usage up to 50\%--60\% and achieve power cost savings up to 10\%--30\%, as well as reduce the delay of requests.

cs.NI