Shannon Wireless’ Post

This paper introduces a novel approach to maximize #low #Earth #orbit (#LEO) satellite coverage by leveraging #reconfigurable #intelligent #surface (#RIS) within 6G sub-#terahertz (#THz) networks. Optimization objectives include improving #end-#to-#end (#E2E) data rate, optimizing satellite-#remote #user #equipment (#RUE) associations, data packet routing within satellite constellations, RIS phase shift, and #ground #base #station (#GBS) transmit power (i.e., active beamforming). The formulated joint optimization problem poses significant challenges because of its time-varying environment, non-convex characteristics, and NP-hard complexity. To address these challenges, they propose a #block #coordinate #descent (#BCD) algorithm that integrates balanced K-means clustering, #multi-#agent #proximal #policy #optimization (#MAPPO) #deep #reinforcement #learning (#DRL), and #whale #optimization #algorithm (#WOA) techniques. ---- Sheikh Salman Hassan, Ph.D., Yu Min Park , Yan Kyaw Tun, Walid Saad , Zhu Han , Choong Seon Hong More details can be found at this link: https://lnkd.in/eQmHxryW

SpaceRIS: LEO Satellite Coverage Maximization in 6G Sub-THz Networks by MAPPO DRL and Whale Optimization

SpaceRIS: LEO Satellite Coverage Maximization in 6G Sub-THz Networks by MAPPO DRL and Whale Optimization

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Sheikh Salman Hassan

Research Associate at the University of Edinburgh

5mo

Shannon Wireless Thanks for sharing our work!

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