Deep Reinforcement Learning for Energy Efficiency Maximization in RSMA-IRS-Assisted ISAC System
Shaoyang University · Nanyang Technological University · +3 more institutions
Abstract
The combination of rate splitting multiple access (RSMA) and integrated sensing and communication (ISAC) has recently played a constructive role in various emerging applications associated with sixth-generation networks. However, in complex urban environments, the network performance may be severely restricted by transmission blockages. With the help of intelligent reflecting surfaces (IRS), this paper leverages a virtual line-of-sight link to guarantee the qualityof-service (QoS). First, a three-dimensional (3D) geometry-based stochastic channel model (GBSM) is developed to characterize the IRS-empowered ISAC networks with RSMA. Based on the proposed channel model, we formulate an energy efficiency (EE)…
Citation impact
- FWCI
- 69.22
- Percentile
- 100%
- References
- 21
Authors
7Topics & keywords
- Reinforcement learning
- Maximization
- Computer science
- Efficient energy use
- Artificial intelligence
- Electrical engineering
- Mathematical optimization
- Engineering
- Affordable and clean energy