Conference proceeding
Predictive Optimal Channel Allocation in Integrated Sensing, Communication and Computation Systems
International Symposium on Networks, Computers and Communications, pp 1-6
22 Oct 2024
Abstract
The growing demand for new applications, like digital twins, Extended reality(XR), autonomous vehicles, smart environments, and other Internet of Things(IoT) has set the stage for wireless evolution towards 6G. In 6G wireless sensing, communication and computation are expected to be imbued in a ubiquitous manner. However, optimizing resource allocation in such an integrated sensing, communication, and computation (ISCC) raises critical challenges. In this paper, we focus on the efficient and optimal distribution of orthogonal, homogeneous, subcarriers among these computation, communication, and sensing domains. We propose a novel bi-level multi-objective optimization approach to maximize communication throughput, sensing coverage, and data offloaded from user equipment (UE) to the base station (BS) for computation, resulting in a Pareto efficient front for channel allocations. A 2-stage future Pareto front estimation framework is introduced where the exogeneous parameters are forecasted using using a) Long Short Term Memory (LSTM) or b) Convolutional Neural Network (CNN) model. Then, Non-dominated sorting genetic algorithm II (NSGA-II) is used to estimate the Pareto front for each time step within a prediction window. The framework's performance is evaluated by using a comparison of the generational distance (GD) between the estimated Pareto front from the predicted parameters to the Pareto front generated by the true parameters. Simulation results point out that compared to baseline, LSTM and CNN-based frameworks respectively reduce the GD by 47% and 84% in objective space and 56% and 65% in decision space.
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Details
- Title
- Predictive Optimal Channel Allocation in Integrated Sensing, Communication and Computation Systems
- Creators
- Abhinanda Dutta - Drexel UniversityAbhishek RoyNavrati Saxena - San Jose State UniversitySteven Weber - Drexel University
- Publication Details
- International Symposium on Networks, Computers and Communications, pp 1-6
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Scopus ID
- 2-s2.0-85212178112
- Other Identifier
- 991021985102004721