Computationally Aware Sum-Rate Optimal Scheduling for Centralized Radio Access Networks
Peter Rost, Andreas Maeder, Matthew C. Valenti, and Salvatore Talarico

TL;DR
This paper introduces two computationally aware scheduling algorithms for centralized radio access networks that optimize sum-rate performance while managing limited processing resources, evaluated through LTE simulations.
Contribution
It proposes a novel resource scheduling framework that accounts for computational constraints, including an optimal water-filling based scheduler and a simpler heuristic approach.
Findings
Both schedulers prevent computational outages.
Slight sum-rate reduction compared to ideal scheduling.
Effective in LTE system simulations.
Abstract
In a centralized or cloud radio access network, certain portions of the digital baseband processing of a group of several radio access points are executed at a central data center. Centralizing the processing improves the flexibility, scalability, and utilization of computational assets. However, the performance depends critically on how the limited data processing resources are allocated to serve the needs of the different wireless devices. As the processing load imposed by each device depends on its allocated transmission rate and channel quality, the rate-allocation aspect of the scheduling should take into account the available computing. In this paper, two computationally aware schedulers are proposed that have the objective of maximizing the sum-rate of the system while satisfying a constraint on the offered computational load. The first scheduler optimally allocates resources and…
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Taxonomy
TopicsAdvanced Wireless Network Optimization · Advanced MIMO Systems Optimization · Satellite Communication Systems
