Energy-Spectrum Efficient Content Distribution in Fog-RAN Using Rate-Splitting, Common Message Decoding, and 3D-Resource Matching

Abstract

Multi-objective resource allocations are studied for a multi-level edge-caching enabled fog-radio access network. Notably, joint maximization of the energy-efficiency (EE) and spectrum-efficiency (EE) and interference management for the content distribution phase are investigated. In the envisioned system, the popular contents are cached at both the fog access point (F-AP) and fog user equipments (F-UEs), and the content-requesting devices are grouped into multiple device-clusters based on their locations. Using a rate-splitting with common message decoding based transmission strategy, each device-cluster is simultaneously served by a suitably selected F-UE and the F-AP over the same radio resource blocks. To maximize system EE and SE of the content distribution phase jointly, a multi-objective optimization problem (MOOP) is formulated. By using the-constraint method, the proposed MOOP is converted to an EE-SE trade-off optimization problem. Leveraging iterative function evaluation based power control and generalized 3D-resource matching, a novel algorithm is devised to obtain near-optimal Pareto front for the proposed MOOP. By inspecting solutions over the Pareto optimal front, a suitable operating EE-SE pair and the corresponding resource allocation variables are obtained. A low-complexity algorithm to obtain a suitable EE-SE trade-off is also devised. The conducted simulations confirm that the proposed algorithms achieve substantial improvement of system EE and SE over the baseline schemes.

Rate-Splitting Multiple Access: Fundamentals, Survey, and Future Research Trends

“…• Cloud-radio access networks (C-RAN) [100], [101], [103], [114]- [116], [127], [128], where RS and common message decoding (RS-CMD) was proposed as a direct application of the HK scheme to the broadcast channel, as is detailed in Section III.B6. • Fog-radio access networks (F-RAN) [129], [133].…”

“…23-25). • Higher energy efficiency: Since RSMA is a superset of OMA, SDMA, NOMA, and multicasting, the performance gain of RSMA is not limited to SE, but also extends to EE and their trade-off [81], [122], [133]. RSMA has been shown to outperform existing MA schemes in terms of EE for various applications with a wide range of network loads and user deployments [74], [84], [94], [96], [102], [107], [114], [126], [131].…”

“…Specifically, F-RAN enables edge-caching to prefetch content with high reuse probability from the centralized processor at the remote radio heads or end-users. RSMA in cache-aided C-RAN and F-RAN has been studied in [129], [133], [141], where RSMA based on RS-CMD was shown to achieve significant performance gains over MU-LP and NOMA requiring a much smaller caching size and fronthaul capacity. Therefore, RSMA has great potential to enhance user performance and simplify the transceiver design in cache-aided C-RAN.…”

AI-Driven Energy-Efficient Content Task Offloading in Cloud-Edge-End Cooperation Networks

“…Li et al [11] formulated the energy minimization issue as a two-stage stochastic mixed integer programming model, and discussed the performance under uncertain content requests. Hassan et al [12] improved energy and spectral efficiency in multiaccess edge computing (MEC)-assisted wireless scenarios by optimizing heterogeneous network resource allocation. Xu et al [13] proposed an optimal energy saving model in green city systems, which chose the candidate content placement positions to improve content distribution and energy efficiency.…”