Cooperative Radio Resource Management in Heterogeneous Cloud Radio Access Networks

Abstract

Responding to the unprecedented challenges imposed by the 5G communications ecosystem, emerging heterogeneous network architectures allow for improved integration between multiple radio access technologies. When combined with advanced cloud infrastructures, they bring to life a novel paradigm of heterogeneous cloud radio access network (H-CRAN). The novel H-CRAN architecture opens door to improved network-wide management, including coordinated cross-cell radio resource allocation. In this paper, emphasizing the lack of theoretical performance analysis, we specifically address the problem of cooperative radio resource management in H-CRAN by providing a comprehensive mathematical methodology for its realtime performance optimization. Our approach enables flexible balance between throughput and fairness metrics, as may be desired by the network operator, and demonstrates attractive benefits when compared against the state-of-the-art multiradio resource allocation strategies. The resulting algorithms are suitable for efficient online implementation, which principal feasibility is confirmed by our proof-of-concept prototype.INDEX TERMS Heterogeneous network, cloud infrastructure, heterogeneous cloud radio access network, cooperative radio resource management, mathematical methodology, prototyping.

Networking Solutions for Integrated Heterogeneous Wireless Ecosystem

“…In this implementation, we force the UE to prefer a single RAN at a time [4]. Such a decision was made mainly due to its practical feasibility, since otherwise said technique would lose to the UE-centric approach by assigning the maximum radio resources to the users with better connectivity conditions, while potentially not allowing the users with worse channel to even attempt the WiFi/small cells.…”

“…This approach enables improved management on the network-wide scale, allowing to implement cross-cell radio resource allocation in a coordinated way. Recent research addressed the gaps in theoretical performance analysis and provided assessment and mathematical methodology for real-time optimization of cooperative radio resource management in H-CRAN [4]. Resulting algorithms allow to balance between throughput and fairness metrics in a flexible way, as well as might align with network operator's development plans.…”

Dynamic Resource Sharing in 5G with LSA: Criteria-Based Management Framework

“…At the same time, radio spectrum has transformed into a critical resource from economic, cultural, and societal perspectives [5,6]. Its scarcity has become a major limiting factor in particular frequency ranges, spanning 100 MHz to 6 GHz, with desired propagation characteristics for a 2 Wireless Communications and Mobile Computing wide range of static spectrum users (e.g., military, radar, TV broadcasting, and medical and event production) [7,8].…”

A Service-Oriented Approach for Radio Resource Management in Virtual RANs

“…A model of RRM is proposed in [15] for 5G wireless infrastructures, which aggregates users' traffic across a Wi-Fi/LTE network, by considering an -fair mechanism in the objective function, including proportional fairness as its special case; however, there is no effort to address the specifications of different services. Another approach for cooperative RRM in 5G heterogeneous cloud RANs is proposed in [16], which considers a modified max-min technique as an alternative to proportional fairness, although still the evaluation of the effect of different service parameters on model performance is neglected.…”