Adaptive Resource Management Strategy in Practical Multi-Radio Heterogeneous Networks
Mikhail Gerasimenko, Dmitri Moltchanov, Sergey D. Andreev, Yevgeni Koucheryavy, Nageen Himayat, Shu‐ping Yeh, Shilpa Talwar
Abstract
Mikhail Gerasimenko, Dmitri Moltchanov, Sergey D. Andreev, Yevgeni Koucheryavy, Nageen Himayat, Shu‐ping Yeh, Shilpa Talwar
Abstract
The ongoing evolution of mobile wireless communications has resulted in the vision of a multiradio heterogeneous network (HetNet) that comprises cells of different scales controlled by various radio access technologies (RATs). These emerging architectures call for more advanced methods of cross-RAT radio resource allocation, which are the primary focus of this article. In this paper, based on network flow optimization techniques, we adapt the concept of weighted α-fairness for efficient resource management in future HetNets. The corresponding scheme relies on a certain degree of centralized control of the HetNet architecture and allows to achieve the desired balance between the overall system throughput and the fairness of the resulting resource allocations based on a single parameter. Our analytical findings, validated with detailed system-level simulations, are expected to further advance the understanding of feasible resource control strategies in intelligent multi-radio networks, as well as help optimize the performance of next-generation HetNets.
OpenAlex reports 23 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The ongoing evolution of mobile wireless communications has resulted in the vision of a multiradio heterogeneous network (HetNet) that comprises cells of different scales controlled by various radio access technologies (RATs). These emerging architectures call for more advanced methods of cross-RAT radio resource allocation, which are the primary focus of this article. In this paper, based on network flow optimization techniques, we adapt the concept of weighted α-fairness for efficient resource management in future HetNets. The corresponding scheme relies on a certain degree of centralized control of the HetNet architecture and allows to achieve the desired balance between the overall system throughput and the fairness of the resulting resource allocations based on a single parameter. Our analytical findings, validated with detailed system-level simulations, are expected to further advance the understanding of feasible resource control strategies in intelligent multi-radio networks, as well as help optimize the performance of next-generation HetNets.
Key concepts: Heterogeneous network, Computer science, Radio resource management, Resource allocation, Throughput, Resource management (computing), Computer network, Distributed computing