Stable Matching based Resource Allocation for Service Provider's Revenue Maximization in 5G Networks
5G technology is foreseen to have a heterogeneous architecture with the various computational capability, and radio-enabled service providers (SPs) and service requesters (SRs), working altogether in a cellular model. However, the coexistence of heterogeneous network model spawns several research challenges such as diverse SRs with uneven service deadlines, interference management, and revenue maximization of non-uniform computational capacities enabled SPs. Thus, we propose a coexistence of heterogeneous SPs and SRs enabled cellular 5G network and formulate the SPs' revenue maximization via resource allocation, considering different kinds of interference, data rate, and latency altogether as an optimization problem and further propose a distributed many-to-many stable matching-based solution. Moreover, we offer an adaptive stable matching based distributed algorithm to solve the formulated problem in a dynamic network model. Through extensive theoretical and simulation analysis, we have shown the effect of different parameters on the resource allocation objectives and achieves 94 percent of optimum network performance.
A. Pratap and S. K. Das, "Stable Matching based Resource Allocation for Service Provider's Revenue Maximization in 5G Networks," IEEE Transactions on Mobile Computing, vol. 21, no. 11, pp. 4094 - 4110, Institute of Electrical and Electronics Engineers, Nov 2022.
The definitive version is available at https://doi.org/10.1109/TMC.2021.3064047
Keywords and Phrases
5G; IoT; Service provider; service requester; smart healthcare; stable matching
International Standard Serial Number (ISSN)
Article - Journal
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01 Nov 2022
National Science Foundation, Grant CCF-1725755