Combinatorial Auction-Based Pricing for Multi-tenant Autonomous Vehicle Public Transportation System

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Matching theory as enabler of efficient spectrum management in 5G networks

This is the peer reviewed version of the following article: Tsirakis, C, Lopez‐Aguilera, E, Agapiou, G, Varoutas, D. Matching theory as enabler of efficient spectrum management in 5G networks. Trans Emerging Tel Tech. 2020; 31:e3769., which has been published in final form at https://doi.org/10.1002/ett.3769. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.This paper analyzes the spectrum trading problem in virtualized fifth generation (5G) networks in order to enhance the network performance with respect to the spectrum utilization. The problem is modeled as a Many-to-Many Matching (M2MM) game with utility-based preferences and determines the matching between mobile network operators and mobile virtual network operators. The two proposed versions of utility functions for each set aim at maximizing the satisfaction of both sets with conflicting interests and improving the overall spectrum efficiency. In the simulation evaluation, the proposed scheme is compared with three different schemes in terms of the system utility, individual and pair matching satisfaction. We also investigate the scalability aspects, the strategy plan impact on the matching performance of our proposed scheme, and, at the same time, we attempt to make appropriate assumptions closer to reality. Our proposed scheme shows much better performance than the other schemes achieving a quite high level of satisfaction for the matching result on both sets.Postprint (author's final draft

Auction based spectrum trading for cognitive radio networks

Due to copyright restrictions, the access to the full text of this article is only available via subscription.In this letter, we consider the shared used model in cognitive radio networks and design a spectrum trading method to maximize the total satisfaction of the Secondary Users (SUs) and revenue of the Wireless Service Provider (WSP). In our design, we consider the risk of imperfect spectrum sensing which causes the SUs miss the presence of licensed users and interfere with them. Taking into account this risk, we first propose a multi-unit sequential sealed-bid first-price auction to optimize the payoff of each SU. Then, we derive an expression for the total revenue of WSP and maximize it by optimizing the sensing time. Our results demonstrate that the proposed auction-based spectrum trading method brings better revenue than its counterparts.TUB