Cournot Equilibrium in an Owner-Renter Model for 5G Networks under Flat-Rate Pricing

Flamini, Marta; Naldi, Maurizio

doi:10.1109/tsp49548.2020.9163457

Cited by 3 publications

(3 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The game's equilibrium is established by calculating the first-order derivative of the profit function in relation to price. Two great examples of utilizing Cournot games are found in [31] and [32]. In [31], the researchers employ a Cournot game model to maximize Mobile Network Operator (MNO) revenues by strategically determining prices and allocating bandwidth resources.…”

Section: Bertrand Games and Cournot Oligopolymentioning

confidence: 99%

“…Two great examples of utilizing Cournot games are found in [31] and [32]. In [31], the researchers employ a Cournot game model to maximize Mobile Network Operator (MNO) revenues by strategically determining prices and allocating bandwidth resources. The equilibrium study demonstrates that the most effective pricing approach entails a combination of customer willingness to pay and operational costs, highlighting the need for a careful equilibrium to sustain profitability in a competitive market.…”

Section: Bertrand Games and Cournot Oligopolymentioning

confidence: 99%

See 1 more Smart Citation

A Reinforcement Learning-Based Reverse Auction Enforcing Smart Pricing Policies towards B5G Offloading Strategies

Kaltakis,

Dimos,

Giannoulakis

et al. 2024

Electronics

View full text Add to dashboard Cite

In this paper, we present our work on developing a Smart Pricing Policies module specifically designed for individual users and Mobile Network Operators (MNOs). Our framework will operate in a multi-MNO blockchain radio access network (B-RAN) and is tasked with determining prices for resource sharing among users and MNOs. Our sophisticated adaptive pricing system can adjust to situations where User Equipment (UE) shifts out of the coverage area of their MNO by immediately sealing a contract with a different MNO to cover the users’ needs. This way, we aim to provide financial incentives to MNOs while ensuring continuous network optimization for all parties involved. Our system accomplishes that by utilizing deep reinforcement learning (DLR) to implement a reverse auction model. In our reinforcement learning scenario, the MNOs, acting as agents, enter a competition and try to bid the most appealing price based on the user’s request, and based on the reward system, agents that do not win in the current round will adjust their strategies in an attempt to secure a win in subsequent rounds. The findings indicated that combining DRL with reverse auction theory offers a more appropriate method for addressing the pricing and bid challenges, and additionally, administrators can utilize this strategy to gain a notable edge by dynamically selecting and adjusting their methods according to the individual network conditions and requirements.

show abstract

Section: Bertrand Games and Cournot Oligopolymentioning

confidence: 99%

Section: Bertrand Games and Cournot Oligopolymentioning

confidence: 99%

A Reinforcement Learning-Based Reverse Auction Enforcing Smart Pricing Policies towards B5G Offloading Strategies

Kaltakis,

Dimos,

Giannoulakis

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

“…The control object of this paper is an amorphous flattened air-to-ground wireless ad hoc network system (Wang et al , 2020b), where amorphous (Zhang et al , 2020c; Nykyruy et al , 2020) means that the ad hoc network node topology can change the corresponding topology according to the needs of the scenario (Yan, 2020), flattened (Penkin et al , 2020; Flamini and Naldi, 2020) means that the originally complex hierarchical architecture is highly integrated to form a relatively simple structure, and the air-to-ground ad hoc network refers to the introduction of quadrotor unarmed aerial vehicles (Kuo et al , 2021; Chiu et al , 2020; Ali et al , 2019) as aerial compensation nodes to play the role of signal transmission to fill the blindness (Zhao et al , 2009). The control goal is to make the wireless signal transmission more stable and to improve the stability of the ad hoc network topology, so various kinds of interference and faults that may be encountered need to be considered when designing the matching controller.…”

Section: Introductionmentioning

confidence: 99%

Research on robust adaptive sliding film fault-tolerant control under nonlinear distortion of signal transmission in amorphous flat air-to-ground wireless ad-hoc network system

Wang

Lin

2022

View full text Add to dashboard Cite

Purpose To solve the above problems and ensure the stability of the ad hoc network node topology in the process of wireless signal transmission, this paper aims to design a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system. Design/methodology/approach This paper designs a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system. Findings The simulation results show that the amorphous flat wireless self-organizing network system has good nonlinear distortion fault-tolerant correction ability under the feedback control of the designed controller, and the system has the asymptotically stable convergence ability; the test results show: the node topology of the self-organizing network structural stability is significantly improved, which provides a foundation for the subsequent realization of long-distance transmission of ad hoc network nodes. Research limitations/implications Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further. Originality/value The controller can extract the fault information caused by nonlinear distortion in the wireless signal transmission process, and at the same time, its feedback matrix K can gradually converge the generated wireless signal error to zero, to realize the stable transmission of the wireless signal.

show abstract

Optimal Pricing in a Rented 5G Infrastructure Scenario with Sticky Customers

Flamini

Naldi

2023

Future Internet

View full text Add to dashboard Cite

The ongoing deployment of 5G is accompanied by architecture and pricing decisions. Network sharing is a critical feature, allowing operators to reduce their costs, but introducing a mixed partnering/competition situation, where the infrastructure owner, renting out their infrastructure to virtual operators (who act as customers), also provides services to end customers, competing with virtual operators. Pricing is the leverage through which an optimal balance between the two roles is accomplished. However, pricing may not be the only variable affecting customers’ choice, which may prefer (stick to) one operator for several reasons. In this paper, we formulate a game model to analyse the optimal pricing decisions for operators in the presence of such sticky behaviour of customers. After concluding that the game does not allow for a Nash equilibrium, we consider a case when one of the parties (the infrastructure owner, the virtual operators, or the regulator) is responsible for setting prices and analyse how operators’ profits are impacted when price-setting powers are shifted among the parties. The scenario where the regulator sets prices leads to the lowest profits for the operators, even lower than when competitors set prices.

show abstract

Cournot Equilibrium in an Owner-Renter Model for 5G Networks under Flat-Rate Pricing

Cited by 3 publications

References 20 publications

A Reinforcement Learning-Based Reverse Auction Enforcing Smart Pricing Policies towards B5G Offloading Strategies

A Reinforcement Learning-Based Reverse Auction Enforcing Smart Pricing Policies towards B5G Offloading Strategies

Research on robust adaptive sliding film fault-tolerant control under nonlinear distortion of signal transmission in amorphous flat air-to-ground wireless ad-hoc network system

Optimal Pricing in a Rented 5G Infrastructure Scenario with Sticky Customers

Contact Info

Product

Resources

About