Preference-Based Spectrum Pricing in Dynamic Spectrum Access Networks

Wireless Communications and Mobile Computing

et al. 2020

Network performance is of great importance for processing Internet of Things (IoT) applications in the fifth-generation (5G) communication system. With the increasing number of the devices, how network services should be provided with better performances is becoming a pressing issue. The static resource allocation of wireless networks is becoming a bottleneck for the emerging IoT applications. As a potential solution, network virtualization is considered a promising approach to enhancing the network performance and solving the bottleneck issue. In this paper, the problem of wireless network virtualization is investigated where one wireless infrastructure provider (WIP), mobile virtual network operators (MVNOs), and IoT devices coexist. In the system model under consideration, with the help of a software-defined network (SDN) controller, the WIP can divide and reconfigure its radio frequency bands to radio frequency slices. Then, two MVNOs, MVNO1 and MVNO2, can lease these frequency slices from the WIP and then provide IoT network services to IoT users under competition. We apply a two-stage Stackelberg game to investigate and analyze the relationship between the two MVNOs and IoT users, where MVNO1 and MVNO2 firstly try to maximize their profits by setting the optimal network service prices. Then, IoT users make decisions on which network service they should select according to the performances and prices of network services. Two competition cases between MVNO1 and MVNO2 are considered, namely, Stackelberg game (SG) where MVNO1 is the leader whose price of network service is set firstly and MVNO2 is the follower whose network service price is set later and noncooperative strategic game (NSG) under which the service prices of MVNO1 and MVNO2 are simultaneously set. Each IoT user decides whether and which MVNO to select on the basis of the network service prices and qualities. The numerical results are provided to show the effectiveness of our game model and the proposed solution method.

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Competition of Duopoly MVNOs for IoT Applications through Wireless Network Virtualization

Zhang¹,

Li²,

Wireless Communications and Mobile Computing

et al. 2020

“…<θN. The system model that we use is mainly inspired by [8] and [11] but with different pricing schemes.…”

Section: Sus' Modelmentioning

confidence: 99%

Optimal Pricing for Spectrum Allocation in Cognitive Radio Networks

Gu¹,

Li²,

et al. 2018

MATEC Web Conf.

In this paper, we investigate the problem of spectrum allocation in Cognitive Radio Networks (CRNs) where a primary user (PU) leases its idle spectrums to a number of secondary users (SUs) who may have different willing to pay for these spectrums. For the PU, its main objective is to gain profit from selling the idle spectrums, and from the perspective of the Sus, they aim to maximize their utility from using spectrums. We model the interaction between the PU and SUs as a two-stage Stackelberg game, where the PU sets the prices for its spectrum in the first stage, and SUs make their spectrum demands decisions in the second stage. We use the backward induction method to solve this game. The numerical results show that the proposed solution method can increase revenue of the PU compared with the uniform pricing scheme.

“…In this section, we introduce the system model where one secondary operator, denoted by MVNO, lease spectrum from spectrum owner and provide network service to a number of SUs, as illustrated in Fig.2. The system model that we use is mainly inspired by the works of Li [8] and Zhao [16] but with different objective functions. As the radio spectrum allocated to spectrum holder remains largely unused even in densely populated urban areas [1], the unused spectrum can form a spectrum pool where the total available bands are divided into a lot of unit channels.…”

Section: System Modelmentioning

confidence: 99%

“…We assume that the channels with quality q are leased to MVNO. The channel quality q can be expressed as [8]…”

Section: System Modelmentioning

confidence: 99%

Optimal Pricing for Service Provisioning in the Secondary Spectrum Market

Gu¹,

Li²,

et al. 2018

MATEC Web Conf.

In this paper, we investigate the problem of spectrum sharing in a secondary spectrum market where one secondary operator provisions network access services to a number of secondary users (SUs) by leasing spectrum from spectrum holder. For the system model under consideration, the spectrum allocated to the secondary operator can be shared by SUs. We model the interaction between the secondary operator and SUs as a two-stage Stackelberg game, where the secondary operator network price decisions in the first stage, and SUs make their spectrum demands decisions in the second stage. We use the backward induction method to solve this game. The numerical results show that the proposed solution method can capture the main factors of the secondary spectrum market, and provide a promising framework for the design of future secondary CR systems.