Game Theoretic Infrastructure Sharing in Wireless Cellular Networks

2015 ◽  
pp. 368-398
Author(s):  
Alexandra Bousia ◽  
Elli Kartsakli ◽  
Angelos Antonopoulos ◽  
Luis Alonso ◽  
Christos Verikoukis
Keyword(s):  
Energy Consumption ◽  
Cellular Networks ◽  
Cost Savings ◽  
Mobile Network ◽  
Cost Effective ◽  
Base Stations ◽  
Traffic Demand ◽  
Game Theoretic ◽  
Mobile Network Operators ◽  
Low Traffic

The emerging traffic demand has fueled the rapid densification of cellular networks. The increased number of Base Stations (BSs) leads to augmented energy consumption and expenditures for the Mobile Network Operators (MNOs), especially during low traffic, when many of the BSs remain underutilized. Hence, the MNOs are encouraged to provide “green” and cost effective solutions for their networks. In this chapter, an innovative algorithm for infrastructure sharing in two-operator environments is proposed, based on BSs switching off during low traffic periods. Motivated by the conflicting interests of the operators, the problem is formulated in a game theoretic framework that enables the MNOs to act individually to estimate the switching off probabilities that reduce their financial cost. The authors analytically and experimentally estimate the potential energy and cost savings that can be accomplished. The obtained results show a significant reduction in both energy consumption and expenditures, thus giving the operators the necessary incentives for infrastructure sharing.

scholarly journals Optimum Sizing of Photovoltaic and Energy Storage Systems for Powering Green Base Stations in Cellular Networks

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1895
Author(s):  
Mahshid Javidsharifi ◽  
Hamoun Pourroshanfekr ◽  
Tamas Kerekes ◽  
Dezso Sera ◽  
Sergiu Spataru ◽  
...  
Keyword(s):  
Cellular Networks ◽  
Renewable Energy Sources ◽  
Cost Effective ◽  
Point Of View ◽  
Base Stations ◽  
Optimal Method ◽  
Battery System ◽  
Traffic Demand ◽  
Effective Manner ◽  
Battery Capacity

Satisfying the mobile traffic demand in next generation cellular networks increases the cost of energy supply. Renewable energy sources are a promising solution to power base stations in a self-sufficient and cost-effective manner. This paper presents an optimal method for designing a photovoltaic (PV)-battery system to supply base stations in cellular networks. A systematic approach is proposed for determining the power rating of the photovoltaic generator and battery capacity from a technical and economical point of view in order to minimize investment cost as well as operational expenditure, while the power autonomy of the PV-battery system is maximized in a multi-objective optimization framework. The proposed method is applied to optimally size a photovoltaic-battery system for three cases with different availability of solar power to investigate the effect of environmental conditions. Problem-solving using the proposed approach leads to a set of solutions at different costs versus different levels of power autonomy. According to the importance of each criterion and the preference of decision-makers, one of the achieved solutions can be selected for the implementation of the photovoltaic-battery system to supply base stations in cellular networks.

A Game Theoretic Approach to Guarantee Fairness in Cooperation Among Green Mobile Network Operators

2013 ◽  
Vol 9 (3) ◽  
pp. 1-15 ◽  
Author(s):  
Leonardo Militano ◽  
Antonella Molinaro ◽  
Antonio Iera ◽  
Ármin Petkovics
Keyword(s):  
Mobile Networks ◽  
Optimal Algorithm ◽  
Mobile Network ◽  
Base Stations ◽  
Theoretic Approach ◽  
Game Theoretic ◽  
Cellular Mobile ◽  
Mobile Network Operators ◽  
Rational Players ◽  
Game Theoretic Approach

Energy efficiency is one of leading design principles for the current deployment of cellular mobile networks. A first driving reason for this is that half of the operating costs for the network providers comes from the energy spent to power the network, with almost 80% of it being consumed at the base stations. A second reason is related to the high environmental pollution, which makes the green cellular networks deployment mandatory. Cooperation between mobile network providers can be an effective way to reduce the CO2 emissions and, simultaneously, reduce the operating expenditures. In this paper, a game theoretic approach is proposed to introduce fairness and stability into an optimal algorithm for switching off the cooperating base stations. This aims at making such a solution more attractive in real implementation scenarios where profit-driven network providers act as rational players.

scholarly journals Adaptive offloading in mobile-edge computing for ultra-dense cellular networks based on genetic algorithm

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Zhuofan Liao ◽  
Jingsheng Peng ◽  
Bing Xiong ◽  
Jiawei Huang
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Cellular Networks ◽  
Physical Distance ◽  
Edge Computing ◽  
Base Stations ◽  
Mobile Edge Computing ◽  
Total Energy Consumption ◽  
Average Delay ◽  
Server Selection

AbstractWith the combination of Mobile Edge Computing (MEC) and the next generation cellular networks, computation requests from end devices can be offloaded promptly and accurately by edge servers equipped on Base Stations (BSs). However, due to the densified heterogeneous deployment of BSs, the end device may be covered by more than one BS, which brings new challenges for offloading decision, that is whether and where to offload computing tasks for low latency and energy cost. This paper formulates a multi-user-to-multi-servers (MUMS) edge computing problem in ultra-dense cellular networks. The MUMS problem is divided and conquered by two phases, which are server selection and offloading decision. For the server selection phases, mobile users are grouped to one BS considering both physical distance and workload. After the grouping, the original problem is divided into parallel multi-user-to-one-server offloading decision subproblems. To get fast and near-optimal solutions for these subproblems, a distributed offloading strategy based on a binary-coded genetic algorithm is designed to get an adaptive offloading decision. Convergence analysis of the genetic algorithm is given and extensive simulations show that the proposed strategy significantly reduces the average latency and energy consumption of mobile devices. Compared with the state-of-the-art offloading researches, our strategy reduces the average delay by 56% and total energy consumption by 14% in the ultra-dense cellular networks.

Stackelberg Game Theoretic Framework in Cognitive Green Heterogeneous Networks

2017 ◽  
pp. 269-286
Author(s):  
Chungang Yang ◽  
Pengyu Huang ◽  
Jia Xiao ◽  
Lingxia Wang ◽  
Jiandong Li
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Cognitive Radio ◽  
Cellular Networks ◽  
Communication Networks ◽  
Cognitive Radio Networks ◽  
Stackelberg Game ◽  
Radio Networks ◽  
Heterogeneous Cellular Networks ◽  
Game Theoretic

Game theory has found an extensive application in wireless communication networks including cognitive radio networks, heterogeneous cellular networks, cooperative relay networks. Also, cognitive radio networks, green communications and heterogeneous cellular networks have attracted a wide attention on improve the spectrum efficiency and energy efficiency; therefore, the capacity, the coverage and the energy consumption. However, interference problem and energy consumption are critical for these networks. Introducing hierarchy among different decision-making players in cognitive, heterogeneous, green, cooperative cellular networks can both save energy and mitigate interference, thus enhance throughput. Stackelberg game suits to model, analyze and design the distributed algorithms in these hierarchical decision-making networking scenarios. In this chapter, we introduce basics of Stackelberg game and survey the extensive applications of Stackelberg game in cognitive, heterogeneous, cooperative cellular networks with the emphasis on resource management, green commutations design and interference management. This chapter highlights the potentials and applications with the promising vision of Stackelberg game theoretic framework for future cognitive green heterogeneous cellular networks.

scholarly journals Collaborative Resource Management for Negotiable Multi-Operator Small Cell Networks

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3550 ◽  
Author(s):  
Shashi Shah ◽  
Somsak Kittipiyakul ◽  
Yuto Lim ◽  
Yasuo Tan
Keyword(s):  
Performance Metrics ◽  
Mobile Network ◽  
Base Stations ◽  
Small Cells ◽  
Network Resources ◽  
Small Cell Networks ◽  
User Data ◽  
Mobile Network Operators ◽  
Cell Networks ◽  
Mutual Agreement

The ubiquitous coverage/connectivity requirement of wireless cellular networks has shifted mobile network operators’ (MNOs) interest toward dense deployment of small cells with coverage areas that are much smaller as compared to macrocell base stations (MBSs). Multi-operator small cells could provide virtualization of network resources (infrastructure and spectrum) and enable its efficient utilization, i.e., uninterrupted coverage and connectivity to subscribers, and an opportunity to avoid under-utilization of the network resources. However, a MNO with exclusive ownership to network resources would have little incentive to utilize its precious resources to serve users of other MNOs, since MNOs differentiate among others based on their ownership of the licensed spectrum. Thus, considering network resources scarcity and under-utilization, this paper proposes a mechanism for multi-operator small cells collaboration through negotiation that establishes a mutual agreement acceptable to all involved parties, i.e., a win–win situation for the collaborating MNOs. It enables subscribers of a MNO to utilize other MNOs’ network resources, and allows MNOs to offer small cells “as a service” to users with ubiquitous access to wireless coverage/connectivity, maximize the use of an existing network resources by serving additional users from a market share, and enhance per-user data rate. We validated and evaluated the proposed mechanism through simulations considering various performance metrics.

scholarly journals Energy Efficient Caching in Backhaul-Aware Cellular Networks with Dynamic Content Popularity

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Jiequ Ji ◽  
Kun Zhu ◽  
Ran Wang ◽  
Bing Chen ◽  
Chen Dai
Keyword(s):  
Energy Efficiency ◽  
Cellular Networks ◽  
Energy Efficient ◽  
Base Stations ◽  
Noise Model ◽  
Traffic Demand ◽  
Hit Rate ◽  
Dynamic Content ◽  
Content Popularity ◽  
Cache Capacity

Caching popular contents at base stations (BSs) has been regarded as an effective approach to alleviate the backhaul load and to improve the quality of service. To meet the explosive data traffic demand and to save energy consumption, energy efficiency (EE) has become an extremely important performance index for the 5th generation (5G) cellular networks. In general, there are two ways for improving the EE for caching, that is, improving the cache-hit rate and optimizing the cache size. In this work, we investigate the energy efficient caching problem in backhaul-aware cellular networks jointly considering these two approaches. Note that most existing works are based on the assumption that the content catalog and popularity are static. However, in practice, content popularity is dynamic. To timely estimate the dynamic content popularity, we propose a method based on shot noise model (SNM). Then we propose a distributed caching policy to improve the cache-hit rate in such a dynamic environment. Furthermore, we analyze the tradeoff between energy efficiency and cache capacity for which an optimization is formulated. We prove its convexity and derive a closed-form optimal cache capacity for maximizing the EE. Simulation results validate the proposed scheme and show that EE can be improved with appropriate choice of cache capacity.

scholarly journals Independence and Fairness Analysis of 5G mmWave Operators Utilizing Spectrum Sharing Approach

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Mothana L. Attiah ◽  
A. A. M. Isa ◽  
Zahriladha Zakaria ◽  
M. K. Abdulhameed ◽  
Mowafak K. Mohsen ◽  
...  
Keyword(s):  
Spectrum Sharing ◽  
Mobile Network ◽  
Analytical Framework ◽  
Base Stations ◽  
Spectrum Utilization ◽  
Selection Scheme ◽  
Research Activities ◽  
Cost Efficient ◽  
Network Functionality ◽  
Mobile Network Operators

The spectrum sharing approach (SSA) has emerged as a cost-efficient solution for the enhancement of spectrum utilization to meet the stringent requirements of 5G systems. However, the realization of SSA in 5G mmWave cellular networks from technical and regulatory perspectives could be challenging. Therefore, in this paper, an analytical framework involving a flexible hybrid mmWave SSA is presented to assess the effectiveness of SSA and investigate its influence on network functionality in terms of independence and fairness among operators. Two mmWave frequencies (28 GHz and 73 GHz) are used with different spectrum bandwidths. Various access models have been presented for adoption by four independent mobile network operators that incorporate three types of spectrum allocation (exclusive, semipooled, and fully pooled access). Furthermore, an adaptive multi-state mmWave cell selection scheme is proposed to associate typical users with the tagged mmWave base stations that provide a great signal-to-interference plus noise ratio, thereby maintaining reliable connections and enriching user experience. Numerical results show that the proposed strategy achieves considerable improvement in terms of fairness and independence among operators, which paves the way for further research activities that would provide better insight and encourage mobile network operators to rely on SSA.

scholarly journals Characterizing Multi-radio Energy Consumption in Cellular/Wi-Fi Smartphones

2016 ◽  
Vol 6 (6) ◽  
pp. 2920
Author(s):  
Zuhaibuddin Bhutto ◽  
Jun-Hyuk Park ◽  
Wonyong Yoon
Keyword(s):  
Energy Consumption ◽  
Cellular Networks ◽  
Measured Data ◽  
Bandwidth Aggregation ◽  
Data Set ◽  
Traffic Demand ◽  
Consumption Behavior ◽  
Energy Consumption Model ◽  
Consumption Model ◽  
Commercial Network

<p>Cellular networks evolved to meet the ever increasing traffic demand by way of offloading mobile traffic to Wi-Fi network elements. Exploiting multi-radio interfaces on a smartphone has recently been examined with regards to heterogeneous bandwidth aggregation and radio switching. However, how a smartphone consumes its energy in driving cellular and Wi-Fi multi-radio interfaces, is not well understood. In this paper, we revealed the energy consumption behavior of 3G cellular and Wi-Fi multi-radio operations of a smartphone. We modified smartphone’s firmware to enable multi-radios operations simultaneously and we performed extensive measurements of multi-radio energy consumption in a real commercial network. From the measured data set, we established a realistic multi-radio energy consumption model and it gave 98% stability from the derived coefficients.</p>

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