Business models for deployment and operation of femtocell networks; - Are new cooperation strategies needed for mobile operators?

In this paper we discuss different business models for deployment and operation of femtocell networks intended for provisioning of public mobile broad band access services. In these types of business cases the operators use femtocells in order to reduce investments in "more costly" macro networks since the traffic can be "offloaded" to "less costly" femtocell networks. This is in contrast to the many business cases presented in Femtoforum where femtocells mainly are discussed as a solution to improve indoor coverage for voice services in homes and small offices, usually for closed user groups The main question discussed in this paper is if "operators need to consider new forms of cooperation strategies in order to enable large scale deployment of femtocells for public access?" By looking into existing solutions for indoor wireless access services we claim that the answer is both "Yes" and "No". No, since many types of cooperation are already in place for indoor deployment. Yes, because mobile operators need to re-think the femtocell specific business models, from approaches based on singe operator networks to different forms of cooperation involving multi-operator solutions, e.g. roaming and network sharing. --

5G Ultra-dense networks with non-uniform Distributed Users

User distribution in ultra-dense networks (UDNs) plays a crucial role in affecting the performance of UDNs due to the essential coupling between the traffic and the service provided by the networks. Existing studies are mostly based on the assumption that users are uniformly distributed in space. The non-uniform user distribution has not been widely considered despite that it is much closer to the real scenario. In this paper, Radiation and Absorbing model (R&A model) is first adopted to analyze the impact of the non-uniformly distributed users on the performance of 5G UDNs. Based on the R&A model and queueing network theory, the stationary user density in each hot area is investigated. Furthermore, the coverage probability, network throughput and energy efficiency are derived based on the proposed theoretical model. Compared with the uniformly distributed assumption, it is shown that non-uniform user distribution has a significant impact on the performance of UDNs.Comment: 14 pages, 10 figure

WiFi Hot Spot Service Business for the Automotive and Oil Industries: A Competitive Analysis

While you refuel for gas, why not refuel for information or upload vehicle data, using a cheap wireless technology as WiFi? This paper analyzes in extensive detail the user segmentation by vehicle usage, service offering, and full business models from WiFi hot spot services delivered to and from vehicles (private, professional, public) around gas stations. Are also analyzed the parties which play a role in such services: authorization, provisioning and delivery, with all the dependencies modelled by attributed digraphs. Account is made of WiFi base station technical capabilities and costs. Five year financial models (CAPEX, OPEX), and data pertain to two possible service suppliers: multi-service oil companies, and mobile service operators (or MVNOs). Model optimization on the return-on-investment (R.O.I.) is carried out for different deployment scenarios, geographical coverage assumptions, as well as tariff structures. Comparison is also being made with public GPRS and 3G data services, as precursors to HSPA/LTE, and the effect of WiFi roaming is analyzed. Regulatory implications, including those dealing with public safety, are addressed. Analysis shows that due to manpower costs and marketing costs, suitable R.O.I. will not be achieved unless externalities are accounted for and innovative tariff structures are introduced. Open issues and further research are outlined. Further work is currently carried out with automotive electronics sector, wireless systems providers, wireless terminals platform suppliers, and vehicle manufacturers. Future relevance of this work is also discussed for the emerging electrical reloading grids for electrical vehicles.WiFi, Fuel Stations, Business Models, Oil Company, Mobile Operator, WiFi Services, Regulations, Professional Vehicles

WLAN Hot Spot services for the automotive and oil industries :a business analysis Or : "Refuel the car with petrol and information, both ways at the gas station"

While you refuel for gas ,why not refuel for information or download vehicle data ? This paper analyzes in extensive detail the user segmentation by vehicle usage , service offering , and full business models from WLAN hot spot services delivered to vehicles (private, professional , public) around gas stations . Are also analyzed the parties which play a role in such service authorization, provisioning and delivery , with all the dependencies modelled by attributed digraphs . Sevice planning is included as to WLAN base station capabilities . Five year financial models (CAPEX,OPEX) , and data pertain to two possible service suppliers : multi-service oil companies, and mobile service operators (or MVNO) . Model optimization on the return-on-investment (ROI) is carried out for different deployment scenarios ,geographical coverage assumptions, as well as tariff structures . Comparison is also being made with public GPRS data services ,as precursors for 3G services,and the effect of WLAN roaming is analyzed .Analysis shows that due to manpower costs and marketing costs , suitable ROI will not be achieved unless externalities are accounted for and innovative tariff structures are introduced . Open issues and further research are outlined . Further work is carried out,also with automotive electronics sector , wireless systems providers , wireless terminals platform suppliers , and vehicle manufacturers .WLAN services;WLAN;business models;fuel stations;mobile operator;oil company;professional vehicles

Distributed drone base station positioning for emergency cellular networks using reinforcement learning

Due to the unpredictability of natural disasters, whenever a catastrophe happens, it is vital that not only emergency rescue teams are prepared, but also that there is a functional communication network infrastructure. Hence, in order to prevent additional losses of human lives, it is crucial that network operators are able to deploy an emergency infrastructure as fast as possible. In this sense, the deployment of an intelligent, mobile, and adaptable network, through the usage of drones—unmanned aerial vehicles—is being considered as one possible alternative for emergency situations. In this paper, an intelligent solution based on reinforcement learning is proposed in order to find the best position of multiple drone small cells (DSCs) in an emergency scenario. The proposed solution’s main goal is to maximize the amount of users covered by the system, while drones are limited by both backhaul and radio access network constraints. Results show that the proposed Q-learning solution largely outperforms all other approaches with respect to all metrics considered. Hence, intelligent DSCs are considered a good alternative in order to enable the rapid and efficient deployment of an emergency communication network

Performance Analysis of Multicast Mobility in a Hierarchical Mobile IP Proxy Environment

Mobility support in IPv6 networks is ready for release as an RFC, stimulating major discussions on improvements to meet real-time communication requirements. Sprawling hot spots of IP-only wireless networks at the same time await voice and videoconferencing as standard mobile Internet services, thereby adding the request for multicast support to real-time mobility. This paper briefly introduces current approaches for seamless multicast extensions to Mobile IPv6. Key issues of multicast mobility are discussed. Both analytically and in simulations comparisons are drawn between handover performance characteristics, dedicating special focus on the M-HMIPv6 approach.Comment: 11 pages, 7 figure