Bargaining-Based Mobile Data Offloading

Mobile data offloading is a promising approach to alleviate network congestion and enhance quality of service (QoS) in mobile cellular networks. In this paper, we investigate the economics of mobile data offloading through third-party WiFi or femtocell access points (APs). Specifically, we consider a market-based data offloading solution, where macrocellular base stations (BSs) pay APs for offloading traffic. The key questions arising in such a marketplace are following: (i) how much traffic should each AP offload for each BS? and (ii) what is the corresponding payment of each BS to each AP? We answer these questions by using the non-cooperative game theory. In particular, we define a multi-leader multi-follower data offloading game (DOFF), where BSs (leaders) propose market prices, and accordingly APs (followers) determine the traffic volumes they are willing to offload. We characterize the subgame perfect equilibrium (SPE) of this game, and further compare the SPE with two other classic market outcomes: (i) the market balance (MB) in a perfect competition market (i.e., without price participation), and (ii) the monopoly outcome (MO) in a monopoly market (i.e., without price competition). Our results analytically show that (i) the price participation (of BSs) will drive market prices down, compared to those under the MB outcome, and (ii) the price competition (among BSs) will drive market prices up, compared to those under the MO outcome.

The unforeseen mobile data explosion poses a major challenge to the performance of today's cellular networks, and is in urgent need of novel solutions to handle such voluminous mobile data. Obviously, data offloading through third-party WiFi access points (APs) can effectively alleviate the data load in the cellular networks with a low operational and capital expenditure. In this paper, we propose and analyze an attractor-aware offloading ratio selection (AORS) algorithm, which can adaptive select an optimum offloading ratio based on attractor selection for the current networks environment. In the proposed algorithm, the throughput of AP and the cellular load corresponding to the coverage area of the AP, are mapped into the cell activity, which is the reflector of the current network environment. When the current attractor activity is low, the network is dominated by the noise. Then, the noise triggers the controller to select adaptive attractor for each users, the optimal offloading ratio $$\phi $$?, to adapt to the dynamic network environment. Hence, according to the offloading ratio $$\phi $$?, the part of the cellular traffic will be transmitted via WiFi networks. Through simulation, we show that the proposed AORS algorithm outperforms the existing ones with 42 % higher heterogeneous network throughput in a dense traffic environment.

This chapter considers the challenges faced by network operators and service providers accommodating the increasing traffic demands in cellular networks in the most efficient yet inexpensive way. It proposes that these challenges are addressed by offloading part of the traffic to femto cell access points (FAPs) and WiFi access points (WiFiAPs). Whereas 4G micro and pico cell base stations are assumed to be managed by the network operator in terms of setup and maintenance, FAPs and WiFiAPs are normally bought and operated by the end-user. The main difference between these two solutions is that the FAPs operate on the frequency bands assigned to the network operator by national regulators, while WiFiAPs work on unlicensed spectrum. This chapter analyzes the pros and cons of such approaches, and the tradeoffs related to the different mechanisms employed in cellular and WiFi networks for interference management. Moreover, various methods for traffic offloading by the mobile network operator are discussed in detail, including local IP access (LIPA), selective IP traffic offloading (SIPTO), IP flow mobility (IFOM), access network discovery and selection function (ANDSF), and Hotspot 2.0, etc. In the experimental part of this chapter, means for traffic management from the network operator's perspective are discussed, taking into account costs and energy savings. Furthermore, a novel resource usage coordination concept in conjunction with the WiFi offloading concept is presented. Introduction The traffic served by cellular networks grows significantly on a yearly basis, making the efficient, fair, and inexpensive management of users’ traffic demands a real challenge. Various forecasts provided both by legal bodies and commercial companies show that this trend will not change in the future. One can, for example, consider the expectations provided in Table 6.1, created based on the data delivered in the Cisco Visual Networking Index [1, 2] in 2012 and 2013. It is shown that the monthly average traffic generated by mobile devices is foreseen to grow exponentially. Based on [3], it can be stated that in 2017 IP traffic originating from mobile devices will comprise more than 13% of fixed IP traffic, while in 2013 this comprised only around 4% of fixed IP traffic.

Presently, femtocell technology is emerging for cellular wireless networks, which have rapidly engrossed the cellular industry. The main advantage of femtocell to the mobile operators is a reduction of cost and an improvement of the signal quality in indoor coverage, which is also considered a possible path to the Fixed–Mobile Convergence (FMC) goal. Femtocell extends network coverage and delivers high-quality mobile services inside residential and business buildings through broadband networks (i.e. ADSL). Femtocell Access Points (FAP) or Home Base Stations (HBS) are intended to serve small number of users (i.e. 4 users) and cover about 30-square meters, similar to existing WiFi access points. However, femtocell introduces new challenges to the telecom industries in terms of handoff between femto and microcells, interference management, localization, and synchronization. Among all of these challenges, synchronization is considered as the cornerstone for the femtocells to function properly. The problematic issue in femtocell synchronization is that all the data and control traffic travels through an IP broadband network. The IP broadband network is usually owned and managed by a third party and not by the mobile operator which can complicate the synchronization. Unsynchronized FAPs may cause harmful interference and wrong handover dictions. In this chapter, the authors investigate and overview the current femtocell synchronization techniques and make comparisons between them. Possible improvements and recommendations for each method have been identified. Future research areas and open issues are also discussed.

Mobile data offloading through third-party Femtocell access points (FAPs) is an emerging technology which is used to alleviate congestion in cellular network. We propose a distributed algorithm that combines college admissions game with auction theory to achieve the maximum social welfare of offloading and guarantee the Quality of service (QoS) of Mobile users (MUs). As the optimal problem is NP-hard, the college admissions game is developed to solve the sub-problem of matching between FAPs and MUs. The Second revenue sealed-bid auction with a reserve price (SRSARP) algorithm is developed to solve another sub-problem of matching between Wireless operators (WOs) and FAPs. The simulation results reveal that the distributed algorithm we proposed achieves the performance very close to that of the centralized method and significantly better than those of the random and Maxprice algorithms.

The unprecedented growth in cellular traffic forced researchers towards extending the Long Term Evolution (LTE) cellular network to unlicensed bands, which is known as U-LTE. However, this extension is by no means straightforward, because centralized control impeded in traditional LTE BSs challenges the performance and radio resources management of today's cellular networks. To cope with the increasing scarcity of today's cellular architecture and radio resources management, for the first time, we propose Break-Even Point (BEP) as a novel approach for solving the radio resources management problem. In this case, the BEP is modelling where the total remaining throughput of Wi-Fi or Small cell Programmable Base Station (SPBS) equals to the total consuming throughput by Users Equipment (UEs). Therefore, we can identify if Wi-Fi and Femtocell or SPBS are working above or below BEP. By using proposed BEP scheme, we guarantee cellular network utilizations with optimal precision, as well as, performance evaluation indicates that optimal spectrum access and fair distribution by using BEP scheme.

This paper studies distributed formation of femto-clouds in a UMTS LTE network. Femtocell access points (FAPs) are equipped with computational resources. They share their resources with neighboring FAPs and form local clouds with the aim to avoid the remote cloud costs while improving the user quality of experience (QoE) in terms of handling latency. In exchange for sharing their excess resources, FAPs receive monetary incentives proportional to their contribution in performing computational tasks in the femto-cloud. The resource sharing problem is formulated as an optimization problem and a myopic procedure is presented that enables FAPs to collaboratively find its solution in a distributed fashion. In such an optimal femto-cloud structure, the local computational resources of FAPs are maximally exploited, yet the incentive earned by each femto-cloud is divided among the FAPs in a fair fashion. Numerical simulations using NS-3 verify superior QoE of users as well as higher incentives provided to FAP owners as compared with alternative heuristic schemes. Numerical results also show that the grand femto-cloud-the largest collaborative cloud comprising of all FAPs-is not always the optimal structure.

With growing demand for high data rates, the mobile network has faced excessive traffic and it seems that one of the few long‐term solutions to this problem is employing femtocells which improve capacity and indoors coverage. In the typical femtocell networks, co‐ and cross‐layer interferences caused by simultaneous transmission of macrocell base stations and femtocell access points in the same frequency band, results in dead spots especially if femtocells are densely employed. In this study, to mitigate the interference and improve the system's performance, the authors study the application of time‐hopping approach. Particularly, the impact of aggressive signals of femto access points on a macro user equipment located in the second tier, that is, the femtocell coverage area, is analysed and the semi‐closed‐form expression for the system outage probability is derived. Based on the analysis, they also simulate the transmission capacity (TC) that represents the total capacity of the co‐channel two‐tier networks with outage constraints. Next, employing Gaussian approximations, they derive upper and lower bounds on the outage probability. These bounds provide better insight on the effect of system's parameters on its performance. Their numerical results show that the time‐hopping technique significantly reduces the outage probability and therefore increases the TC of two‐tier networks.

The paper is concerned with the study of the co-channel cross-layer interference which appears in evolved mobile networks, in which femtocell access points (FAPs) have been deployed. We will investigate the levels of interference for the downlink communication channel, in two cases: macrocell base station (MacroBS) interference at the femtocell user (FUE), and FAP interference at the macrocell user (MUE). The simulations are carried out in a combined indoor-outdoor environment. The performances of the network are evaluated according to the signal to interference plus noise ratio, measured on the downlink communication channel. The results of the study reveal the impact of the deployment of femtocells in existing mobile networks.

Femtocell networks which use femtocell access point (FAP) and existing networks as backhaul connectivity can meet the requirement of high data rate for wireless communication system as well as solve the indoor coverage problem. The handover from femtocell to femtocell is quite demanding and complicated because there are hundreds of possible target FAPs when mobile station (MS) moves out from the coverage of its serving FAP. In this paper, we propose a new mechanism for femtocell-to-femtocell handover which considers several factors such as received signal level, the hidden FAP problem and the access mode of femtocell. The simulation results show that our proposed scheme has a lower handover failure rate and a smaller neighbor femtocell list than the traditional scheme which is based on received signal level only.

This paper studies formation of local femto-clouds in a UMTS LTE network via a cooperative game- theoretic formulation. Femtocell access points (FAPs) equipped with processing power form collaborative coalitions, namely, femto-clouds, with neighboring FAPs and share their computational resources in exchange for monetary incentives. Femto-clouds are formed with the aim to avoid the remote cloud costs while improving the quality of experience (QoE) of users in terms of handling latency. The core of the formulated game represents an optimal structure for femto-clouds such that the computational resources of FAPs are maximally exploited, yet the incentive earned by each femto- cloud is divided among the FAPs in a fair fashion. Numerical simulations using NS3 verify superior QoE of users and higher incentives to FAP owners as compared with alternative schemes.

Soft Computing Based Power Control for Interference Mitigation in LTE Femtocell Networks

Intercell interference is one of the most challenging issues in femtocell deployment under the coverage of existing macrocell. Allocation of resources between femtocell and macrocell is essential to counter the effects of interference in dense femtocell networks. Advances in resource management strategies have improved the control mechanism for interference reduction at lower node density, but most of them are ineffective at higher node density. In this paper, a dynamic resource allocation management algorithm (DRAMA) for spectrum shared hybrid access OFDMA femtocell network is proposed. To reduce the macro-femto-tier interference and to improve the quality of service, the proposed algorithm features a dynamic resource allocation scheme by controlling them both centrally and locally. The proposed scheme focuses on Femtocell Access Point (FAP) owners' satisfaction and allows maximum utilization of available resources based on congestion in the network. A simulation environment is developed to study the quantitative performance of DRAMA in hybrid access-control femtocell network and compare it to closed and open access mechanisms. The performance analysis shows that higher number of random users gets connected to the FAP without compromising FAP owners' satisfaction allowing the macrocell to offload a large number of users in a dense heterogeneous network.

The OpenMobileNetwork is an open platform that provides approximated and semantically enriched mobile network and WiFi access point topology data based on the principles of Linked Data. By making use of the data within the Linking Open Data Cloud, this platform enables the development of new and sophisticated location-based services for the end consumer that also incorporate the semantics of a location rather than plain geospatial information. More importantly, it gives mobile network operators the opportunity to exploit their asset (being their network topology) for innovative services based on semantically enriched data analytics such as identifying location hotspots or traffic heat maps. The foundation of the OpenMobileNetwork is an ontology comprising static and dynamic network context facets that describe mobile and WiFi access point networks from a topological perspective (e.g., base stations, their locations and coverage areas). Within this paper, we present this ontology in detail and demonstrate its applicability in a power management scenario for mobile networks.

The opportunistic utilization of access devices to offload mobile data from cellular network has been considered as a promising approach to cope with the explosive growth of cellular traffic. To foster this opportunistic utilization, we consider a mobile data offloading market where mobile network operator (MNO) can sell bandwidth made available by the access points (APs) to increase MNO's profit. We formulate the offloading problem as a multi-item auction and study MNO's profit maximization problem. We discuss the conditions to (i) offload the maximum amount of data traffic, (ii) foster the participation of mobile subscribers (MSs) (individual rationality), (iii) prevent market manipulation (incentive compatibility) and (iv) preserve budget feasibility of MSs. Then, we propose a robust optimization based method to implement multi-item auction mechanism. We further propose two iterative algorithms that efficiently solve the offloading problem. The simulation results show the efficiency and robustness of our proposed methods for cellular data offloading.