Journal of Communications Vol. 14, No. 3, March 2019 Optimized Wi-Fi Offloading Scheme for High User Density in LTE Networks Thamary Alruhaili1, Ghadah Aldabbagh1, Fatma Bouabdallah2, Nikos Dimitriou3, and Moe Win4 1Computer Science Department, Faculty of Computing and Information Technology, King AbdulAziz University, Jeddah, Saudi Arabia 2Information Technology Department, Faculty of Computing and Information Technology, King AbdulAziz University, Jeddah, Saudi Arabia 3Institute of Informatics and Telecommunications, NCSR Demokritos, Athens, Greece 4Laboratory for Information & Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA Emails: [email protected], {fothman1, galdabbagh}@kau.edu.sa, [email protected], [email protected], [email protected] Abstract1—Mobile networks are facing the growing flood of year. Vendors need to find new solutions for such Internet data, as stated by Cisco. Indeed, the traffic from smart occasions rather than building new base stations or leasing phones is expected to grow from 92 percent to 99 percent by new spectrum [1], [2]. Long Term Evolution (LTE) 2021. Therefore, new solutions must be conceived by vendors attracts attention, as wireless operators with LTE networks and mobile operators to reduce network congestion with a low can handle more mobile traffic, as LTE technology cost to preserve customers. This issue is even more critical with mass events, which occur once a year, such as hajj, festivals and incorporates adding additional spectrum. football games at stadiums. Half of smartphones and over 90% of One promising solution to cope with the huge capacity 4G enabled laptops and notebook PCs are already Wi-Fi enabled. requirements generated by the increasing number of Hundreds of millions ubiquitous Wi-Fi access points provide mobiles is Wi-Fi small cell deployment. Wi-Fi is a good large enough complementary capacity space for mobile networks. solution due to its characteristics, uses vast unlicensed Thus, a novel mechanism for Wi-Fi offloading must be explored bands 2.4 GHz and 5 GHz, high user experience, advanced with the purpose of finding a suitable cell association method to security, high data rate, advanced QoS and its built in most assign users to the best tier. This can be done by considering suitable approaches to manage the network selection method, to end user devices [3], [4]. Wi-Fi small cell deployment gain the expected capacity enhancement. In this paper, we overlay in a Macro LTE cell, introduces the offloading propose a new offloading algorithm called, Optimized Wi-Fi notion. Data offloading concept implies, the use of a offloading algorithm, based on an optimization cost function. complementary network technology to deliver data traffic, This Optimized Wi-Fi offloading algorithm, not only optimizes which originally targeting the cellular network [5]. The three important criteria in balancing the load, but also it can motivation behind using Wi-Fi offloading in high guarantee a Quality of Service (QoS) to the successfully populated areas is to help users in gaining a connection connected user to any tier based on required service. Simulation with high throughput and data rate. This may relieve the results prove the expected capacity enhancement, by comparing the performance of the Optimized Wi-Fi Offloading with another congested LTE Macro cell, and improve the overall tow offloading Algorithms. The first algorithm is Wi-Fi if network capacity indeed. Coverage, second, Fixed SNR threshold. This study aims to find a proper cell association scheme to offload users in a high-density area from LTE to Wi-Fi Index Terms—Capacity, LTE, Network selection, QoS, Wi-Fi Access Points. This is done with the objective of Offloading. enhancing the overall network capacity. Capacity enhancement is evident in terms of the number of I. INTRODUCTION connected users, and network throughput can validate the Mobile communication technology evolved rapidly, system improvement. This is achieved through serving with the popularity of using smart phones in the past years. users with QoS based on the required service, which is This creates an exponential growth in traffic demands assumed to be VoIP service in this research. from users with QoS. Wireless communication will not be The rest of the paper is organized as follows: Section 2 able to cope with the increasing demands for higher presents the related state of the art in Wi-Fi offloading throughput and data rate. This issue is raised in schemes. Section 3 demonstrates the proposed Optimized congestions areas and mass events, which occur once a Wi-Fi offloading algorithm. Network Selection Schemes (NSS) are presented in section 4. Simulation setup and performance assessment along with the result is declared Manuscript received Month Day, 2016; revised Month Day, 2016. in Section 5. Section 6 concludes the study, and future This work was supported by KACST award number work is presented. Section 7 represents the author's (12-INF2743-03). Corresponding author email: [email protected] acknowledgment statement. doi:10.12720/jcm.14.3.179-186 ©2019 Journal of Communications 179 Journal of Communications Vol. 14, No. 3, March 2019 II. STATE OF THE ART there is Wi-Fi coverage, otherwise the user joins LTE. The WF performance under uniform and a non-uniform Wi-Fi In this section authors review the related Wi-Fi backhaul capacity distribution. Results proves that WF has offloading schemes and algorithms. The first section a bad performance in terms of average throughput per user demonstrates levels of integration between LTE and Wi-Fi and fairness. Fixed SNR Threshold offloading algorithm is networks. The second section presents different offloading mentioned in [12], and it is a function of the WLAN load. schemes or algorithms, with different network access This algorithm triggers network offloading based on selection mechanisms to trigger the offloading decision. choosing the best SNR min value for WLAN APs. This A. Levels of Integrating Wi-Fi with LTE Networks algorithm may have a similar behavior to Wi-Fi if The European Telecommunications Standards Institute Coverage only at low traffic loads. Fixed SNR algorithm is has defined different levels of integration for 3GPP and considered better than Wi-Fi if coverage in terms of non-3GPP networks. There are three levels of integration balancing the load between a Wi-Fi AP tier and an LTE between LTE network and Wi-Fi networks. The first tier. integration level is called: Network bypass or the In [14] different traffic steering policy was investigated, un-managed data offloading. Second is: managed data which is called Best-Server algorithm. This algorithm offloading and the third is: integrated data offloading. The connects users to Wi-Fi AP first rather than cellular, which first approach is, un-managed data offloading or bypass is like Wi-Fi if a coverage and WF algorithm. The offloading, considered the easiest type of offloading, offloading is triggered if the Signal to Interference and where data are directed to Wi-Fi whenever the coverage is Noise Ratio (SINR) perceived by end user is above a found with no need for equipment installation. In this certain threshold; otherwise users are connected to LTE immediate offloading solution operator suffers from network. Best-Server algorithm depends on SINR, while losing revenue and control over subscribers [6], [7]. Wi-Fi if a Coverage and WF algorithms depend on SNR The Second approach is managed data offloading, is with the assumption of using non-overlapping channels. used by the operators who don’t want to lose control of All three algorithms only guarantee the connection for their subscribers. However, they are not allowed to send connected users, they do not guarantee a quality of service subscribed content. Managed data offloading, give (QoS). Another offloading scheme presented in [13] is operators a limited control on their subscribers without the Physical Data Rate Based algorithm (PDR), which is need to fully integrate the two networks. The Third technically based on the PDR measured from different offloading approach is integrated data offloading, which available RATs. This scheme compares the perceived data empower the operators with a full control over their rate for LTE and Wi-Fi, and chooses the highest value a subscribers along with the ability to send subscribed user can get. A similar algorithm presented in [14], called content. Integrated offloading raises the coupling the SMART algorithm, triggers the offloading based on architecture notion for Wi-Fi with cellular systems, which the minimum PDR as long measured SINR exceeds a they can be divided into two coupling architectures: loose certain threshold. coupling and tight coupling [6]-[8]. In loose coupling A generic framework called Mobile Femto cells architecture, no need for a major cooperation between utilizing Wi-Fi (MFW) developed in [15]. The MFW Wi-Fi network and the cellular network and both can be exploit both Femto-cell and Wi-Fi networks at the same independent from each other. In tight coupling, each time. This framework permits operators to offload the network is required to modify its services, protocols, and traffic onto Femto base stations (mob FBS) in a public interfaces for interworking together as both owned by the transportation system The Wi-Fi AP is utilized by mob same operator. This is provided through I-WLAN standard FBS as a backhaul for routing traffic to the cellular from 3GPP, which allows transferring data through Wi-Fi network. between user’s devices and cellular systems [6], [7], [9], C. Network Selection Mechanisms [10]. Offloading approach is used to overcome the B. Wi-Fi Offloading Algorithms & Schemes congestions in a cellular network, by offloading data Offloading decisions or Network access selection traffic to a complementary access network. There are triggering criteria, are performed based on different various network selection mechanisms with different parameters. The offloading may have different objectives offloading decision.