# Game Theory-Based Smart Mobile-Data Offloading Scheme in 5G Cellular Networks
## 2 Related Work and Background  
Recently, there has been some work on MDO in WCNs, which roughly falls into three technologies [26]: for data traffic through small cells, on Wi-Fi networks and via opportunistic communications. In the following, we summarize the related work in each technology. Figure 1: A simple offloading example. MDO through small cells is an effective method to reduce traffic congestion and network energy consumption in a heterogeneous cellular network (HCN) [26; 27]. [PERSON] et al. [26] provided a brief survey on existing traffic offloading techniques in WCNs, and they modeled the energy-aware traffic offloading problem in such HCNs as a discrete-time Markov decision process that puts forward an online reinforcement learning framework. [PERSON] et al. [27] proposed an auction-based traffic offloading scheme to achieve both load balance among base stations (BSs) and fairness among UEs. Unfortunately, dense deployment of BSs in small cells is limited due to expensive backhaul connections and possible severe interference. Moreover, the problem of macrocell traffic admitted by incentivizing femtocell owners is recently studied [28; 29; 30; 31; 32]. The economic incentive issue is studied in MDO via third-party access points by using either the auction framework [33] or the non-cooperative Stackelberg game framework [34]. In general, these works studied the incentive issues using a non-cooperative game framework, which cannot capture the potential of coordination among players (which calls for a cooperative game approach). [PERSON] et al. [35] studied the economic incentive issue by using a cooperative game framework (Nash bargaining) with the bargaining model between one mobile operator and one fixed-line operator, while the multi-player bargaining model in our work is a more general type of bargaining among D2D links. [PERSON] et al. [36] applied the NBS for a fair user-association scheme in heterogeneous networks (HetNets), where different BSs are modeled as players to compete for serving users. MDO on Wi-Fi networks provides a performance benefit that has been proven in the literature [3; 4; 5; 6; 7; 8], and several works addressed the network economics of traffic offloading using game theory [2; 37; 38]. [PERSON] et al. [2] modeled and analyzed MDO via third-party Wi-Fi and femtocell access points (APs) and proposed a one-to-many bargaining framework to study the economic incentive issues. In [37], [PERSON] et al., modeled a market based on a two-stage sequential game, and investigated how much economic benefit can be generated from delayed Wi-Fi offloading. [PERSON] et al. [38] formulated the problem of MDO as a reverse auction to offload the maximum amount of data traffic with the cheapest APs selected from the cellular network. However, service coverage and mobility are limited in Wi-Fi offloading, and CNOs usually find it impossible to capture complete visibility of traffic flows if using this offload technique for traffic offloading [26]. MDO via opportunistic communications exploits D2D communications as an overlay to offload traffic from the BSs [26]. With D2D communications, UEs in proximity to each other can exchange data directly without relying on a network infrastructure [39; 40], and consequently, they get higher data rates and reduced power consumption [39; 41; 42; 43]. [PERSON] et al. [43] investigated the problem of traffic offloading in cellular networks by reducing the required number of long-distance channels while distributing common content to a group of UEs. [PERSON] et al. [44] studied a resource allocation problem to maximize overall network throughput while guaranteeing QoS requirements for both D2D users and regular cellular users. Non-cooperative game model is employed to obtain a distributed resource allocation for D2D communications underlay cellular network [45; 46; 47; 48; 49]. [PERSON] et al.