An automated dynamic offset for network selection in heterogeneous networks
- 1. An Automated Dynamic Offset for Network Selection in Heterogeneous Networks Abstract Complementing traditional cellular networks with the option of integrated small cells and WiFi access points can be used to further boost the overall traffic capacity and service level. Small cells along with WiFi access points are projected to carry over 60% of all the global data traffic by 2015. With the integration of small cells on the radio access network levels, there is a focus on providing operators with more control over small cell selection while reducing the feedback burden. Altogether, these issues motivate the need for innovative distributed and autonomous association policies that operate on each user under the network operator’s control, utilizing only partial information, yet achieving near optimal solutions for the network. In this paper, we propose a load-aware network selection approach applied to automated dynamic offset in heterogeneous networks (HetNets). In particular, we investigate the properties of a hierarchical (Stackelberg) Bayesian game framework, in which the macro cell dynamically chooses the offset about the state of the channel in order to guide users to perform intelligent network selection decisions between macro cell and small cell networks. We derive analytically the utility related to the channel quality perceived by users to obtain the equilibria, and compare it to the fully centralized (optimal), the full channel state information and the non-cooperative (autonomous) models. Building upon these results, we effectively address the problem of how to intelligently configure a dynamic offset which optimizes network’s global utility while users maximize their individual utilities. One of the technical contributions of the paper lies in obtaining explicit characterizations of the dynamic offset at the equilibrium and the related performances in terms of the price of anarchy. Interestingly, it turns out that the complexity of the algorithm for finding the dynamic offset of the Stackelberg model is O(n4) (where n is the number of users). It is shown that the proposed hierarchical mechanism keeps the price of anarchy almost equal to 1
- 2. even for a low number of users, and remains bounded above by the non- cooperative model Existing system To cope with the rapidly increasing demand for mobile data driven largely by mobile video and personal communications, low power base stations (BSs) are being deployed in dense urban areas to complement the existing cellular architecture. Densification of the network with SCs is a way to get more capacity from existing spectrum. This results in shifting the spectrum equation as the comparison between spectrum costs and SC costs has changed dramatically. Both engineers and academics are still working out ways for SCs and WiFi APs to integrate seamlessly with macro BSs and with one another. Network access selection is a major concern. Proposed system This paper is to design a dynamic offset which enables operators to steer traffic in order to provide a better user experience and enable the operator to move traffic from the cellular network. To do so, we have proposed a Bayesian hierarchical load- aware association method where partial asymmetric information from the MC and the SC are available in making optimal network selection decisions. The users’ network selection decision is guided by CQI messages conveyed to the mobile users by the MC. Our main result is that we have shown that, in order to maximize its revenue, the network operator – rather than increasing the throughput (which is costly and energy inefficient) – can drive the users to the MC network by a proper choice of information to transmit. We notably propose an algorithm for finding the dynamic offset for the Stackelberg model whose complexity is polynomial in the number of users. It turns out that the channel quality indicator the operator should choose is either very small or very large in comparison to the one maximizing the global throughput of both systems. We have also observed that the dynamic offset Ψ at the Stackelberg equilibrium is decreasing with the number of active users n.
- 3. This is to say that when n grows, users can connect more often to the SC network without wasting the MC resources, which results in a smaller Ψ above which users connect to SC. One important consequence is that any mechanism aim in gat stimulating the use of the MC network only through a small amount of proper signaling, should concentrate on doing it for smaller number of users. Furthermore, we have observed that the PoA of the proposed hierarchical mechanism is almost equal to 1 even for a low number of users, and remains bounded above by the non- cooperative model as the number of users grows. Achieving these results offers hope that such a smart mechanism can be designed around SC integration in HetNets and can be implemented using the notion of Cell Selection Bias (CSB) proposed by LTE standards.