Interference-Aware Decoupled Cell Association in Device-to-Device based 5G Networks

Cell association in cellular networks is an important aspect that impacts network capacity and eventually quality of experience. The scope of this work is to investigate the different and generalized cell association (CAS) strategies for Device-to-Device (D2D) communications in a cellular network infrastructure. To realize this, we optimize D2D-based cell association by using the notion of uplink and downlink decoupling that was proven to offer significant performance gains. We propose an integer linear programming (ILP) optimization framework to achieve efficient D2D cell association that minimizes the interference caused by D2D devices onto cellular communications in the uplink as well as improve the D2D resource utilization efficiency. Simulation results based on Vodafone's LTE field trial network in a dense urban scenario highlight the performance gains and render this proposal a candidate design approach for future 5G networks.Comment: 5 pages, 5 figures. Accepted in IEEE VTC spring 201

Matching theory for priority-based cell association in the downlink of wireless small cell networks

The deployment of small cells, overlaid on existing cellular infrastructure, is seen as a key feature in next-generation cellular systems. In this paper, the problem of user association in the downlink of small cell networks (SCNs) is considered. The problem is formulated as a many-to-one matching game in which the users and SCBSs rank one another based on utility functions that account for both the achievable performance, in terms of rate and fairness to cell edge users, as captured by newly proposed priorities. To solve this game, a novel distributed algorithm that can reach a stable matching is proposed. Simulation results show that the proposed approach yields an average utility gain of up to 65% compared to a common association algorithm that is based on received signal strength. Compared to the classical deferred acceptance algorithm, the results also show a 40% utility gain and a more fair utility distribution among the users.Comment: 5 page

On/Off Macrocells and Load Balancing in Heterogeneous Cellular Networks

The rate distribution in heterogeneous networks (HetNets) greatly benefits from load balancing, by which mobile users are pushed onto lightly-loaded small cells despite the resulting loss in SINR. This offloading can be made more aggressive and robust if the macrocells leave a fraction of time/frequency resource blank, which reduces the interference to the offloaded users. We investigate the joint optimization of this technique - referred to in 3GPP as enhanced intercell interference coordination (eICIC) via almost blank subframes (ABSs) - with offloading in this paper. Although the joint cell association and blank resource (BR) problem is nominally combinatorial, by allowing users to associate with multiple base stations (BSs), the problem becomes convex, and upper bounds the performance versus a binary association. We show both theoretically and through simulation that the optimal solution of the relaxed problem still results in an association that is mostly binary. The optimal association differs significantly when the macrocell is on or off; in particular the offloading can be much more aggressive when the resource is left blank by macro BSs. Further, we observe that jointly optimizing the offloading with BR is important. The rate gain for cell edge users (the worst 3-10%) is very large - on the order of 5-10x - versus a naive association strategy without macrocell blanking