Traffic scheduling and power allocations for mobile data offloading via dual-connectivity

Abstract

With the rapid growth of mobile traffic demand, a promising approach to relieve cellular network congestion is to offload users' traffic to small-cell networks. In this paper, we investigate how the mobile users (MUs) can effectively offload traffic by taking advantage of the capability of dual-connectivity, which enables an MU to simultaneously communicate with a macro base station (BS) and a small-cell access point (AP) via two radio-interfaces. Offloading traffic to the AP usually reduces the MUs' mobile data cost, but often at the expense of suffering increased interferences from other MUs at the same AP.We thus formulate an optimization problem that jointly determines each MU's traffic schedule (between the BS and AP) and power control (between two radio-interfaces). The system objective is to minimize all MUs' total cost, while satisfying each MU's transmit-power constraints through proper interference control. In spite of the non-convexity of the problem, we design both a centralized algorithm and a distributed algorithm to solve the joint optimization problem. Numerical results show that the proposed algorithms can achieve the close-to-optimum results comparing with the ones achieved by the LINGO (a commercial optimization software), but with significantly less computational complexity. The results also show that the proposed adaptive offloading can significantly reduce the MUs' cost, i.e., save more than 75% of the cost without offloading traffic and 65% of the cost with a fixed offloading.

SDN-assisted efficient LTE-WiFi aggregation in next generation IoT networks

“…The work in [22] reduces the waiting time of queues by introducing a virtual WLAN scheduler and aggregating at RLC layer, however, it is not applicable for non-collocated scenarios as it demands heavy MAC layer interactions. Connecting to a BS and AP is considered as a joint optimization problem in [23] and it is solved to minimize cost and power. In [24] additionally a 5-tuple traffic flow template is used to classify the traffic classes between BS and AP.…”

Dual Connectivity for LTE-NR Cellular Networks: Challenges and Open Issues

“…This modification allowed the PF to maintain its property of providing a good trade-off between user fairness and system capacity. The authors in [30] studied a cost minimization problem considering per-user minimum rate constraints for the UL of DC-enabled scenarios, where the authors proposed optimal rate and power allocation schemes. In [31], a resource allocation optimization problem was proposed for computing the user association and frequency slots allocation with the objective of rate maximization.…”

Dual Connectivity in Backhaul-Limited Massive-MIMO HetNets: User Association and Power Allocation

“…We now describe the details of the two-step transformations to reach the GP formulation that approximates the original SGP. Denote x(t) as the variables at the t-th iteration of the iterative algorithm which solves (8). Also, define {s k (t)|k ∈ K 2 } as the set of auxiliary variables, and define {w k (t)|k ∈ K 2 } as the non-negative weighting factors on the respective auxiliary variables.…”

“…Previous works [3,4,7,8] address the traffic splitting optimization with dual connectivity without jointly considering the user-PBS association optimization and backhaul limitations. In this work, we focus on the optimization of traffic splitting and user-PBS association in the uplink by taking into account the backhaul capacity constraints of the single-antenna PBSs, where the MBS is equipped with a large number of antennas.…”