Autonomous distributed QoS aware sleep control considering carrier aggregation in heterogeneous cellular networks In order to reduce power consumption and provide various kinds of communication services to the users with different quality of services (QoSs) in heterogeneous cellular networks (HetNets), sleep control has been studied considering QoS provision. Most of the existing studies employ central control manner in their sleep control for base stations (BSs), and less consideration of carrier aggregation (CA) operation, which is one of the promising techniques for improving the QoS provision performance. This paper investigates QoS aware sleep control for the HetNets, by using autonomous and distributed control manner with small control overhead, while considering the CA operation. Then, the performance for the proposed autonomous distributed QoS aware sleep control is evaluated through computer simulation, including the effect of the CA operation in the HetNets. The proposed sleep control shows better performance in the energy efficiency and QoS provision, compared with the conventional one.

Proportional Fair RAT Aggregation in HetNets Heterogeneity in wireless network architectures (i.e., the coexistence of 3G, LTE, 5G, WiFi, etc.) has become a key component of current and future generation cellular networks. Simultaneous aggregation of each clientu0027s traffic across multiple such radio access technologies (RATs)  base stations (BSs) can significantly increase the system throughput, and has become an important feature of cellular standards on multiRAT integration. Distributed algorithms that can realize the full potential of this aggregation are thus of great importance to operators. In this paper, we study the problem of resource allocation for multiRAT traffic aggregation in HetNets (heterogeneous networks). Our goal is to ensure that the resources at each BS are allocated so that the aggregate throughput achieved by each client across its RATs satisfies a proportional fairness (PF) criterion. In particular, we provide a simple distributed algorithm for resource allocation at each BS that extends the PF allocation algorithm for a single BS. Despite its simplicity and lack of coordination across the BSs, we show that our algorithm converges to the desired PF solution and provide (tight) bounds on its convergence speed. We also study the characteristics of the optimal solution and use its properties to prove the optimality of our algorithmu0027s outcomes.