The mobile network operators (MNOs) are looking into economically viable backhaul solutions as alternatives to fiber, specifically the hybrid fiber coaxial networks (HFC). When the latencies from both the wireless and the HFC networks are added together, the result is a noticeable end-to-end system latency, particularly under network congestion. In order to decrease total system latency, we proposed a method to improve upstream user-to-mobile core latency by coordinating the LTE and HFC scheduling in previous papers. In this paper, we implement and optimize the proposed method on a custom LTE and DOCSIS end-to-end system testbed. The testbed uses the OpenAirInterface (OAI) platform for the LTE network, along with Cisco's broadband router cBR-8 that is currently deployed in the HFC networks around the world. Our results show a backhaul latency improvement under all traffic load conditions.

Multi-stream carrier aggregation (MSCA) has been recently proposed as a mechanism to increase the amount of bandwidth available to users for heterogeneous networks (HetNets) in 5G wireless systems. Previous studies have focused only on maximizing the network capacity and fairness, without considering the energy efficiency of the MSCA. In this paper, the use of MSCA to minimize the energy consumption in a multi-layer HetNet is studied. The convexity of the energy minimization problem is examined, leading to the need of a quasi-convex relaxation. With this approximation, an algorithm bisection method for energy minimization is designed to solve the energy minimization problem and obtains an optimum cell-association policy. Since the operators are generally interested in a balance between the energy minimization and capacity maximization, such multi-objective optimization is needed, and we studied it in this paper. The two aforementioned conflicting objectives can be jointly analyzed and solved through scalarization, even though the energy minimization has a quasi-convex objective function, and not a convex one. Performance evaluation is provided to identify the achievable energy savings of our proposed algorithm and to characterize the tradeoffs between the energy minimization and capacity maximization in a multi-layer HetNet in 5G systems that support MSCA.

Cellular network technologies have traditionally evolved to meet the ever-increasing need for capacity and coverage. Particularly, there has been a significant focus on exploiting the use of small cells and heterogeneous networks (HetNets). In the latter, the economic and environmental impact of the energy consumption is a key concern. Although much research has been done to address the energy consumption in HetNets, existing approaches have failed to capture the key factors affecting it. In this paper, the energy consumption in HetNets is analyzed with a focus on their multi-layer nature and the dependence of the energy consumption on the spatio-temporal traffic demands and the internal base station hardware components. The problem of minimizing the energy consumption is then studied and characterized in terms of a 0-1 Knapsack-like problem. Due to the differences with the classical 0-1 Knapsack problem, an efficient algorithm is introduced to minimize the energy consumption by adjusting the cell-association and the base stations on-off policies. Such algorithm is shown to be applicable to the twoand m-layer HetNet cases. Performance evaluation is provided to identify the achievable energy savings of our algorithm and its effect on the energy consumption, activity, and load across multiple layers.

The energy consumption reduction in cellular systems is important from both economic and environmental perspectives. Nearly 80% of the energy in cellular systems is consumed by the Radio Access Network (RAN). In recent years, much research has been done to reduce the energy consumption in the RAN. However, existing models fail to capture the spatiotemporal variability of traffic demands, bit rate and power requirements, as well as the peculiarities in the energy consumption from different hardware components in a base station (BS). In this paper, a new RAN energy consumption model for multi-layer infrastructure-based heterogeneous wireless systems (IbHWS) is proposed. It captures all the aforementioned factors and accurately addresses the characteristics of IbHWS, where cellular systems are a particular case. A low-complexity algorithm is proposed to minimize the RAN's energy consumption, and to satisfy all traffic demands in space and time. Based on extensive simulation results across a wide range of scenarios, the energy savings from this algorithm were on average 26%.

Femtocells have emerged as an alternative solution for operators to improve coverage and throughput in indoor environments. However, modeling and development platforms are still needed in order to test implementation-specific characteristics of femtocells, such as interference mitigation techniques and self-organizing algorithms. Using OPNET, a high fidelity simulation environment for wireless networks, a femtocell modeling and development platform is created, closely following the specifications dictated by 3GPP regarding the entities, functionalities, procedures, and message formats for femtocell networks. It is shown how the platform reflects the effect of both interference and backhaul degradation on the overall performance of the network, which represent the key concerns for operators nowadays regarding femtocell deployments.