Louai Saker

Optimal Control of Wake Up Mechanisms of Femtocells in Heterogeneous Networks

We study, in this work, optimal sleep/wake up schemes for the base stations of network-operated femto cells deployed within macro cells for the purpose of offloading part of its traffic. Our aim is to minimize the energy consumption of the overall heterogeneous network while preserving the Quality of Service (QoS) experienced by users. We model such a system at the flow level, considering a dynamic user configuration, and derive, using Markov Decision Processes (MDPs), optimal sleep/wake up schemes based on the information on traffic load and user localization in the cell, in the cases where this information is complete, partial or delayed. Our results quantify the energy consumption and QoS perceived by the users in each of these cases and identify the tradeoffs between those two quantities. We also illustrate numerically the optimal policies in different traffic scenarios.

Minimizing Energy Consumption via Sleep Mode in Green Base Station

In this paper, we develop new energy-efficient, radio resource management schemes for green wireless networks. Our goal is to optimize energy consumption at the network scale while preserving the Quality of Service (QoS) perceived by users. We specifically propose two new sleep mechanisms for base station where a number of resources in system can be shut down for some traffic scenarios in one of two ways: a dynamic way where resources are activated/deactivated in real-time as a function of the instantaneous load of the system, and a semi-static one where resources are kept unchanged during longer time intervals, in the order of one hour. We apply the proposed schemes to 2G and HSPA (High Speed Packet Access) systems and show that the dynamic one achieves larger energy reductions while the semi-static one has an acceptable performance with low complexity

Sleep mode implementation issues in green base stations

In this paper, we focus on practical issues when implementing sleep mode in base stations. Our aim being to reduce energy consumption without affecting the Quality of Service (QoS) perceived by users, we expose some problems that my occur when applying sleep mode and propose practical solutions to cope with the resulting QoS degradation. We namely consider activation time issue that may result in blocking new or handover calls, and the ping-pong effect resulting in unnecessary ON/OFF oscillations. We show, using a realistic large-scale simulator, how to choose sleep mode implementation that achieves the best tradeoff between QoS preservation and energy consumption reduction.

Optimal control for base station sleep mode in energy efficient radio access networks

In this paper1, we investigate network sleep mode for reducing energy consumption of radio access networks. We propose an offline-optimized controller that associates to each traffic an activation/deactivation policy that maximizes a multiple objective function of the Quality of Service (QoS) and the energy consumption. We focus on practical implementation issues that may affect the QoS and the stability of the system. We namely consider the activation time issue that results in the degradation of the throughput and the ping-pong effect that results in unnecessary ON/OFF oscillations. We illustrate our results numerically in beyond 3G networks.

Capacity and Energy Efficiency of Picocell Deployment in LTE-A Networks

In this paper, we show the impact of deploying picocells on the capacity and energy efficiency of LTE-A networks. We analyze the Erlang-like capacity of a network composed of macro networks only and study the impact of introducing a number of picocells per site. Knowing that the capacity is not the only factor that will drive the evolution of the network, we also consider the energy efficiency as a Key Performance Indicator (KPI). Our results show that, in some scenarios, introducing picocells is a good network densification method as they achieve a higher network capacity with good energy efficiency.

Optimal online control for sleep mode in green base stations

In this paper, we investigate network sleep mode schemes for reducing energy consumption of radio access networks. We first propose, using Markov Decision Processes (MDPs), an optimal controller that associates to each traffic an activation/deactivation policy that maximizes a multiple objective function of the Quality of Service (QoS) and the energy consumption. We focus on a practical implementation issue, namely the ping pong effect resulting in unnecessary ON/OFF oscillations, that may affect the stability of the system. We illustrate our results numerically using theoretical models of the radio access network, and apply the developed mechanisms on a large-scale network simulator. Knowing that an offline optimization is not suitable for a large-scale network nor does it fit all traffic configurations, we propose, using an online controller that derives dynamically the optimal policy based on the dynamics of users in the cell. The design of our online controller is based on a simple ?-greedy algorithm and learns the optimal threshold policy for activation/deactivation of network resources.

Realistic Energy Saving Potential of Sleep Mode for Existing and Future Mobile Networks

This paper presents an extensive overview on an energy saving feature referred to as ‘site sleep mode’, designed for existing and future mobile broadband networks. In addition to providing a detailed understanding of the main concept, the paper also provides various studies and results to highlight potential savings, and emphasize some of the expected limitations. Since site measurements show that the energy consumption of base station sites is largely load-independent, this makes such a feature highly effective for reducing the energy consumption of mobile networks during hours of low traffic. After going through a number of different alternatives of the feature, this is applied to different network topologies, macro-only based networks, and a set of heterogeneous networks that employ the use of small cells in traffic hotspots. Results obtained through detailed case studies show that sleep mode can reduce the average daily energy consumption of a network by around 30%. This can be achieved while maintaining a predefined level of performance, used as a measure of comparing different scenarios.

How femtocells impact the capacity and the energy efficiency of LTE-Advanced networks

In this paper1, we show the impact of femtocells deployment on the capacity of LTE-Advanced networks. We analyze the Erlang-like capacity of a network composed of macro networks only and study the impact of introducing femtocells. We study the ability of open and closed access femtocells to offload traffic from the macro network and draw the capacity gains that are expected from this offload. Knowing that femtocells are not managed by the operator, but installed by clients, we take into account the random nature of the resulting deployment in the capacity analysis. Our results quantify the gains thus achieved, in terms of user QoS and cell load, as well as energy efficiency, as compared to a pure macro network.

Impact of picocells on the capacity and energy efficiency of mobile networks

The deployment of small cells in mobile networks has aroused a large interest in the last few years. This paper investigates the impact of picocell deployment on the performance and power consumption of mobile networks. Since different network upgrades introduce different performance gains, comparing different configurations exclusively on their overall power consumption can be rather biased. For this reason, a new key performance indicator, termed “energy efficiency”, is introduced and used throughout this study, bringing together network performance and its overall power consumption. In the first section of the study, a theoretical analysis for the Erlang-like capacity of a network, considering a uniform topology and traffic, is performed, using queuing theory analysis, namely processor-sharing queues. Results show that in all cases the deployment of picocells improve the performance of the network, however the energy efficiency is noted to be dependent on the deployment scenario considered. In the second part of the study, a more realistic scenario with non-uniform topology and traffic is considered, which is carried out through a large-scale system level simulator. Results show that by deploying picocells in areas experiencing high levels of traffic, the energy efficiency of the network can be considerably improved.