Abstract-The growing energy demands, the increasing depletion of traditional energy resources, together coupled with the recent explosion of mobile internet traffic call for green solutions to address the challenges in energy efficient wireless access networks. In this paper, we consider possible power saving through reducing the number of active BSs and adjusting the transmit power of those that remain active while maintaining a satisfying service for all users in the network. Thus, we introduce an optimization problem that jointly minimizes the power consumption of the network and the sum of the transmission delays of the users in the network. Our formulation allows investigating the tradeoff between power and delay by tuning the weighting factors associated to each one. Moreover, to reduce the computational complexity of the optimal solution of our nonlinear optimization problem, we convert it into a Mixed Integer Linear Programming (MILP). We provide extensive simulations for various decision preferences such as power minimization, delay minimization and joint minimization of power and delay. Presented results show that we obtain power savings up to 20% compared to legacy network models.
International audienceIn this paper, we formulate an optimization problem that jointly minimizes the network power consumption and transmission delay in broadband wireless networks. Power saving is achieved by adjusting the operation mode of the network Base Stations (BSs) from high transmit power levels to low transmit levels or switched-off. Minimizing the transmission delay is achieved by selecting the best user association with the BSs. We study the case of a realistic Long Term Evolution (LTE) Network where the challenge is the high computational complexity necessary to obtain the optimal solution. Therefore, we propose a simulated annealing based heuristic algorithm for the power-delay minimization problem. The proposed heuristic aims to compute the transmit power level of the network BSs and associate users with these BSs in a way that jointly minimizes the total network power and the total network delay. The simulation results show that the proposed algorithm has a low computational complexity which makes it advantageous compared with the optimal scheme. Moreover, the heuristic algorithm performs close to optimally and outperforms the existing approaches in realistic 4G deployments
In this paper, we seek to jointly minimize the network power consumption and the user transmission delays in green wireless access networks. We recently studied the case of a WLAN, where we evaluated the tradeoffs between these two minimization objectives using a Mixed Integer Linear Programming (MILP) formulation. However, the MILP formulation could not deliver solutions in a reasonable amount of time due to computational complexity issues. As a result, we propose here a heuristic algorithm for the power-delay minimization problem. The proposed heuristic aims to compute the transmit power level of the Access Points (APs) deployed in the network and associate users with these APs in a way that jointly minimizes the total network power and the total network delay. The simulation results show that the proposed algorithm has a low computational complexity, which makes it advantageous compared with the optimal scheme, particularly in dense networks. Moreover, the heuristic algorithm performs close to optimally and provides power savings of up to 45% compared with legacy networks.
In wireless access networks, one of the most recent challenges is reducing the power consumption of the network, while preserving the quality of service perceived by users. Hence, mobile operators are rethinking their network design by considering two objectives, namely, saving power and guaranteeing a satisfactory quality of service. Since these objectives are conflicting, a tradeoff becomes inevitable. We formulate a multi-objective optimization with aims of minimizing the network power consumption and transmission delay. Power saving is achieved by adjusting the operation mode of the network base stations from high transmit power levels to low transmit levels or even sleep mode. Minimizing the transmission delay is achieved by selecting the best user association with the network base stations. In this article, we cover two different technologies: IEEE 802.11 and LTE. Our formulation captures the specificity of each technology in terms of the power model and radio resource allocation. After exploring typical multi-objective approaches, we resort to a weighted sum mixed integer linear program. This enables us to efficiently tune the impact of the power and delay objectives.We provide extensive simulations for various preference settings that enable to assess the tradeoff between power and delay in IEEE 802.11 WLANs and LTE networks. We show that for a power minimization setting, a WLAN consumes up to 16% less power than legacy solutions. A thorough analysis of the optimization results reveals the impact of the network topology, particularly the inter-cell distance, on both objectives. For an LTE network, we assess the impact of urban, rural and realistic deployments on the achievable tradeoffs. The power savings mainly depend on user distribution and the power consumption of the sleep mode. Compared with legacy solutions, we obtained power savings of up to 22.3% in a realistic LTE networks. When adequately tuned, our optimization approach reduces the transmission delay by up to 6% in a WLAN and 8% in an LTE network.technological developments in the past years to meet capacity and Quality of Service (QoS) demands for User Equipment (UE). Pushed by the needs to reduce energy, mobile operators have recently been rethinking network design for optimizing energy efficiency and satisfying user QoS requirements.Currently, over 80% of the power in mobile telecommunications is consumed by the radio access network, more specifically at the base station (BS) level [4]. Hence, many research activities focus on improving the energy efficiency of wireless access networks. In the following, we give an overview of these activities and classify them according to different approaches that run at different timescales.Planning and deployment: The planning of energy-efficient wireless networks and the deployment of energyaware BSs deal with the problem of determining the positioning of BSs, the type (e.g., macro, micro, pico or femto) and the number of BSs needed to be deployed. In this context, we find that heterogeneous networks ha...
Abstract-Targeting energy efficiency while meeting user Quality of Service (QoS) is one of the most challenging problems in future wireless networks. Since base stations (BSs) consume a high percentage of the total energy used in a wireless access network, saving power at the BS level is a major concern in green networks.In this paper, we propose an optimization model based on finding a tradeoff between reducing the number of active radio cells and increasing the transmit power of BSs to better serve all users in the system. The main contribution of the paper is the formulation of a multiobjective optimization problem that jointly minimizes the network power consumption and the sum of data unit transmission delays of all users in the network. Our proposed model is solved using an exhaustive search algorithm to obtain the optimal solution. Solving the optimization problem at hand is very challenging due to the exhaustive search high computational complexity. Therefore, we run simulations in a small network to give insights into the optimal solution. Specifically, we study different cases by tuning the weights of the power and delay costs. This is a distinctive and important feature of our model allowing it to reflect various decision preferences. Regarding these preferences and under various users spatial distribution, results show that our solution allows to select the optimal network configuration in terms of power consumption while guaranteeing minimal delay for all users in the network.
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