1,720,993 research outputs found
Green Mobile Networks: from self-sustainability to enhanced interaction with the Smart Grid
Full text linkNowadays, the staggering increase of the mobile traffic is leading to the deployment of denser and denser cellular access networks, hence Mobile Operators are facing huge operational cost due to power supply. Therefore, several research efforts are devoted to make mobile networks more energy efficient, with the twofold objective of reducing costs and improving sustainability. To this aim, Resource on Demand (RoD) strategies are often implemented in Mobile Networks to reduce the energy consumption, by dynamically adapting the available radio resources to the varying user demand. In addition, renewable energy sources are widely adopted to power base stations (BSs), making the mobile network more independent from the electric grid. At the same time, the Smart Grid (SG) paradigm is deeply changing the energy market, envisioning an active interaction between the grid and its customers. Demand Response (DR) policies are extensively deployed by the utility operator, with the purpose of coping with the mismatches between electricity demand and supply. The SG operator may enforce its users to shift their demand from high peak to low peak periods, by providing monetary incentives, in order to leverage the energy demand profiles. In this scenario, Mobile Operators can play a central role, since they can significantly contribute to DR objectives by dynamically modulating their demand in accordance with the SG requests, thus obtaining important electricity cost reductions.
The contribution of this thesis consists in investigating various critical issues raised by the introduction of photovoltaic (PV) panels to power the BSs and to enhance the interaction with the Smart Grid, with the main objectives of making the mobile access network more independent from the grid and reducing the energy bill.
When PV panels are employed to power mobile networks, simple and reliable Renewable Energy (RE) production models are needed to facilitate the system design and dimensioning, also in view of the intermittent nature of solar energy production.
A simple stochastic model is hence proposed, where RE production is represented by a shape function multiplied by a random variable, characterized by a location dependent mean value and a variance. Our model results representative of RE production in locations with low intra-day weather variability. Simulations reveal also the relevance of RE production variability: for fixed mean production, higher values of the variance imply a reduced BS self-sufficiency, and larger PV panels are hence required. Moreover, properly designed models are required to accurately represent the complex operation of a mobile access network powered by renewable energy sources and equipped with some storage to harvest energy for future usage, where electric loads vary with the traffic demand, and some interaction with the Smart Grid can be envisioned. In this work various stochastic models based on discrete time Markov chains are designed, each featuring different characteristics, which depend on the various aspects of the system operation they aim to examine.
We also analyze the effects of quantization of the parameters defined in these models, i.e. time, weather, and energy storage, when they are applied for power system dimensioning. Proper settings allowing to build an accurate model are derived for time granularity, discretization of the weather conditions, and energy storage quantization.
Clearly, the introduction of RE to power mobile networks entails a proper system dimensioning, in order to balance the solar energy intermittent production, the traffic demand variability and the need for service continuity. This study investigates via simulation the RE system dimensioning in a mobile access network, trading off energy self-sufficiency targets and cost and feasibility constraints. In addition, to overcome the computational complexity and long computational time of simulation or optimization methods typically used to dimension the system, a simple analytical formula is derived, based on a Markovian model, for properly sizing a renewable system in a green mobile network, based on the local RE production average profile and variability, in order to guarantee the satisfaction of a target maximum value of the storage depletion probability.
Furthermore, in a green mobile network scenario, Mobile Operators are encouraged to deploy strategies allowing to further increase the energy efficiency and reduce costs. This study aims at analyzing the impact of RoD strategies on energy saving and cost reduction in green mobile networks. Up to almost 40% of energy can be saved when RoD is applied under proper configuration settings, with a higher impact observed in traffic scenarios in which there is a better match between communication service demand and RE production. While a feasible PV panel and storage dimensioning can be achieved only with high costs and large powering systems, by slightly relaxing the constraint on self-sustainability it is possible to significantly reduce the size of the required PV panels, up to more than 40%, along
with a reduction in the corresponding capital and operational expenditures.
Finally, the introduction of RE in mobile networks contributes to give mobile operators the opportunity of becoming prominent stakeholders in the Smart Grid environment. In relation to the integration of the green network in a DR framework, this study proposes different energy management policies aiming at enhancing the interaction of the mobile network with the SG, both in terms of energy bill reduction and increased capability of providing ancillary services. Besides combining the possible presence of a local RE system with the application of RoD strategies, the proposed energy management strategies envision the implementation of WiFi offloading (WO) techniques in order to better react to the SG requests. Indeed, some of the mobile traffic can be migrated to neighbor Access Points (APs), in order to accomplish the requests of decreasing the consumption from the grid. The scenario is investigated either through a Markovian model or via simulation. Our results show that these energy management policies are highly effective in reducing the operational cost by up to more than 100% under proper setting of operational parameters, even providing positive revenues. In addition, WO alone results more effective than RoD in enhancing the capability to provide ancillary services even in absence of RE, raising the probability of accomplishing requests of increasing the grid consumption up to almost 75% in our scenario, twice the value obtained under RoD. Our results confirm that a good (in terms of energy bill reduction) energy management strategy does not operate by reducing the total grid consumption, but by timely increasing or decreasing the grid consumption when required by the SG.
This work shows that the introduction of RE sources is an effective and feasible solution to power mobile networks, and it opens the way to new interesting scenarios, where Mobile Network Operators can profitably interact with the Smart Grid to obtain mutual benefits, although this definitely requires the integration of suitable energy management strategies into the communication infrastructure management
Can High Altitude Platforms Make 6G Sustainable?
Full text linkThe staggering growth of mobile traffic
fostered by the spreading of 5G technology and massive
Internet of Things applications is leading to the need for
extensive Radio Access Network (RAN) densification.
However, the entailed boost in energy consumption
poses significant challenges for a sustainable transition
towards 6G. High Altitude Platform Stations (HAPSs)
equipped with aerial Base Stations (BSs) represent a
promising and flexible solution to provide additional
capacity that can be used in a flexible way to facilitate
terrestrial BSs sleep modes and, ultimately, reduce
energy consumption and make the network more sus-
tainable.
As a case study, we consider a portion of a urban RAN
to investigate the potential benefits deriving from the
integration of HAPSs in terrestrial RANs as a means to
support joint energy and resource allocation strategies
that will be needed in 6G networks. Our results show
that offloading traffic to HAPS mounted BSs allows to
reduce the grid energy demand of terrestrial still maintaining adequate Quality of Service
Integration of Renewable Energy Sources into 5G Networks and Beyond
No full textWith the incredible upsurge of traffic demand in 5G scenarios, the need for extensively densified communication networks is currently leading to remarkably increase their overall energy consumption and the related operational cost. In this context, the integration of renewable energy (RE) results promising to support a sustainable shift towards future generation networks. However, the intermittent and unpredictable nature of RE generation poses relevant issues to be tackled when planning and operating a RE-powered communication network. This article discusses the main challenges raised by the integration of RE in 5G and beyond scenarios and the possible solutions to overcome criticalities that may hamper a sustainable deployment of next generation communication networks. First, the problem of properly dimensioning and displacing RE generators to power network nodes is addressed. Furthermore, the crucial role of implementing energy and radio resource management strategies to more efficiently exploit RE, enhance the renewable system feasibility, and improve the performance of the network operation is discussed. Moreover, new business models are analysed, raising from the possibility for RE-powered networks to dynamically interact with the Smart Grid to obtain mutual financial benefits, also based on energy trading, and to take advantage of the cooperation between different domains to achieve sustainability goals. A special focus is devoted to the key role played by Artificial Intelligence to support an effective operation of RE-powered networks, thanks to the provisioning of accurate predictions of RE availability, traffic load, and electricity prices, required to take timely and appropriate energy and resource management decisions. Finally, this article discusses how the integration of aerial networks to support on-ground mobile networks may contribute to enhance the feasibility of RE-powered communication networks and promote a sustainable transition towards the 6G era
Renewable powered Battery Swapping Stations for sustainable urban mobility
Full text linkDue to sustainability concerns raised by the transportation sector, still relying mostly on oil as main energy source, urban mobility is quickly shifting towards the adoption of electric vehicles (EVs), The EV charging process should heavily rely on Renewable Energy Sources (RES) and be smartly scheduled to promote sustainability and pollution reduction. In this context, renewable powered Battery Swapping Stations (BSS) represent a promising solution to enable sustainable and feasible e-mobility. Focusing on a BSS powered by photovoltaic panels, we investigate the issue of properly dimensioning its capacity (in terms of number of sockets) and the renewable energy supply to satisfy the battery swapping demand, trading off cost, Quality of Service and feasibility constraints. In addition, we analyse the potential benefits of smart scheduling strategies for battery recharging. Our results show that considerable cost saving of up to almost 40% can be achieved with a local RE supply to power the BSS. Furthermore, a proper tuning of the scheduling strategy configuration parameters is required to better trade off cost and Quality of Service, based on the desired performance targets
Reinforcement Learning for charging scheduling in a renewable powered Battery Swapping Station
Full text linkBattery Swap (BS) technology represents a promising solution to overcome the main obstacles to a widespread adoption of electric vehicles (EVs) in a urban environment, like the limited range of EVs and the long battery charging time. Furthermore, with respect to traditional charging stations, it offers higher flexibility in dynamically managing the EV electricity demand to prevent the risk of power grid overload. Nevertheless, proper scheduling of the battery charge process is crucial to offer effective e-mobility services, trading off cost, Quality of Service and feasibility constraints. In this paper we consider a renewable powered multi-socket Battery Swapping Station (BSS) and design two algorithms based on Approximate Dynamic Programming (ADP) and Reinforcement Learning (RL) to dynamically adapt the scheduling of the battery charging process to the stochastic nature of the system. Both approaches are proved to be effective in remarkably enhancing the service quality in terms of increased capability to satisfy the customer demand for EV battery charging, at a lower cost with respect to benchmark approaches, with RL outperforming ADP under any budget constraint. In particular, under RL the probability of not satisfying the EV demand can be decreased by up to more than 40% with respect to benchmark approaches, and a significant cost reduction of almost 20% can be achieved, jointly with a greener system operation. Furthermore, our results show that a fine tuning of hyper-parameters is fundamental to properly trade off cost and Quality of Service constraints according to varying business needs. Finally, we analyse how the proposed strategies may affect the battery health due to their impact on battery degradation, hence influencing the BSS management cost
Radio Resource Management for Improving Energy Self-sufficiency of Green Mobile Networks
No full textThree factors make power supply one of the most urgent and challenging issues for the future of mobile networks. First, the expected fast growth of mobile traffic raises doubts about the sustainability of mobile communications, that already account for 0.5% of the woldwide energy consumption. Second, power supply has become far the largest component of the operational costs of running a network. Third, the deployment of network infrastructures in emerging countries is strategic, but, in these countries, the power grid is not always reliable. Renewable energy sources can help to cope with these issues. However, one of their main drawbacks is the intermittent and difficult to predict energy generation profile. The feasibility of renewable power supply for base station (BS) powering depends then by the possibility to reduce the BS consumption and to adapt it to the amount of available energy. In this paper, we consider a cluster of BSs powered with photovoltaic (PV) panels and equipped with energy storage units. Resource on Demand (RoD) strategies are implemented to reduce the cluster energy consumption and to adapt it to energy availability. The results show that resource of demand can effectively be applied to make off-grid BS deployment feasible
Caching in the Air: High Altitude Platform Stations for Urban Environments
Full text linkDue to the evolution in communications technologies
and antennas, as well as advances in solar panel efficiency, High
Altitude Platforms (HAPS) have been recently considered as a
promising aerial network component, to support Radio Access
Networks (RANs). Through their directional antenna they can
activate beams and provide coverage to up to 1.5 km radius
ground area. In this work, we consider a HAPS equipped with a
Multi Access Edge Computing (MEC) server, which provides
caching capabilities. The HAPS is used to off-load content
requests. We analyse an urban environment scenario, as well as
the effects of the simultaneous activation of beams in different
areas. Results demonstrate that the HAPS is a suitable solution
to bring additional capacity to the RAN and highlight that the
provided performance strictly depends on the traffic demand
profile of the covered portion of RAN
On Fairness in Network Sharing
Full text linkNetwork Sharing (NS) has gained increasing interest for Mobile Operators (MOs) because of the high investment costs of 5G combined with a period of low return of investment. The benefits that NS can offer include reduced capital and operational expenditures, because of fewer equipment, and lower energy consumption, possibly combined with higher network resiliency. While these aspects have been investigated in the literature, in those works more attention was paid to the overall benefits, disregarding asymmetries between the involved MOs. In this paper we address the issue of fairness in sharing network infrastructure among MOs and we introduce a Fair Cooperative Network Sharing (FCNS) framework that dynamically offloads traffic among co-located BSs owned by different MOs with two primary objectives: distributing active operational time more equitably between BSs in a pair, and significantly decreasing the failure rate of BS pairs. Simulation results based on empirical mobile traffic data demonstrate that the proposed FCNS framework effectively balances the BS active time across operators. In addition, FCNS achieves energy savings of up to 38% for each MO within a BS pair and reduces the failure rate by approximately 20%. These findings highlight the potential of cooperative network sharing as a feasible and sustainable solution for resilient 5G deployments
Accounting for the Varying Supply of Solar Energy when Designing Wireless Access Networks
Full text linkTraditionally, we rely highly upon fossil fuels for our energy provisioning, but there are drawbacks to using these fossil fuels: the risk for depletion in the future; the increased cost as already observed during the last few years, and the high impact on climate change. One virtually carbon-neutral alternative to fossil fuels are renewable energy sources, like solar energy. In this paper, we investigate the energy and network performance of a wireless access network powered by the traditional electricity grid and a photovoltaic panel system. An energy-aware management system for the future wireless access networks is proposed. This system consists of the management of the energy provisioning and storage system and the application of the proposed energy-saving strategies which aim to reduce the energy footprint through the traditional grid in case a renewable energy shortage occurs. To evaluate the network's performance, this paper proposes a deployment tool with the above described energy-aware management system. The results show that it is promising to further investigate a more evolved and complex energy-aware management system
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