Article

Delay Aware Resource Management for Grid Energy Savings in Green Cellular Base Stations With Hybrid Power Supplies

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Abstract

Base stations (BSs) equipped with resources to harvest renewable energy are not only environment-friendly but can also reduce the grid energy consumed, thus bringing cost savings for the cellular network operators. Intelligent management of the harvested energy can further increase the cost savings. Such management of energy savings has to be carefully coupled with managing the quality of service so as to ensure customer satisfaction. In such a process, there is a trade-off between the energy drawn from grid and the quality of service. Unlike prior studies which mainly focus on network energy minimization, this paper proposes a framework for jointly managing the grid energy savings and the quality of service (in terms of the network latency) which is achieved by downlink power control and user association reconfiguration. We use a real BS deployment scenario from London, UK to show the performance of our proposed framework and compare it against existing benchmarks. We show that the proposed framework can lead to around 60% grid energy savings as well as better network latency performance than the traditionally used scheme.

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... The authors of [19] developed an energy efficiency optimization framework in a two-tier network with hybrid powered BSs. The authors of [20] considered a dual-powered framework without the flexibility of inter-BS energy transfer; instead, it proposed to procure energy in case the BS become energy deficient. ...
... Further, it is observed from Fig. 5(c) that the prosumer mode results in a CAPEX saving of about 60% over the off-grid mode of operation, and a saving of about 50% over the energy producer mode. The optimal CAPEX considered in the dual-powered without energy sharing (WES) framework of [20] is constant. It can be inferred from Fig. 5(c) that for the balanced homogeneous traffic scenario, the prosumer mode achieves negative CAPEX gain over [20]. ...
... The optimal CAPEX considered in the dual-powered without energy sharing (WES) framework of [20] is constant. It can be inferred from Fig. 5(c) that for the balanced homogeneous traffic scenario, the prosumer mode achieves negative CAPEX gain over [20]. But with increasing traffic inhomogeneity, the prosumer mode offers significant CAPEX saving, achieving up to 100% gain. ...
Article
Full-text available
Designing solar-enabled and power grid connected, 'dual-powered', cellular networks is challenging due to the double stochasticity arising from energy harvest and user traffic, resulting in spatio-temporally varying traffic-energy imbalances. Improper strategy to optimize the power grid connectivity results in generation of significant carbon footprint. In this paper, we present an analytical framework to mathematically capture the traffic-energy imbalances in such a dual-powered network and propose to improve the temporal network energy utilization by exploiting these imbalances through a cooperative energy sharing mechanism among the base stations (BSs), via the grid infrastructure itself. The cooperative communication system is designed and optimized independently from two perspectives, namely, grid energy procurement and carbon emission minimization (in carbon free 'energy producer' mode) and operator revenue maximization (in 'energy prosumer' mode). The energy producer mode involves the BSs, without the flexibility to procure energy and acting as distributed energy source to the power grid. The energy prosumer mode provides additional flexibility of grid energy procurement to the BSs in addition to energy sharing and selling. For a given capital expenditure (CAPEX), both the optimization problems are reformulated into convex quadratic problems and closed form expressions for the optimal quanta of energies to be shared/procured through/from the grid are obtained. The optimal CAPEX for the proposed modes of network operation are obtained via linear revenue maximization problem formulation. The results demonstrate that the proposed cooperative energy framework significantly improves the temporal network energy utilization, thereby reducing the grid energy procurement and providing significant revenue gains compared to the state-of-art.
... Existing literature mostly deals with two kinds of solar powered BSs. One is the off-grid scenario where the BSs solely depend on the harvested solar energy for power [2]. The other is when the BSs harvest solar energy but are supplemented by the grid or diesel generators as a powering backup [3]. ...
... Secondly, the higher the transmit power level, the larger is the number of users inclined towards associating with that BS because such a BS will offer higher data transfer rate to the users. For simplicity, many works like [2] consider discrete power levels with small granularity (5 W), varying from zero to the maximum power level (e.g., 40 W). Taking discrete power levels simplifies the optimization problem of reducing the network latency, because it imposes a finite number of candidate solutions. ...
... This is done to prevent excessive energy consumption during early hours, resulting in power outage and high latency during evening hours when the traffic is at its peak. Intuitively, the green energy allocation is done by keeping it proportional to base station power consumption [2]. ...
Article
Full-text available
There is an increasing need to power cellular base stations (BSs) using solar energy in many parts of the globe. This is primarily because of the high cost of running these base stations on traditional power sources such as diesel due to lack of reliable grid availability in those areas. Apart from the high cost, the increasing diesel consumption also causes harm to the environment due to its increasing global carbon footprint. Using solar energy powered base stations is a highly promising solution to address these issues. One of the main areas of concern for solar powered cellular networks is to precisely manage the resources, namely, the available spectrum and energy so as to avoid power outages and to maintain an acceptable Quality of Service (QoS) for the end users. This article gives an overview of the challenges faced in resource management for solar powered base stations and presents state-of-the-art resource management strategies for both grid-connected and off-grid solar powered base stations.
... [42] Internet Services Study considered prices of green energy, but did not specifically mentioned the type of green energy used. [43] Cellular Netw. & Internet Services, Sec. ...
... Moreover, the operational expenditures (OPEX) for fossil fuel based energy in the telecommunication industry range from 18% to 32% [48], [49]. If multiple RERs are used by the telecommunication service providers to power their BSs then both their OPEX and the CO 2 emissions can be reduced at global level [43], [44]. ...
... Indeed, BSs based on RERs may not be able to support all the traffic and may need to be switched off due to the intermittent nature of RERs. One solution to cope with this situation is to store the renewable energy from RERs and then use it when on-grid energy does not suffice [41], [43], [44]. A detailed discussion on energy-efficient communications and their interaction with the grid is given in [51]. ...
Article
Full-text available
Rising energy costs, losses in the present-day electricity grid, risks from nuclear power generation, and global environmental changes are motivating a transformation of the conventional ways of generating electricity. Globally, there is a desire to rely more on renewable energy resources (RERs) for electricity generation. RERs reduce green house gas emissions and may have economic benefits, e.g., through applying demand side management with dynamic pricing so as to shift loads from fossil fuel-based generators to RERs. The electricity grid is presently evolving towards an intelligent grid, the so-called smart grid (SG). One of the major goals of the future SG is to move towards 100% electricity generation from RERs, i.e., towards a 100% renewable grid. However, the disparate, intermittent, and typically widely geographically distributed nature of RERs complicates the integration of RERs into the SG. Moreover, individual RERs have generally lower capacity than conventional fossil-fuel plants, and these RERs are based on a wide spectrum of different technologies. In this article, we give an overview of recent efforts that aim to integrate RERs into the SG. We outline the integration of RERs into the SG along with their supporting communication networks. We also discuss ongoing projects that seek to integrate RERs into the SG around the globe. Finally, we outline future research directions on integrating RERs into the SG.
... [42] Internet Services Study considered prices of green energy, but did not specifically mentioned the type of green energy used. [43] Cellular Netw. & Internet Services, Sec. ...
... Moreover, the operational expenditures (OPEX) for fossil fuel based energy in the telecommunication industry range from 18% to 32% [48], [49]. If multiple RERs are used by the telecommunication service providers to power their BSs then both their OPEX and the CO 2 emissions can be reduced at global level [43], [44]. ...
... Indeed, BSs based on RERs may not be able to support all the traffic and may need to be switched off due to the intermittent nature of RERs. One solution to cope with this situation is to store the renewable energy from RERs and then use it when on-grid energy does not suffice [41], [43], [44]. A detailed discussion on energy-efficient communications and their interaction with the grid is given in [51]. ...
... As a result, the energy may be transferred to devices having intense communication demands, which strikes a balance between energy flows and data packet flows in the spatial-domain [19]- [23]. Hybrid sources relying on both the renewable energy harvesters and the conventional power grid [24] may also be invoked for the sake of supplying energy for communication infrastructure [25]- [29]. But in order to reduce maintenance costs, we have to minimise the usage of the power grid. ...
... (18) and (19). As a benefit of its flexible implementation, we can approximately tune the power splitter for each eigen-channel in order to maximise the information transmission rate or the amount of energy received by the power splitting scheme, as expressed in the optimisation problem of Eq. (29). By contrast, having diverse time switching factors for each eigen-channel is not quite realistic, since this operation may result in the time domain misalignment of the RF signals components received by the independent eigen-channels. ...
... (20) and (21), respectively. This optimisation problem aims for maximising the achievable data throughput, as interpreted in terms of its objective function (29). The constraint (29a) represents that the received energy should be higher than the threshold P E ,th , while (29b) represents that the sum of the allocated power should not exceed the total available transmit power P t,total . ...
Chapter
In order to realise integrated wireless energy transfer (WET) and wireless information transfer (WIT) , we have to revisit the information theory for finding its performance limits, while redesigning the transceiver architecture in the physical layer for practical implementation. As a result, in this chapter, we impose the energy delivery requirement on the channel output sequence, when maximising the mutual information. The rate-energy tradeoff is studied from the information theoretical perspective for both the discrete-input-discrete-output channel and for the continuous-input-continuous-output channel. Then we provide an overview on the transceiver architecture in the physical layer by considering diverse signal splitters, namely the spatial splitter, the power splitter and the time switcher. The resultant integrated WET and WIT performance is then evaluated for different transceiver architectures.
... As a result, the energy may be transferred to devices having intense communication demands, which strikes a balance between energy flows and data packet flows in the spatial-domain [19]- [23]. Hybrid sources relying on both the renewable energy harvesters and the conventional power grid [24] may also be invoked for the sake of supplying energy for communication infrastructure [25]- [29]. But in order to reduce maintenance costs, we have to minimise the usage of the power grid. ...
... (18) and (19). As a benefit of its flexible implementation, we can approximately tune the power splitter for each eigen-channel in order to maximise the information transmission rate or the amount of energy received by the power splitting scheme, as expressed in the optimisation problem of Eq. (29). By contrast, having diverse time switching factors for each eigen-channel is not quite realistic, since this operation may result in the time domain misalignment of the RF signals components received by the independent eigen- channels. ...
... (20) and (21), respectively. This optimisation problem aims for maximising the achievable data throughput, as interpreted in terms of its objective function (29). The constraint (29a) represents that the received energy should be higher than the threshold P E,th , while (29b) represents that the sum of the allocated power should not exceed the total available transmit power P t,total . ...
Article
In order to satisfy the power thirst of communication devices in the imminent 5G era, wireless charging techniques have attracted much attention both from the academic and industrial communities. Although the inductive coupling and magnetic resonance based charging techniques are indeed capable of supplying energy in a wireless manner, they tend to restrict the freedom of movement. By contrast, RF signals are capable of supplying energy over distances, which are gradually inclining closer to our ultimate goal – charging anytime and anywhere. Furthermore, transmitters capable of emitting RF signals have been widely deployed, such as TV towers, cellular base stations and Wi-Fi access points. This communication infrastructure may indeed be employed also for wireless energy transfer (WET). Therefore, no extra investment in dedicated WET infrastructure is required. However, allowing RF signal based WET may impair the wireless information transfer (WIT) operating in the same spectrum. Hence, it is crucial to coordinate and balance WET and WIT for simultaneous wireless information and power transfer (SWIPT), which evolves to Integrated Data and Energy communication Networks (IDENs). To this end, a ubiquitous IDEN architecture is introduced by summarising its natural heterogeneity and by synthesising a diverse range of integrated WET and WIT scenarios. Then the inherent relationship between WET and WIT is revealed from an information theoretical perspective, which is followed by the critical appraisal of the hardware enabling techniques extracting energy from RF signals. Furthermore, the transceiver design, resource allocation and user scheduling as well as networking aspects are elaborated on. In a nutshell, this treatise can be used as a handbook for researchers and engineers, who are interested in enriching their knowledge base of IDENs and in putting this vision into practice.
... As a result, the energy may be transferred to devices having intense communication demands, which strikes a balance between energy flows and data packet flows in the spatial-domain [19]- [23]. Hybrid sources relying on both the renewable energy harvesters and the conventional power grid [24] may also be invoked for the sake of supplying energy for communication infrastructure [25]- [29]. But in order to reduce maintenance costs, we have to minimise the usage of the power grid. ...
... (18) and (19). As a benefit of its flexible implementation, we can approximately tune the power splitter for each eigen-channel in order to maximise the information transmission rate or the amount of energy received by the power splitting scheme, as expressed in the optimisation problem of Eq. (29). By contrast, having diverse time switching factors for each eigen-channel is not quite realistic, since this operation may result in the time domain misalignment of the RF signals components received by the independent eigen- channels. ...
... (20) and (21), respectively. This optimisation problem aims for maximising the achievable data throughput, as interpreted in terms of its objective function (29). The constraint (29a) represents that the received energy should be higher than the threshold P E,th , while (29b) represents that the sum of the allocated power should not exceed the total available transmit power P t,total . ...
Preprint
In order to satisfy the power thirsty of communication devices in the imminent 5G era, wireless charging techniques have attracted much attention both from the academic and industrial communities. Although the inductive coupling and magnetic resonance based charging techniques are indeed capable of supplying energy in a wireless manner, they tend to restrict the freedom of movement. By contrast, RF signals are capable of supplying energy over distances, which are gradually inclining closer to our ultimate goal-charging anytime and anywhere. Furthermore, transmitters capable of emitting RF signals have been widely deployed, such as TV towers, cellular base stations and Wi-Fi access points. This communication infrastructure may indeed be employed also for wireless energy transfer (WET). Therefore, no extra investment in dedicated WET infrastructure is required. However, allowing RF signal based WET may impair the wireless information transfer (WIT) operating in the same spectrum. Hence, it is crucial to coordinate and balance WET and WIT for simultaneous wireless information and power transfer (SWIPT), which evolves to Integrated Data and Energy communication Networks (IDENs). To this end, a ubiquitous IDEN architecture is introduced by summarising its natural heterogeneity and by synthesising a diverse range of integrated WET and WIT scenarios. Then the inherent relationship between WET and WIT is revealed from an information theoretical perspective, which is followed by the critical appraisal of the hardware enabling techniques extracting energy from RF signals. Furthermore, the transceiver design, resource allocation and user scheduling as well as networking aspects are elaborated on. In a nutshell, this treatise can be used as a handbook for researchers and engineers, who are interested in enriching their knowledge base of IDENs and in putting this vision into practice. Index Terms-RF signals, wireless energy transfer (WET), wireless information transfer (WIT), simultaneous wireless information and power transfer (SWIPT), wireless powered communication networks (WPCNs), integrated data and energy communication networks (IDENs).
... As a result, the energy may be transferred to devices having intense communication demands, which strikes a balance between energy flows and data packet flows in the spatial-domain [19]- [23]. Hybrid sources relying on both the renewable energy harvesters and the conventional power grid [24] may also be invoked for the sake of supplying energy for communication infrastructure [25]- [29]. But in order to reduce maintenance costs, we have to minimise the usage of the power grid. ...
... (18) and (19). As a benefit of its flexible implementation, we can approximately tune the power splitter for each eigen-channel in order to maximise the information transmission rate or the amount of energy received by the power splitting scheme, as expressed in the optimisation problem of Eq. (29). By contrast, having diverse time switching factors for each eigen-channel is not quite realistic, since this operation may result in the time domain misalignment of the RF signals components received by the independent eigenchannels. ...
... (20) and (21), respectively. This optimisation problem aims for maximising the achievable data throughput, as interpreted in terms of its objective function (29). The constraint (29a) represents that the received energy should be higher than the threshold P E,th , while (29b) represents that the sum of the allocated power should not exceed the total available transmit power P t,total . ...
Article
In order to satisfy the power thirsty of communication devices in the imminent 5G era, wireless charging techniques have attracted much attention both from the academic and industrial communities. Although the inductive coupling and magnetic resonance based charging techniques are indeed capable of supplying energy in a wireless manner, they tend to restrict the freedom of movement. By contrast, RF signals are capable of supplying energy over distances, which are gradually inclining closer to our ultimate goal – charging anytime and anywhere. Furthermore, transmitters capable of emitting RF signals have been widely deployed, such as TV towers, cellular base stations and Wi-Fi access points. This communication infrastructure may indeed be employed also for wireless energy transfer (WET). Therefore, no extra investment in dedicated WET infrastructure is required. However, allowing RF signal based WET may impair the wireless information transfer (WIT) operating in the same spectrum. Hence, it is crucial to coordinate and balance WET and WIT for simultaneous wireless information and power transfer (SWIPT), which evolves to Integrated Data and Energy communication Networks (IDENs). To this end, a ubiquitous IDEN architecture is introduced by summarising its natural heterogeneity and by synthesising a diverse range of integrated WET and WIT scenarios. Then the inherent relationship between WET and WIT is revealed from an information theoretical perspective, which is followed by the critical appraisal of the hardware enabling techniques extracting energy from RF signals. Furthermore, the transceiver design, resource allocation and user scheduling as well as networking aspects are elaborated on. In a nutshell, this treatise can be used as a handbook for researchers and engineers, who are interested in enriching their knowledge base of IDENs and in putting this vision into practice.
... The tradeoff between energy savings and QoS in HetNets powered by both grid power and RE has been studied in [139,140]. In [139], the authors considered optimal user association to reduce the on-grid power consumption, while respecting the traffic delivery latency. ...
... In this regard, a user association algorithm is proposed that takes into account the BS traffic load and harvested energy in order to make user association decisions. In [140], the authors extended the previous work to include BS power control as well. Since the problem of power control is non-convex, a greedy heuristic algorithm is proposed to achieve power control operations. ...
... The idea is to optimize the use of RE in order to achieve the required objective(s), e.g., reduce the on-grid energy consumption and minimize the electric bill of the network operator. There exist several studies that aim at achieving these goals in a green cellular network powered by RE, batteries and the SG [142,177,138,140,43]. For instance, the authors in [142,177] studied the problem of minimizing the on-grid energy consumption of green cellular networks. ...
Thesis
Full-text available
We live in the digital era where the Internet has become an essential part of our daily lives. With more than 750 million connected households and over 6.8 billion mobile subscribers, mobile networks are dominating the Information and Communication Technology (ICT) sector with more than 75%. The trend is of further increase and appears to have no signs of slowing down in the near future due to the ongoing new services and applications. However, this radical surge of ICT devices and services has pushed corresponding energy consumption and its footprint on the environment to grow at a staggering rate consuming more than 5% of the world’s electrical energy and releasing into the atmosphere about 2% of the global CO2 emissions. Since base stations, the core elements to provide internet access, consume most of the energy in cellular networks, it is essential to study new strategies and architectures in order to deter this energy crunch. This thesis focuses on the crucial role of energy in the design and operation of future cellular networks. We consider different and complementary approaches and parameters, including energy efficiency techniques (i.e., radio resource management and sleep schemes), renewable energy sources, Smart Grid and tools from machine learning to bring down the energy consumption of these complex networks while guaranteeing a certain quality of service adapted to 5G use cases.
... In [7], [8], the authors consider a heterogeneous network, where hybrid powered small cells are considered to guarantee user QoS with minimum on-grid power consumption. The additional on-off mechanism and channel assignment are introduced in [9], [10]. Furthermore, during the peak hour, more power will be consumed to serve more users with excessive data demands. ...
... Moreover, the power consumption of user equipment (UE) Objective Restriction [3] Green Data Throughput - [4] Hybrid Data Partial SCs Throughput On-Off SCs [5] Hybrid -Power Predict Offline Data [6] Hybrid Data Throughput Offline Data [7], [8] Hybrid Data Consumed Power - [9], [10] Hybrid Data Consumed Power - [11] Hybrid Data Consumed Power Offline Data [13]- [15] On-Grid Power Throughput Extra Devices [16], [17] On-Grid SWIPT Throughput - [18], [19] On-Grid SWIPT Throughput - [20]- [22] On-Grid SWIPT Consumed Power - [23], [24] On-Grid SWIPT EE - [25]- [27] On-Grid SWIPT Throughput -Our Work Hybrid SWIPT EE is another crucial problem, which should also be taken into account. To prolong the battery lifetime of UEs, wireless power transfer technique is developed as a promising solution [13], where UEs are capable of performing wireless power charging from received signals. ...
... The wireless charging and hybrid power resource allocation in problem (10) have been jointly solved to obtain global optimum solutions in the previous section. However, the original optimization problem adopts approximation and Lagrangian process within SCs, which leads to high computational complexity. ...
Article
Full-text available
In this paper, we consider a simultaneous wireless information and hybrid power transfer system for cellular green networks. The small cells (SCs) use hybrid power of on-grid power and green energy harvested from environments, whilst the user equipments (UEs) are enabled by a power-splitting receiver. A quality-of-service (QoS) constrained problem is designed to maximize energy efficiency (EE) considering joint strategies of hybrid power allocation, resource block assignment, and power splitting ratio adjustment. We propose a joint wireless charging and hybrid power based resource allocation (J-WHA) algorithm by transforming the non-concave EE problem into a solvable one based on proved concavity property and Karush-Kuhn-Tucker (KKT) conditions. Moreover, a separated wireless charging and hybrid power based resource allocation (S-WHA) algorithm is proposed to obtain sub-optimal solutions with lower computational complexity. Simulation results demonstrate the convergence of both proposed algorithms in relation to transmission power utilization, wireless charging amount, and system EE. It is shown that the proposed J-WHA and S-WHA algorithms outperform existing schemes in terms of EE performance.
... Then, the traffic load of a BS can be obtained by integrating the average traffic load density of users who are served by the BS. With it, the works in [41], [44] defined the network latency as a quality of service (QoS) metric whereas the studies in [39], [42], [45] introduced the average waiting delays of the users. ...
... Even though RE is potentially infinite, its limited availability results in uncertainty about the timing and quantity of energy collected. Thus, BSs are required to be equipped with a reliable Stand-alone with energy storage [14], [23], [25], [31], [34], [50], [56]- [77] On-grid without energy storage [38], [40], [42]- [44], [78]- [87] On-grid with energy storage [36], [37], [41], [45], [47], [60] [71], [72], [88]- [108] energy source, such as a power grid or energy storage system, to provide uninterrupted service for users. In this context, RE-powered BS can be classified according to whether it is connected to a grid (on-grid) or not (stand-alone) and whether it has an energy storage system or not, as depicted in Fig. 5. BS can be either connected to a grid so that it can operate without an outage, or it can be operated solely by RE. ...
... Minimizing the network latency [39], [85] [57], [58] Maximizing the weighted sum of on-grid consumption and user QoS metric [40] [40], [41] [42]- [44] [86], [87], [108] [41], [108] Maximizing the utilization of RE [104] [82], [104] Maximizing the energy efficiency [96], [105] [47], [105] Minimizing the cost of using conventional energy source [106] [83], [93] [36], [37], [91] [65] ...
Preprint
div> Renewable energy (RE)-powered base stations (BSs) have been considered as an attractive solution to address the exponential increasing energy demand in cellular networks while decreasing carbon dioxide (CO2) emissions. For the regions where reliable power grids are insufficient and infeasible to deploy, such as aerial platforms and harsh environments, RE has been an alternative power source for BSs. In this survey paper, we provide an overview of RE-enabled cellular networks, detailing their analysis, classification, and related works. First, we introduce the key components of RE-powered BSs along with their frequently adopted models. Second, we analyze the proposed strategies and design issues for RE-powered BSs that can be incorporated into cellular networks and categorize them into several groups to provide a good grasp. Third, we introduce feasibility studies on RE-powered BSs based on the recent literature. Fourth, we investigate RE-powered network components other than terrestrial BSs to address potential issues regarding RE-enabled networks. Finally, we suggest future research directions and conclusions. </div
... RELATED WORK One of the significant factors in enabling the efficient energy operations of green cellular base stations is controlled optimization of resource provisioning with latency aware operations. Studies in [11] have proposed a down-link power controlled optimization framework for delay aware energyefficient green cellular operations, whereas [12] proposed multi-operator based cooperative mechanisms for efficient green networks. In recent times, there has been significant research on the use of energy-efficient green communication systems to cater to the needs of diverse application scenarios ranging from edge computing to cloud computing, and from centralized architectures to decentralized architectures. ...
... Summing the expressions in Eq. (12) and Eq. (13) we can observe that the final time propagation delay of broadcasting is N(N-1)T avg , same as in Eq. (10) However, from Eq. (11) and Eq. (14), the number of node-to-node connections needed for the proposed ring based computed data distribution method was reduced by a factor of N −1 2 , when compared with all-toall node broadcast method. ...
Article
Full-text available
Optimal resource provisioning and management of the next generation communication networks are crucial for attaining a seamless Quality of Service with reduced environmental impact. Considering the ecological assessment, urban and rural telecommunication infrastructure is moving towards deploying green cellular base stations to cater to the needs of the ever-growing traffic demands of heterogeneous networks. In such scenarios , the existing learning-based renewable resource provision-ing methods lack intelligent and optimal resource management at the Small Cell Base Stations (SCBS). Therefore, in this article, we present a novel machine learning-based framework for intelligent resource provisioning mechanisms for micro-grid connected green SCBSs with a completely modified ring parametric distribution method. In addition, an algorithmic implementation is proposed for prediction-based renewable resource redistribution with Energy Flow Control Unit (EFCU) mechanism for grid-connected SCBS, eliminating the need for centralised hardware. Moreover, this modeling enables the prediction mechanism to estimate the future on-demand traffic provisioning capability of SCBS. Furthermore, we present the numerical analysis of the proposed framework showcasing the systems' ability to attain a balanced energy convergence level of all the SCBS at the end of the periodic cycle, signifying our model's merits.
... The idea is to optimize the use of RE in order to achieve the required objective(s), e.g., reduce the on-grid energy consumption and minimize the electric bill of the operator. In [10], [11], the authors focus on the grid energy consumption of a homogeneous cellular network powered by a mixed power supply from power grid and RE. The authors in [10] study the weighted-sum problem of grid-power consumption and blocking probability. ...
... The aim is to optimize the state of the BSs (ON and OFF) and the number of active resource blocks to guarantee a certain Quality of Service (QoS) while minimizing the energy consumption. In [11], the trade-off between the grid energy and the network latency is studied. The joint management of energy savings and QoS is achieved by downlink power control and user association reconfiguration. ...
Article
The increase of energy demand in cellular networks imposes big economic and ecological challenges. Answering to these challenges requires complex energy frameworks that consider Smart Grid, renewable energy, battery systems and employs efficient management of radio as well as energy resources. In this context, lithium batteries present very good performance indicators (e.g., high energy density, large service life and environmental friendliness) but can also have very poor use duration when the energy management system is not suitable. This is linked to the important consequences of radio resource allocation on energy consumption and operational cost. In this paper, we study and propose energy and radio allocation mechanisms for cellular networks supplied with hybrid energy sources (grid and renewable).We propose a Battery Aging and Price-Aware (BAPA) algorithm that brings down the grid energy consumption of the operator while including battery degradation constraints. We decompose the problem into three subproblems: radio resource allocation problem, grid energy purchase problem and power allocation problem. We show that our algorithm performs very close to the optimal solution and outperforms a benchmark algorithm, allowing more efficient battery use, energy savings and network operation cost reduction with no impact on the QoS of users. Finally, we provide some insights into how the advancement in base station technology will help reducing the investment cost in future cellular networks.
... Then, we calculate the power allocation and RB assignment based on Eqs. (26) and (30). Next, Lagrange multipliers are updated according to Eqs. (31) and (32). ...
... Let {A * , P * } be the RB assignment and power allocation obtained derived based on Eqs. (30) and (26), respectively. Since f (A, P) is convex with respect to P, P * is derived based on the Karush-Kuhn-Tucker (KKT) condition [16]. ...
Article
Heterogeneous cloud radio access network (H-CRAN) promises higher energy efficiency (EE) than the conventional cellular networks by centralizing the baseband signal processing into the baseband unit (BBU) pool hosted by cloud computing platforms. Because of the difference between H-CRAN and conventional cellular networks, existing energy-efficient networking mechanisms designed for conventional cellular networks cannot fully leverage H-CRAN in terms of reducing the network energy consumption. In this paper, we bridge this gap by proposing a radio resource management scheme to optimize the network energy efficiency (NEE) of H-CRAN. We develop a network energy consumption model that characterizes the energy consumption of radio access points (RAPs), fronthaul, and the BBU pool in H-CRAN. Based on the network energy consumption model, we formulate the NEE optimization problem with the consideration of the capacity constrained fronthaul. The NEE optimization problem is a mixed integer non-linear programming problem (MINLP). We propose the H-CRAN energy-efficient radio resource management (HERM) algorithm to solve the NEE optimization problem efficiently. Various properties of the proposed solution are derived and extensive simulations are conducted. The simulation results show that the HERM algorithm significantly improves the NEE of H-CRAN. As compared with a baseline algorithm in which the radio resource management is not optimized, HERM boosts the NEE by 59% under the dynamic network traffic. As compared to an energy-efficient radio resource allocation (ERA) algorithm which does not optimize the energy consumption of the BBU pool, the NEE of H-CRAN achieved by the HERM algorithm is up to 51% better than that by the ERA algorithm with network traffic dynamics.
... The objective of minimizing the electric bill of a cellular network operator was investigated in [9], [10], [11]. In [9], we studied RE allocation, energy consumption minimization, and radio resource allocation to minimize the electric bill of a cellular network powered by both RE and power grid, in a variable electricity price environment. ...
... In [9], we studied RE allocation, energy consumption minimization, and radio resource allocation to minimize the electric bill of a cellular network powered by both RE and power grid, in a variable electricity price environment. In [10], the authors presented intelligent green energy allocation, user association, and downlink power control to increase the cost savings of cellular network operators taking into account, the network's delay. In [11], based on stochastic dynamic programming, the authors studied BS switch-off to reduce the total on-grid energy cost in a large-scale green cellular network. ...
Conference Paper
Wireless networks have important energy needs. Many benefits are expected when the base stations, the fundamental part of this energy consumption, are equipped with renewable energy (RE) systems. Important research efforts have been done to enhance the utilization of RE. However, to the best of our knowledge, these efforts did not take into consideration partially RE-equipped systems. The latter is of great importance considering the high cost of these systems and the feasibility of implementing RE systems at all base station sites. Thus, it is interesting to study the percentage of sites to be equipped with RE systems. In this work, we analyze the energy and cost savings for a defined energy management strategy of a RE hybrid system. Our study of the relationship between cost savings and percentage of sites equipped with RE show significant results. For example, our simulation shows that a cost gain of 60% is realized when 30% of the base stations are equipped with solar panels that harvest only 35% of the total network energy demand at full load. Results also show an upper limit for the battery capacity at which the cost gain is maximized.
... However, in cache-enabled DSCNs, the joint file delivery delay and power consumption optimization (JDPO) problem is non-trivial. In traditional DSCNs, the JDPO problem can be solved by jointly power control and user association, whose difficulty largely stems from the coupling relationship caused by inte-cell interference [15]- [17]. With caching capabilities at SBSs, file placement will be an additional flexible variable to the JDPO problem. ...
Preprint
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Enabling caching capabilities in dense small cell networks (DSCNs) has a direct impact on file delivery delay and power consumption. Most existing work studied these two performance metrics separately in cache-enabled DSCNs. However, file delivery delay and power consumption are coupled with each other and cannot be minimized simultaneously. In this paper, we investigate the optimal tradoff between these two performance metrics. Firstly, we formulate the joint file delivery delay and power consumption optimization (JDPO) problem where power control, user association and file placement are jointly considered. Then we convert it to a form that can be handled by Generalized Benders Decomposition (GDB). with GDB, we decompose the converted JDPO problem into two smaller problems, i.e., primal problem related to power control and master problem related to user association and file placement. An iterative algorithm is proposed and proved to be $\epsilon$-optimal, in which the primal problem and master problem are solved iteratively to approach the optimal solution. To further reduce the complexity of the master problem, an accelerated algorithm based on semi-definite relaxation is proposed. Finally, the simulation results demonstrate that the proposed algorithm can approach the optimal tradeoff between file delivery delay and power consumption.
... For example, the delay-aware downlink control has been investigated in [24], [25]. In this paper, however, we shall consider the resource allocation in the time scale of file segment transmission, which consists of thousands of frames. ...
Article
In this paper, downlink delivery of popular content is optimized with the assistance of wireless cache nodes. Specifically, the requests of one file is modeled as a Poisson point process with finite lifetime, and two downlink transmission modes are considered: (1) the base station multicasts file segments to the requesting users and selected cache nodes; (2) the base station proactively multicasts file segments to the selected cache nodes without requests from users. Hence the cache nodes with decoded files can help to offload the traffic upon the next file request via other air interfaces, e.g. WiFi. Without proactive caching placement, we formulate the downlink traffic offloading as a Markov decision process with random number of stages, and propose a revised Bellman's equation to obtain the optimal control policy. In order to address the prohibitively huge state space, we also introduce a low-complexity sub-optimal solution based on linear approximation of the value functions, where the gap between the approximated value functions and the real ones is bounded analytically. The approximated value functions can be calculated from analytical expressions given the spatial distribution of requesting users. Moreover, we propose a learning-based algorithm to evaluate the approximated value functions for unknown distribution of requesting users. Finally, a proactive caching placement algorithm is introduced to exploit the temporal diversity of shadowing effect. It is shown by simulation that the proposed low-complexity algorithm based on approximated value functions can significantly reduce the resource consumption at the base station, and the proactive caching placement can further improve the performance.
... The base station is equipped with AC power and it is also assumed that a backup energy source is available in case of power failure. The power and backup management are out of the scope of this research, but many researchers already solved this problem [51]. The base stations are heterogeneous in nature and have different storage and computation power. ...
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Unmanned aerial vehicles (UAVs) play an important role in facilitating data collection in remote areas due to their remote mobility. The collected data require processing close to the end-user to support delay-sensitive applications. In this paper, we proposed a data collection scheme and scheduling framework for smart farms. We categorized the proposed model into two phases: data collection and data scheduling. In the data collection phase, the IoT sensors are deployed randomly to form a cluster based on their RSSI. The UAV calculates an optimum trajectory in order to gather data from all clusters. The UAV offloads the data to the nearest base station. In the second phase, the BS finds the optimally available fog node based on efficiency, response rate, and availability to send workload for processing. The proposed framework is implemented in OMNeT++ and compared with existing work in terms of energy and network delay.
... However, the random energy arrivals may cause some instability of the service, so some hybrid energy schemes are proposed, where EH cooperates with the conventional power grid to maintain the service [20,21]. In this paper, we consider a relay system where the source, referring to the base station (BS) most of the time, is powered by the conventional power grid to guarantee a cell-wide coverage [22,23] and the relay is powered by EH to cooperate with the source on the communication with the destination. ...
... However, the integrated approach is complex to implement as it involves wireless rerouting also along with energy saving scheme at the wireless and optical end. In [38] the author used the grid power supply when there is a limited solar power at the base station to operate. As the evidence from the this paper, the renewable energy power utilization has been studied as separate issue for optical and wireless networks. ...
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Hybrid networks have recently received a lot of attention as a means to address some of the issues that standard access networks face. The hybrid network formed by connecting back-end network with an optical fiber network, and the front-end with a wireless network. Hybrid network combines the advantages of wireless networks, including higher flexibility, universality connectivity, and cost-effectiveness with the high bandwidth passive optical networks. However, the integrated approach is consumes lots of non renewable energy, to cater to the end-users. A huge amount of non-renewable energy is consumed to cater to a large geographical area. In order to minimize the energy consumption renewable energy resource are replaced with the renewable energy resources. The use of renewable resources has been researched separately for optical and wireless networks. In order to minimize the traditional fossil energy consumption for Hybrid networks, we have proposed renewable energy-aware traffic grooming algorithms for hybrid networks. In our work, each network node is capable of producing renewable energy in a decentralized way. Here brown energy is used as reserve energy since renewable energy sources are climate dependent. Our algorithms efficiently utilize the renewable energy available at the nodes to route the network traffic demands. Further, we have provided the optimized content placement algorithm for virtual machine in order to minimize the energy consumption and to meet the service level agreement at the data centers.
... As a result, it was observed by the authors that 76-89% of energy could be saved using this algorithm. Authors in [99] proposed a QoS assured, GR-RAM scheme that manages to reduce the grid energy consumption by using the renewable resource of energy. The proposed scheme minimized grid energy consumption up to 60% and improved network latency by intelligently allocating green energy. ...
Article
Rapid advancement in ICT is promoting us into an era of unprecedented prosperity & countless possibilities. However, there is one gloomy side of the ICT technology that contributes toward the inflation of carbon footprint. Research from 2020, estimates the ICT sector, carbon emission, to be 1,100 million tons. The future generation networks and IoT will further escalate this figure, as these would overburden the core ICT pillars i.e. Data Centers (DC's), and Mobile networks (NT). This in turn will inflate the ICT power consumption and leads to more carbon emission. Thus researchers and industries are continuously putting efforts to transform ICT into Green ICT. Apart from this, there is one bright side of ICT i.e. “Green BY ICT” that helps other industries to abate their carbon emission using smart IoT applications. However, the smart IoT devices/sensors/actuators used for this are mostly battery-operated. To reduce the battery waste, efforts are also being made to either prolong their battery life or to make them self-powered or battery-free. This survey discusses both aspects of ICT i.e. Green of ICT and Green by ICT. Firstly, the recent approaches for the Greening of ICT include techniques for Green-DC, Green-NT are discussed. Post discussing this, the paper also confers the energy harvesting solutions & energy-efficient techniques for the greening of user device/senor/. In continuation of this, 5G green physical layer solution, Narrowband Internet of Things (NB-IoT) that prolongs battery life is also discussed, including its enhancement from release 13 to release 16, recent techniques to further optimize the NB-IoT performance, and future research challenges. Overall this survey concludes that ICT's own environmental impact must be evaded, to utilize the ICT's tremendous potential.
... Albeit the considerable amount of energy saving attained by the above solutions, but they overlook tempo-spatial variation of renewable energy availability and traffic arrival distribution. To address the research gap, Chamola et al. [55] proposed a grid energy saving reduction method guided by the temporal allocation of renewable energy and power control load balancing scheme. On the other hand, a Lyapunov optimization based low-complexity online policy is suggested in [57] to curtail average network cost incorporating an energy delay trade-off load balancing algorithm. ...
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... With this energy allocation in place, this paper presents a comprehensive framework for the operation of an off-grid BS, guiding the energy allocation, power control, as well as user-association which has been missing in existing literature. Note that although [25] uses green energy and delay aware BS power control and user association reconfiguration, the problem scenario and formulation are quite different from the ones addressed in this paper. It considers the scenario where the BSs are connected to the grid and the challenge is to manage the trade-off between grid energy savings and the QoS. ...
Article
Cellular base stations (BSs) powered by renewable energy like solar power have emerged as a promising solution to address the issues of reducing the carbon footprint of the telecom industry as well as the operational cost associated with powering the BSs. This paper considers a network of off-grid solar powered BSs and addresses two key challenges while operating them (a) avoiding energy outages and (b) ensuring reliable quality of service (in terms of the network latency). In order to do so, the problem of minimizing the network latency given the constrained energy availability at the BSs is formulated. Unlike existing literature which have addressed this problem using user-association reconfiguration or BS on/off strategies, we address the problem by proposing an intelligent algorithm for allocating the harvested green energy over time, and green energy and delay aware downlink power control and user association. Using a real BS deployment scenario, we show the efficacy of our methodology and demonstrate its superior performance compared to existing benchmarks.
... Hence, by exploring joint frequency allocation, link scheduling, routing, and transmission power control, energy consumption has been minimized [4]. Some other researchers introduced an energy-efficient resource allocation in cellular networks with OFDMA; while enabling a certain level of QoS [5], [6]. Multiple input multiple output (MIMO) techniques, channel coding and etc. have been studied with the aim of improving energy efficiency [7]- [9]. ...
... In the proposed system model, we consider a network that comprises of multiple SPBSs and smart grids. In the proposed model, each SPBS and grid alike, will act as both a producer and a consumer, i.e., as a prosumer [4], [6]. The user functions as a customer when the amount of energy it requires exceeds the amount of energy it generates. ...
Conference Paper
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The rapidly increasing mobile traffic across the globe has proliferated the deployment of cellular base stations, which has, in turn, led to an increase in the power consumption and carbon footprint of the telecommunications industry. In recent times, solar-powered base stations (SPBSs) have gained much popularity in the telecom sector due to their ability to make operations more sustainable. However, some potential energy benefits rendered by the SPBSs have not yet been realized. In areas with dense base station deployment or low mobile traffic, SPBSs store surplus energy, which, in most instances, gets lost due to limited charge storage capacity of the batteries. To limit the wastage of energy, an appropriate mechanism enabling the utilization of excess energy produced by these base stations can be adopted. To this end, we model a Base Station-to-Grid (BS2G) network in which the grid can utilize surplus energy spared by the SPBSs. To overcome challenges in regards to scalability, ro-bustness, and cost-optimization, we propose using the blockchain technology to create the BS2G network. Blockchain is a distributed ledger designed to record transactions in a transparent, lightweight, and tamper-proof manner. To make energy trade between base stations and the grid cost-effective, a game-theoretical approach has also been adopted in this paper. The proposed model simplifies the process of energy trading while also making it cost-optimal.
... Cell ranging and expansion of base stations were managed by switching ON all stations, in turn, focussing on the load balancing. Termed to be Cell Range Expansion Algorithms (Asheralieva 2017;Han and Ansari 2016;Chamola et al. 2017), the algorithms deemed that user association with respective base stations, reducing the traffic flow by reduction of transmission range and distributing load were of significance. ...
Article
Heterogeneous networks are prominent and promising architectures for extended usage and real time communication processes. The placement of small cell Base stations the densely populated to increase the services offered to multiple users simultaneously and hence constitute heterogeneous networks. Energy requirements computation of HetNets is challenged by continuous demand, leading to be deployment of substantial energy harvesting mechanisms. Energy utilization and resource allocation determine the performance of heterogeneous networks, apart from user scheduling and implementing hybrid energy sources. This research article contemplates a model of users scheduling and a load balancing resource allocation scheme, in turn improving the energy efficiency of overall network. The properties of wireless channel communications and environmental conditions are un-predicted and stochastic in nature, reinforcement learning technique is implemented to update the optimal performance in every iteration. Identified problem in our proposal is to acknowledge the continuous valued actions and States of a hybrid model, which is approached by a user-demand deterministic algorithm. The users are derived based on Gaussian distribution, and defining their demands in a continuous state as actions. A gradient ascent methodology is implied to derive every attribute with respect to stochastic actions identified from continuous States. Function approximation analyses the performance of load distribution and resource allocation according to the demands of users. The proposed model is evaluated with simulations to acknowledge the performance of HetNets in terms of improvised energy utilization, optimized users scheduling and conservation of energy through deploying green energy.
... The performance of an EH system also depends on how efficiently it utilizes the harvested energy available [158], Minimizing the weighted sum of the outage probabilities Rayleigh fading channel with finite and infinite cell capacity ...
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Energy harvesting (EH) and spectrum harvesting (SH) are two promising and useful green communication and networking mechanisms for the next-generation wireless networks. While the former techniques exploit ambient energy sources to scavenge energy, the latter exploit the unused or moderately used electromagnetic spectrum. With the advent of cyber-physical systems and the Internet-of-Things (IoT), the presence of tens of billions of low power sensor devices would soon be a reality. These small sensing devices would be present in many systems around us, such as home appliances, telecommunication devices, medical electronics, transport systems, etc. These miniaturized, low-power consuming devices may exploit EH and SH techniques for energy storage and communication. These EH-SH-enabled sensors or low-power nodes need to consume very little energy for sensing and communicating opportunistically. However, several theoretical problems and practical challenges exist in EH-SH communications. In this comprehensive survey paper, we first present the historical background of EH, and SH techniques, and their development over several decades. Specifically, we focus on EH-SH communication technologies and protocols for a wide range of systems and networks. We present a detailed survey of the various harvesting techniques and protocols from recent literature. Finally, we describe exciting open, intra-disciplinary, and inter-disciplinary challenges for further research on EH-SH communication technologies.
... W ITH the growing popularity of smart devices and the increasing traffic demands, developing more infrastructure nodes in the serving area is needed to improve the network coverage and to boost the capacity of existing cellular networks [2]- [4]. Heterogeneous networks (HetNets), which have been introduced to support high capacity requirements and to improve Quality of Service (QoS), are composed of This paper was presented in part at the 2018 IEEE Wireless Communications and Networking Conference (WCNC) [1] Chengcheng Zhou, Haitao Xu macro cells covered with small cells [5], [6]. ...
Preprint
Heterogeneous networks have been utilized in the next generation networks to meet the increasing traffic demands. To optimally allocate the transmit power and effectively manage the interference between the macro base stations (MBS) and small cell base stations (SBSs), we design an innovative Stackelberg differential game approach, where MBS is the game leader and SBSs are the followers. In the proposed Stackelberg game, according to the interference price controlled by the MBS, the SBSs control the transmit power to minimize the cost during information transmission, and to control the co-channel interference with the MBS. Meanwhile, the SBSs in the researched heterogeneous network are assumed powered by renewable energy resources, in which energy storage state can be formulated using differential equations. Based on the energy state's PDE dynamic characteristics, differential game is also introduced into our proposed game framework to obtain dynamic strategies for SBSs to control their transmit power. The MBS can also makes optimal decision on the interference price to minimize its cost using the proposed differential game. The open-loop Nash equilibrium and feedback Nash equilibrium are both researched in our proposed game framework. Under the open loop pattern, the Nash equilibrium of SBSs and MBS would be effected by the time and system state. Under the feedback pattern, we extend the time horizon to the infinite time horizon and discuss the differences between non-cooperative solutions and cooperative solutions. Numerical results are given to show the effectiveness of the proposed power control and interference pricing approach.
... Specifically, the authors proposed an algorithm where the base stations (BSs) cooperatively adjust their sleeping/nonsleeping state based on the actual traffic load and solar energy state. In [18], a scenario is considered wherein a backup supply or grid supply is always available to the BS. Hence, the BS can utilize the grid power supply whenever there is an outage of solar power. ...
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The ever increasing demand for higher data rates and more flexible deployment has accelerated the need for integrating optical fiber with wireless networks. Fiber-wireless (FiWi) network consists of a fiber back-end network integrated with a wireless front-end. With the growing popularity of the FiWi network, it is essential to look into energy conservation mechanisms as well. One such energy conservation mechanism is to employ a renewable source of energy, such as solar energy. In this paper, we have analysed an integrated FiWi network composed of a 10-Gigabit-capable passive optical network (XG-PON) with a WiFi front end. It is assumed that solar panels are installed at the optical network units (ONUs). Depending on the availability of solar power as well as the load generated due to data traffic at ONU, the requirement of resources to power the ONU varies. Consequently, we propose a) Battery allocation (BA) algorithm and b) Photovoltaic (PV) panel allocation (PA) algorithm, for both off-grid as well as on-grid scenarios. To analyse the cost-effectiveness of the proposed algorithms, battery lifetime has also been calculated. Through the obtained results, it has been demonstrated that for locations with good solar profile, there can be a significant reduction in the number of batteries as well as PV panels required to operate a FiWi network.
... In [8], the authors studied the tradeoff between energy savings and delay for different wake-up schemes. Similarly, in [9] this tradeoff is studied in a renewable energy environment where the BSs switch to sleep mode in a cooperative manner to further reduce the grid energy consumption. ...
Conference Paper
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In this paper, we propose a sleep strategy for energy-efficient 5G Base Stations (BSs) with multiple Sleep Mode (SM) levels to bring down energy consumption. Such management of energy savings is coupled with managing the Quality of Service (QoS) resulting from waking up sleeping BSs. As a result, a tradeoff exists between energy savings and delay. Unlike prior work that studies this problem for binary state BS (ON and OFF), this work focuses on multi-level SM environment, where the BS can switch to several SM levels. We propose a Q-Learning algorithm that controls the state of the BS depending on the geographical location and moving velocity of neighboring users in order to learn the best policy that maximizes the tradeoff between energy savings and delay. We evaluate the performance of our proposed algorithm with an online suboptimal algorithm that we introduce as well. Results show that the Q-Learning algorithm performs better with energy savings up to 92% as well as better delay performance than the heuristic scheme.
... In the proposed system model, we consider a network that comprises of multiple SPBSs and smart grids. In the proposed model, each SPBS and grid alike, will act as both a producer and a consumer, i.e., as a prosumer [4], [6]. The user functions as a customer when the amount of energy it requires exceeds the amount of energy it generates. ...
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In this paper, we study sustainable resource allocation for cloud radio access networks (CRANs) powered by hybrid energy supplies (HES). Specifically, the central unit (CU) in the CRANs distributes data to a set of radio units (RUs) powered by both on-grid energy and energy harvested from green sources, and allocates channels to the selected RUs for downlink transmissions. We formulate an optimization problem to maximize the net gain of the system which is the difference between the user utility gain and on-grid energy costs, taking into consideration the stochastic nature of energy harvesting process, time-varying on-grid energy price, and dynamic wireless channel conditions. A resource allocation framework is developed to decompose the formulated problem into three subproblems, i.e., the hybrid energy management, data requesting, and channel and power allocation. Based on the solutions of the subproblems, we propose a net gain-optimal resource allocation (GRA) algorithm to maximize the net gain while stabilizing the data buffers and ensuring the sustainability of batteries. Performance analysis demonstrates that the GRA algorithm can achieve close-to-optimal net gain with bounded data buffer and battery capacity. Extensive simulations validate the analysis and demonstrate that GRA algorithm outperforms other algorithms in terms of the net gain and delay performance.
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With the emergence of smart grids, adopting dynamic energy pricing models have become both possible and desirable. With such a pricing dynamicity, great savings in energy costs can be achieved in telecommunication systems when energy is procured efficiently through carefully designed real-time resource schedulers. Broadly speaking, existing scheduling algorithms can be categorized into two classes: online and offline. Offline algorithms are not practical merely because of their need for prior knowledge of future system information. In this work, we propose an efficient online power procurement and allocation scheduler that maximizes a long-term system utility function without the need for prior knowledge of future system information, where the system utility function is expressed in such a way that the gain coming from serving the users and the cost of the procured energy are traded off for one another. We propose an approach that allows to derive closed-form instantaneous energy procurement and resource allocations that are function only of the actual instantaneous system parameters. Our approach computes the optimal power procurement and users’ allocation per time slot in an online fashion with very low computational complexity. Using simulations, we study the efficiency of the proposed approach under various parameters, and quantify the energy costs our approach can potentially save.
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Mobile video traffic has experienced explosive growth in recent years due to the rapid development of mobile intelligent terminals and cellular communication technologies. The rapid growth of mobile video traffic has brought significant energy expenditure for mobile network operators. To reduce the energy expenditure, one promising solution is to exploit renewable energy harvested from surrounding environments for cellular traffic delivery. In this paper, we investigate mobile video streaming in green cellular networks with hybrid energy sources, i.e., grid energy and ambient energy, to optimize both video quality and energy expenditure. Specifically, we formulate a stochastic optimization problem to maximize the long-term time-averaged network service utility, which is the difference of video quality and energy expenditure. The problem formulation takes the following factors into account: time-varying grid electricity price, energy harvesting process, and different time scales of rate adaptation, resource management, and electricity price fluctuation. We exploit Lyapunov optimization framework to decompose the problem into three subproblems: rate adaptation subproblem, battery energy management subproblem, and joint power control and subchannel assignment subproblem. We propose an efficient online green video streaming algorithm to solve these subproblems. We analyze the stability of the proposed algorithm with respect to lengths of energy queue and user request queues. Extensive simulations are conducted and the results validate the efficiency of the proposed algorithm.
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Base stations have been widely deployed to satisfy the service coverage and explosive demand increase in today's cellular networks. Their reliability and availability heavily depend on the electrical power supply. Battery groups are installed as backup power in most of the base stations in case of power outages due to severe weathers or human-driven accidents, particularly in remote areas. The limited numbers and capacities of batteries, however, can hardly sustain a long power outage without a well-designed allocation strategy. As a result, the service interruption occurs along with an increasing maintenance cost. Meanwhile, a deep discharge of a battery in such case can also accelerate the battery degradation and eventually contribute to a higher battery replacement cost. In this paper, we closely examine the base station features and backup battery features from a 1.5-year dataset of a major cellular service provider, including 4,206 base stations distributed across 8,400 square kilometers and more than 1.5 billion records on base stations and battery statuses. Through exploiting the correlations between the battery working conditions and battery statuses, we build up a deep learning based model to estimate the remaining lifetime of backup batteries. We then develop BatAlloc , a battery allocation framework to address the mismatch between the battery supporting ability and diverse power outage incidents. We present an effective solution that minimizes both the service interruption time and the overall cost. Our real trace-driven experiments show that BatAlloc cuts down the average service interruption time from 4.7 hours to nearly zero with only 85 percent of the overall cost compared to the current practical allocation.
Preprint
In this paper, the power control and interference pricing problems between macro base station (MBS) and small cell base stations (SBSs) in Heterogeneous networks (HetNets) are investigated. To optimally allocate power resources and effectively manage the power resources to reduce the interference in HetNets, an innovative Stackelberg differential game approach is proposed. In the proposed Stackelberg game, the SBSs control their transmit power to achieve cost minimization based on the interference price offered the MBS. Given the optimal power control strategies of SBSs, the MBS can adjust the interference price to realize the objective optimization. Renewable energy sources are introduced into the proposed HetNets and the SBSs' dynamic energy is formulated by differential equations. Meanwhile, the MBS's state is given by the dynamic spectrum resources. Then differential game is imported to achieve optimal power control and interference pricing. The open-loop Nash equilibrium solutions are firstly This paper was presented in part at the DRAFT 2 analyzed for the MBS and SBSs. Then the feedback Nash equilibrium solutions are given. Under the feedback pattern, the performance of the proposed model in non-cooperative situation and cooperative situation are discussed. Numerical simulations are given to show the converge and effectiveness of the proposed game approach.
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In this paper, we consider a fiber-wireless (FiWi) network consisting of 10-Gigabit-capable passive optical network (XG-PON) and wireless fidelity (WiFi). In order to mitigate the conventional limitations of grid-power supply, an off-grid FiWi network is considered, where the components of the network such as optical network units (ONUs) and IEEE 802.11 access points (APs) are powered using renewable sources of energy such as photovoltaic (PV) panels and wind turbines along with batteries. Depending on the availability of renewable power at different locations, the energy resources available to power ONU-AP may vary. Consequently, we propose a joint energy resource allocation framework to minimize the number of PV panels and batteries required by ONU-AP based on its location as well as throughput requirement of the users. An analytical framework is derived to justify the accuracy of the proposed joint energy resource allocation framework. Further, a socio-economic analysis and trade-off analysis between allocation efficiency and cost is also presented. The results show a good agreement between the analytical and the proposed approach. It has also been observed that location with high renewable energy sources contributes to a significant reduction in the number of PV panels and batteries requirement and, therefore, has lower cost and carbon dioxide (CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) emissions.
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There has been a surge in telecommunication network deployments across the globe to facilitate advanced communication infrastructure which is necessary for smart cities. This has in turn increased the power consumption of telecommunication networks, thus motivating the need to adopt green energy solutions like solar energy to power them. Base stations (BSs) are the primary entities contributing to the power consumption in the telecommunication network. To efficiently deploy solar powered base stations, it is imperative to optimally provision them with appropriate Photo Voltaic (PV) panel and battery resources. The ultimate goal of such dimensioning is to provide best possible quality of service (QoS) to the consumers while maintaining an optimal cost of deployment and operation. Both PV panels and the batteries are major contributors while calculating the overall cost of deployment and operation for a solar powered BSs. Therefore an accurate calculation of battery lifetime with respect to different PV panel dimension and battery sizes is an important step in cost optimal resource provisioning for the solar powered BSs. This issue is addressed in this paper by presenting an analytical scheme to estimate the battery lifetime for a particular resource provisioning of PV panels and batteries. This is then used for evaluating the cost-optimal photo-voltaic panel dimensions and battery size for the base station with acceptable limit of outage probability. The proposed methodology would find great relevance in developing energy efficient sustainable telecommunication networks for upcoming smart cities.
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The increasing deployment of cellular networks across the globe has brought two issues to the forefront: the energy cost of running these networks and the associated environmental impact. Also, most of the recent growth in cellular networks has been in developing countries, where the unavailability of reliable electricity grids forces operators to use sources like diesel generators for power, which not only increases operating costs but also contributes to pollution. Cellular base stations powered by renewable energy sources such as solar power have emerged as one of the promising solutions to these issues. This article presents an overview of the stateof- the-art in the design and deployment of solar powered cellular base stations. The article also discusses current challenges in the deployment and operation of such base stations and some of the proposed solutions.
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The deployment of cellular network infrastructure powered by renewable energy sources is gaining popularity as an avenue to provide coverage in areas without reliable grid power and also as a means to reduce the environmental impact of the telecommunications industry. To facilitate the deployment of such networks, this paper addresses the problem of resource provisioning and dimensioning solar powered base stations in terms of the required battery capacity and photo-voltaic (PV) panel sizing. The paper first develops a framework for evaluating the outage probability associated with a base station at a given location as a function of the battery and panel size, by using the solar energy and traffic profiles as inputs. A model is then proposed to evaluate the optimal battery and PV panel sizing, subject to the desired limit on the worst month outage probability. The proposed framework for dimensioning the base station's energy resource requirements has been evaluated using real solar irradiation data for multiple locations.
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Powering cellular networks with renewable energy sources via energy harvesting (EH) has recently been proposed as a promising solution for green networking. However, with intermittent and random energy arrivals, it is challenging to provide satisfactory quality of service (QoS) in EH networks. To enjoy the greenness brought by EH while overcoming the instability of the renewable energy sources, hybrid energy supply (HES) networks that are powered by both EH and the electric grid have emerged as a new paradigm for green communications. In this paper, we will propose new design methodologies for HES green cellular networks with the help of Lyapunov optimization techniques. The network service cost, which addresses both the grid energy consumption and achievable QoS, is adopted as the performance metric, and it is optimized via base station assignment and power control (BAPC). Our main contribution is a low-complexity online algorithm to minimize the long-term average network service cost, namely, the Lyapunov optimization-based BAPC (LBAPC) algorithm. One main advantage of this algorithm is that the decisions depend only on the instantaneous side information without requiring distribution information of channels and EH processes. To determine the network operation, we only need to solve a deterministic per-time slot problem, for which an efficient inner-outer optimization algorithm is proposed. Moreover, the proposed algorithm is shown to be asymptotically optimal via rigorous analysis. Finally, sample simulation results are presented to verify the theoretical analysis as well as validate the effectiveness of the proposed algorithm.
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The fifth generation (5G) mobile networks are envisioned to support the deluge of data traffic with reduced energy consumption and improved quality of service (QoS) provision. To this end, the key enabling technologies, such as heterogeneous networks (HetNets), massive multiple-input multiple-output (MIMO) and millimeter wave (mmWave) techniques, are identified to bring 5G to fruition. Regardless of the technology adopted, a user association mechanism is needed to determine whether a user is associated with a particular base station (BS) before the data transmission commences. User association plays a pivotal role in enhancing the load balancing, the spectrum efficiency and the energy efficiency of networks. The emerging 5G networks introduce numerous challenges and opportunities for the design of sophisticated user association mechanisms. Hence, substantial research efforts are dedicated to the issues of user association in HetNets, massive MIMO networks, mmWave networks and energy harvesting networks. We introduce a taxonomy as a framework for systematically studying the existing user association algorithms. Based on the proposed taxonomy, we then proceed to present an extensive overview of the state-of-the-art in user association conceived for HetNets, massive MIMO, mmWave and energy harvesting networks. Finally, we summarize the challenges as well as opportunities of user association in 5G and provide design guidelines and potential solutions for sophisticated user association mechanisms.
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In green communications, it is imperative to reduce the total on-grid energy consumption as well as minimize the peak on-grid energy consumption, since the large peak on-grid energy consumption will translate into the high operational expenditure (OPEX) for mobile network operators. In this paper, we consider the two dimensional optimization to lexicographically minimize the on-grid energy consumption in heterogeneous networks (HetNets). All the base stations (BSs) therein are envisioned to be powered by both power grid and renewable energy sources, and the harvested energy can be stored in rechargeable batteries. The lexicographic minimization of on-grid energy consumption involves the optimization in both the space and time dimensions, due to the temporal and spatial dynamics of mobile traffic and green energy generation. The reasonable assumption of time scale separation allows us to decompose the problem into two sub-optimization problems without loss of optimality of the original optimization problem. We first formulate the user association optimization in space dimension via convex optimization to minimize total energy consumption through distributing the traffic across different BSs appropriately in a certain time slot. We then optimize the green energy allocation across different time slots for an individual BS to lexicographically minimize the on-grid energy consumption. To solve the optimization problem, we propose a low complexity optimal offline algorithm with infinite battery capacity by assuming non-causal green energy and traffic information. The proposed optimal offline algorithm serves as performance upper bound for evaluating practical online algorithms. We further develop some heuristic online algorithms with finite battery capacity which require only causal green energy and traffic information. The performance of the proposed optimal offline and online algorithms is evaluated by simulations.
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With tremendous attention for green communications, base station (BS) which is powered by both the power grid and renewable energy sources, is regarded as a promising paradigm to reduce energy consumption as well as provide uninterrupted service. In this paper, we propose dIstributed Delay-Energy Aware (IDEA) user association in 3-tier HetNets with hybrid energy sources. IDEA user association aims to reduce on-grid power consumption by maximizing the utilization of green power harvested from renewable energy sources, as well as enhance network quality of service by minimizing the average traffic delay. To this end, a convex optimization problem is formulated which enables a flexible tradeoff between average traffic delay and on-grid power consumption. We prove that the proposed IDEA user association converges to the globally optimal solution. We then address admission control for the case where the traffic load is heavy to ensure IDEA user association works when network traffic demand is over network capacity. Simulation results indicate that the proposed IDEA user association is able to adjust the loads of BSs and RSs along with the distributions of green power, substantially reduces on-grid power consumption and achieves comparable average traffic delay compared with the existing algorithm which aims to minimize average traffic delay.
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