The design of green cellular networking according to the traffic arrivals has the capability to reduce the overall energy consumption to a cluster in a cost-effective way. The cell zooming approach has appealed much attention that adaptively offloads the BS load demands adjusting the transmit power based on the traffic intensity and green energy availability. Besides, the researchers are focused on implementing renewable energy resources, which are considered the most attractive practices in designing energy-efficient wireless networks over the long term in a cost-efficient way in the existing infrastructure. The utilization of available solar can be adapted to acquire cost-effective and reliable power supply to the BSs, especially that sunlight is free, available everywhere, and a good alternative energy option for the remote areas. Nevertheless, planning a photovoltaic scheme necessitates viability assessment to avoid poor power supply, particularly for BSs. Therefore, cellular operators need to consider both technical and economic factors before the implementation of solar-powered BSs. This paper proposed the user-centric cell zooming policy of solar-powered cellular base stations taking into account the optimal technical criteria obtained by the HOMER software tool. The results have shown that the proposed system can provide operational expenditure (OPEX) savings of up to 47%. In addition, the efficient allocation of resource blocks (RBs) under the cell zooming technique attain remarkable energy-saving performance yielding up to 27%.

The energy consumption rate of information and communication technology (ICT) has increased rapidly over the last few decades owing to the excessive demand for multimedia services. Wireless networks are considered one of the main sources of energy consumption in the ICT arena [

Researchers are focused on numerous distinctive approaches to reduce the energy consumption into wireless networks such as energy-efficient hardware components, selective operation of components, efficient use of radio transmission process, deploying heterogeneous cells, and implementing renewable energy resources (RESs) [

Considering all these inferences, researchers have insufficient descriptions for the total OPEX savings including optimum extent efficient solution of RESs. Therefore, this study examines as a major contribution achieve a balance between network performance and energy efficiency via examines the feasibility of incorporating solar-powered BSs technique with a dynamic cell zooming strategy according to the traffic load conditions in Korea to determine the net OPEX savings. The contributions of this work are summarized as follows:

To propose and determine the technical feasibility of an adaptive standalone solar power solution incorporating a dynamic cell zooming strategy based on resource susceptibility to obtain a long-tenure energy balance.

To investigate the optimal solution of harvested green energy for the considered cellular architecture endeavoring to minimum net present cost as well as OPEX savings.

To examine the technical viability in terms of energy yield, cost-effectiveness in accordance with optimum system design. Thereafter, the suggested framework is compared to other techniques for further validation.

The rest of this work is organized as follows; Section 2 presents the cell zooming concept and performance metrics. Section 3 block diagram of BS hardware elements and mathematical modeling. Section 4 shows the proposed solar power system and mathematical formulations. The cost optimization formula is given in Section 5. Section 6 presents the simulation configurations. Then, results and discussion are described in Section 7; and the economic feasibility of the proposed solar system is discussed. Lastly, Section 8 concludes the work by highlighting the attained results.

The principle cell zooming strategy depends on the capability of allowing for the adjustment of the size of the cell according to the traffic load. When congestion occurs in a cell due to an increase in the number of users, the congested cell could “zoom-in,” while neighboring cells with a smaller amount of traffic could “zoom-out” to provide coverage for the users that cannot be served by the congested cell [

If the traffic density in a particular BS is below the threshold value, then the particular BS shifts its loads to the neighboring BSs according to their current traffic status and the BS goes into sleep mode to reduce energy consumption. In such a case, the accepting BSs can zoom out to serve the new arrivals in a cooperative manner. Note that the provision of sleep mode is appropriate for low traffic density under off-peak duration. However, the neighboring BSs can only serve the incoming BSs based on their unoccupied resource blocks and green energy availability without sacrificing its own performance. In other words, the acceptor BSs adjust their transmit power to extend the coverage distances allowing the low-density BSs to enter dormant conditions. On the other hand, the BSs experiencing high traffic demand exceeding their capacity will share the load to surrounded low densified BSs according to the proposed heuristic algorithm. The two different heuristic cell zooming algorithms are described in the following.

Distance-traffic aware: sort the BSs in a cluster in ascending order based on the traffic arrivals (_{th}

Set of _{RB}_{i}

In the cell zooming algorithm, _{Zi}_{i, j},

Green energy-aware: likewise, user traffic variations, the generation of green energy is heavily dependent on the time and space domain owing to the different factors. Therefore, renewable energy production is highly variable over the geographical location. Arrange the BSs in accordance with the green energy availability in a descending manner in a certain period. According to the algorithm, the highest energy available BSs zooms out through extending the transmit power to cover surrounding new demand arrivals from the donor BSs. It is worthy to mention that the surplus electricity during peak RE generation is stored in the battery bank and can be used in the night-time. It is obvious that the green energy aware scheme exhibit inferior performance in the counterpart as it cannot have guaranteed the continuous power supply over a day or during unavailability of RE generation.

Symbol Definition |
---|

_{i} |

_{i, j} = _{i} |

Energy Consumption Gain (ECG): ECG metrics accounts the energy required for sending requested data transmission over a particular duration. ECG in green communications can be defined as the ratio of the ECR metrics of the proposed system to the reference schemes under the specified network settings. For instance, the network architecture without cell zooming is considered as a reference baseline and cell zooming enabled green-powered cellular system is the proposed scheme recognized as a more energy-efficient architecture.

A system with lower ECG identified as more energy efficient as it consumes low power to transmit the same amount of data transmission.

However, ECR is an equipment level standard that evaluates the achievable throughput of the entire radio access network per given power expenditure. On the other hand, ERG metrics are sometimes preferable for energy efficiency analysis in the area of green cellular networking. The ERG can be expressed as

Energy Saving Index (ESI): ESI metric measures the energy-saving gain introducing the cell zooming concept under different zoom out range. It can define as

where

Load factor (_{O}_{T}

A RB is the least unit of physical resource allocation assigned to every user. Resource block allocation decide the number of simultaneous users connected to the LTE base stations. In LTE, one physical RB occupied 10 kHz bandwidth, having 12 subcarriers (each 15 kHz) and 14 symbols over 1 msec duration. Typically, 10% RBs are kept reserved in LTE system in order to avoid overlapping issue.

The cellular BS consists of various equipment that can be used to communicate with mobile/cellular units. The backhaul network has the following sub-units: (i) multiple transceivers (TRXs), (ii) power amplifier (PA), (iii) radio-frequency (RF), (iv) baseband (BB), (v) DC–DC Power supply, and (vi) cooling systems. The TRXs comprise PA which amplifies the signal power coming from the BB unit. Besides, the BB is adapted for internal processing and coding, as shown in

The net power consumption by the BS is derived through the following equation [

where _{TRX}

Elements | Parameters | Unit | BS | Cell zooming-out | Cell zooming-in | |
---|---|---|---|---|---|---|

PA | Watts | 51.5 | 102.6 | 16.3 | ||

RF | Watts | 10.9 | 10.9 | 5.4 | ||

BB | Watts | 14.8 | 14.8 | 13.6 | ||

Loss factor ( |
% | 6.0 | 6.0 | 6.0 | ||

Loss factor ( |
% | 10.0 | 10.0 | 0.0 | ||

Watts | 91.25 | 151.65 | 37.55 | |||

No. of transceivers |
6 | 6 | 6 | |||

Total power of the BS |
Watts | 547.52 | 909.93 | 225.32 |

The proposed system comprises three segments such as sources, converters, and loads. PV panels which are arranged in series and parallel connection based on the voltage and current ratings. A battery bank or battery energy storage system (BESS) stores the energy from PV panels and ensures the reliability and power quality of the generated power. Furthermore, a DC/AC converter is used to convert the power to AC which supplies the power to the AC load (Air conditioner). Moreover, excess energy is stored in the BESS as a backup which can be utilized during non-sunny periods notably at night. The following subsections thoroughly demonstrate the architecture of a solar system.

The total annual energy extraction from the PV arrangement (_{PV}

where _{PV}_{PV}

The BESS capacity of the BS merely depends on the depth of discharge (DOD) and must be evaluated before commissioning. It can be expressed as [

where _{min}

where the terms _{batt} and V_{nom} are the total number of battery units in the BESS and a nominal voltage of a single battery unit (V), respectively. The terms _{nom}_{prim, ave} are the nominal capacity of a single battery (Ah) and average daily BS load (kWh), respectively.

The lifetime of the battery plays a crucial role. The lifetime of a battery can be predicted based on the operating conditions. More specifically, the DOD during each diurnal charge-discharge cycle displays a foremost role in the battery lifetime. It can be computed as [

where the term _{lifetime}_{thrpt}_{battf}

The total capacity of the inverter (_{inv}

where the term _{AC}

The HOMER Micro-power optimization tool aids, to obtain an optimal solar system with low net present cost (NPC). The term NPC contains all incurred expenses and incomes throughout the project lifetime. The total annualized cost (_{TAC}

The net present cost (_{NPC}

The term CRF denotes the recovery factor which converts a _{NPC}

The _{NPC}

wherein where _{comp}_{rem}_{rep}

This study scrutinizes to minimize the total cost of the NPC for an optimal scheme of a stand-alone solar system based on various constraints. To attain system optimization, the objective function of the NPC can be derived using

The above-derived objective function is subjected to the following constraints;

To warrant a power balance between actual demand and energy production, the power production of the available sources (_{PV}_{Battery}_{BS}_{Losses}

The monthly average solar irradiation values, as shown in

Components | Parameters | Range |
---|---|---|

Control factors | Interest rate-Annual Korea (December, 2020) | 0.5% |

Project lifespan | 10 years | |

Dispatch scheme | cyclic charging | |

Apply set point SOC | 80% | |

Percentage of load and hourly load | 10% | |

PV | Sizes considered | 2, 2.5, 3, 4, 4.5, 5 kW |

Operational lifetime | 25 years | |

Efficiency | 85% | |

Principal rate | $1/Watt | |

Replacement rate | $1/Watt | |

O&M price/year | $0.01/Watt | |

Inverter | Sizes considered | 0.1, 0.2, 0.3, 0.4 kW |

Efficiency | 95% | |

Operational lifespan | 15 years | |

Principal cost | $0.4/Watt | |

Replacement rate | $0.4/Watt | |

O&M price/year | $0.01/Watt | |

Trojan L16P Battery | Number of batteries | 24, 32, 40, 64, 72 |

Round trip efficacy | 85% | |

Minimum operational lifespan | 5 years | |

Principal cost | $300 | |

Replacement rate | $300 | |

O&M price/year | $10 |

Most economically, the total NPC cost of solar-powered BS is $26,887 that comprises 2.5 kW rated PV panels and 64 numbers batteries which are connected in eight parallel strings along with a 0.1 kW inverter. Detailed discussions of the optimal size measures, energy harvest, and economic investigation of the proposed solar-powered BS are given in the following subsections.

The optimal capacity of the PV array, as determined by the HOMER, is 2.5 kW. The designed PV array has 10 Sharp modules, and each proposed module is rated at 250 W with a nominal voltage of 29.80 V, nominal current of 8.40 A, open-circuit voltage of 38.3 V, and short circuit current of 8.9 A. The yearly energy output of the PV is calculated using

The ratios of annual energy output and input of the BESS, i.e., 2625 and 3077 kWh, respectively. Roughly, the BESS supplies the power to the load about 237 h, specifically during the malfunction of the PV array. The seasonal statistics that the maximum energy contribution of the BESS is in August, while the minimum energy contribution in April. Besides, the frequency histogram of the state of charge (SOC) shown that the state of charge stretched to 42%. The average hourly energy generation of the PV, BESS, unmet load, and excess electricity is presented in

The net capacity of the inverter unit is 0.1 kW, and its efficiency is computed between the input (236 kWh) and output energy (224 kWh) annually and observed as 95%. The total operating hours are 8,759 h/year (24 h

A cash flow summary for Seoul city is presented in

The size of the system is directly proportional to the IC cost invested during the commencement of the scheme. The total IC of the proposed scheme is $21,740 and its breakdown is as follows:

11.50% for PV array (2.5 kW (size)

88.32% for BESS (64 (units)

0.19% for inverter (0.1 kW (size)

The O&M cost of the system is considered to be $6660, and its breakdown is as follows:

For PV array (i.e., 2.5 kW (size)

For BESS (64 (units)

For inverter (0.1 kW (size)

Due to the short operational lifespan of the project (10 years), and the lifespan of the BESS, PV arrays, and inverter is 10, 25, 15 years respectively. There are no replacement costs.

The salvage value of each component at the end of the project lifespan has to be considered. With the help of

The net NPC is calculated by adding up the aggregated cash flows for each year and found to be $26,887 i.e., $21,740 (IC) + $6660 (O&M prices) − $1513 (salvage).

A quantitative comparison of the ECG identifying the impact of two different cell zooming techniques is clearly presented in

A detailed comparison of two different BS zooming options such as distance-traffic aware and green energy availability is demonstrated in

The key priority of the mobile operators is to increase the profit with reduced OPEX in the cellular network. The economic viability with the PV system over conventional energy resources are as follows;

In remote areas, i.e., an off-grid station, the Diesel generator (DG) is usually employed to power the BS. The DG rating should be around 3.5 kW that can be figured between the ratio of maximum BS and 30% DG efficiency

The IC costs are computed by multiplying the system size of 3.5 kW with its cost of about $660/kW.

The O&M cost (annual) of the DG is approximately $4,150 (excluding fuel transportation cost). A breakdown of this cost is described as;

▪ The net maintenance cost of DG is $438/year, estimated using the product of DG maintenance cost ($0.05/h) with annual operational hours (8760 h).

▪ The total fuel cost is computed using the product of diesel price ($1.04/liter) with total diesel consumption (3,569 liter/year) and found to be $3,712. It is calculated based on specific fuel consumption (0.388 liter/kWh)

Every three years, a cellular operator has to replace the DG, i.e., a minimum of three DG replacements during the lifespan of the scheme. Therefore, the net replacement rate is equal to $6,930, i.e., 3

The net NPC of the solar system is approximately $26,887. Applying the proposed solar system, total OPEX savings $23,849 which is 47% compared with the conventional power sources.

In this work, the solar-powered BSs technique with a dynamic cell zooming strategy according to the traffic load conditions is suggested for the green wireless networks. The simulation results revealed that the proposed system can be achieved OPEX savings of up to 47%, and it can potentially meet the total demand of BS without any outage. Moreover, two different heuristic cell zooming algorithms are extensively compared to extract the best option by means of energy savings under optimal technical conditions. Results reveal that distance-traffic aware cell zooming scheme exhibits more energy-efficient yielding to 27%, 5%, 6.5% in terms of ECG, ERG, and ESI, respectively compared to the availability of renewable energy-based method.