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Abstract 5G base stations (BSs) are potential flexible resources for power systems due to their dynamic adjustable power consumption. However, the ever‐increasing energy consumption of 5G BSs places great pressure on electricity costs, and existing energy‐saving measures do not fully utilise BS wireless resources in accordance with dynamic changes in communication load, resulting in flexible resource waste and seriously limiting electricity cost savings for 5G BSs. A multi‐BS cooperation self‐optimising sleep strategy for 5G BSs that consists of an initial user association stage based on multi‐BS cooperation (MBSC) and a self‐optimising variable‐threshold sleep stage (SVTS). First, a heterogeneous cellular network (HCN) model is established. Then, a 5G BS economic optimisation model is constructed, which aims at minimising the electricity cost of the BSs and takes the BS and user equipment (UEs) states in the HCN model as constraints to clarify the optimisation objective and constraints for the proposed strategy. Furthermore, BSs are initially associated with UEs through MBSC, and idle and lightly loaded BSs are then maximally put to sleep through SVTS to reduce power and energy consumption and thereby realise economic optimisation of the BSs. Finally, simulations are conducted to validate the proposed strategy and illustrate the ability of 5G BSs to provide flexible resource regulation for power systems.

Reformation of the 3.7–4.0 GHz band to expand 5G communication deployment poses a risk of 5G signals disrupting radar altimeter operation, leading to data loss or inaccuracies. Thus, this paper proposes a guard band protection method to facilitate the coexistence of 5G base stations and radar altimeters operating in the 4.2–4.4 GHz band. To enhance the adjacent channel leakage ratio (ACLR), we implemented spectral regrowth on an oversampled waveform using a high-power amplifier model, filtering out-of-band spectral emissions. The results demonstrated that a 150 MHz guard band enables coexistence, except in the case of the 16-by-16 antenna array in rural environments. Notably, for the 4-by-4 antenna array in urban environments, coexistence can be achieved using a 50 MHz guard band. The proposed mitigation techniques may also be extended to promote coexistence between non-terrestrial networks and 5G communication systems, including satellites, unmanned aerial vehicles, and hot air balloons. [ABSTRACT FROM AUTHOR]

The reliability of the power supply for 5G base stations (BSs) is increasing. A large amount of BS backup energy storage (BES) remains underutilized. This study establishes a double-layer optimization distribution network (DN) considering BS clusters. An energy consumption characteristics and scheduling ability model of the BSs was established to address the differences in the characteristics of different traffic flows. A double-tier planning model for BS-joining grid market ancillary services is proposed. The upper-layer model addresses optimal tidal flow problems in DNs to minimize integrated operating costs, while the lower-layer model focuses on BES economic optimization. The double-layer model changes into a single-layer linear model using the Karush-Kuhn-Tucker (KKT) condition and the Big M method. Simulation validation using the IEEE-33 node DN proves that this approach can reduce DN operating costs, regulate voltage fluctuations, and guarantee economical and safe DN operation. [ABSTRACT FROM AUTHOR]

With the rapid development of the digital new infrastructure industry, the energy demand for communication base stations in smart grid systems is escalating daily. The country is vigorously promoting the communication energy storage industry. However, the energy storage capacity of base stations is limited and widely distributed, making it difficult to effectively participate in power grid auxiliary services by only implementing the centralized control of base stations. Aiming at this issue, an interactive hybrid control mode between energy storage and the power system under the base station sleep control strategy is delved into in this paper. Grounded in the spatiotemporal traits of chemical energy storage and thermal energy storage, a virtual battery model for base stations is established and the scheduling potential of battery clusters in multiple scenarios is explored. Then, based on the time of use electricity price and user fitness indicators, with the maximum transmission signal and minimum operating cost as objective functions, a decentralized control device is used to locally and quickly regulate the communication system. Furthermore, a multi-objective joint peak shaving model for base stations is established, centrally controlling the energy storage system of the base station through a virtual battery management system. Finally, a simulation analysis was conducted on data from different types of base stations in the region, designing two distinct scheduling schemes for four regional categories. The analysis results demonstrate that the proposed model can effectively reduce the power consumption of base stations while mitigating the fluctuation of the power grid load. [ABSTRACT FROM AUTHOR]

Dense network deployment is now being evaluated as one of the viable solutions to meet the capacity and connectivity requirements of the fifth-generation (5G) cellular system. The goal of 5G cellular networks is to offer clients with faster download speeds, lower latency, more dependability, broader network capacities, more accessibility, and a seamless client experience. However, one of the many obstacles that will need to be overcome in the 5G era is the issue of energy usage. For energy efficiency in 5G cellular networks, researchers have been studying at the sleeping strategy of base stations. In this regard, this study models a 5G BS as an M [ X ] / G / 1 feedback retrial queue with a sleeping strategy to reduce average power consumption and conserve power in 5G mobile networks. The probability-generating functions and steady-state probabilities for various BS states were computed employing the supplementary variable approach. In addition, an extensive palette of performance metrics have been determined. Then, with the aid of graphs and tables, the resulting metrics are conceptualized and verified. Further, this research is accelerated in order to bring about the best possible (optimal) cost for the system by adopting a range of optimization approaches namely particle swarm optimization, artificial bee colony and genetic algorithm. [ABSTRACT FROM AUTHOR]

With its technical advantages of high speed, low latency, and broad connectivity, fifth-generation mobile communication technology has brought about unprecedented development in numerous vertical application scenarios. However, the high energy consumption and expansion difficulties of 5G infrastructure have become the main obstacles restricting its widespread application. Therefore, aiming to optimize the energy utilization efficiency of 5G base stations, a novel distributed photovoltaic 5G base station DC microgrid structure and an energy management strategy based on the Curve Fitting–Perturb and Observe–Incremental Conductance (CF-P&O-INC) Maximum Power Point Tracking (MPPT) algorithm from the perspectives of energy and information flows are proposed. Simulation results show that the proposed MPPT algorithm can increase the efficiency to 99.95% and 99.82% under uniform irradiation and partial shading, respectively. Under the proposed strategy, when the base station load changes drastically, the voltage fluctuation of the DC bus is less than 1.875%, and returns to a steady state within 0.07s, alleviating the high energy consumption of 5G base stations effectively and achieving coordinated optimization management of various types of energy in multi-source power supply systems. [ABSTRACT FROM AUTHOR]

Radio Determination Satellite Service (RDSS) is a characteristic service of BeiDou, which can provide users with short message communication services. Since the working frequency of an RDSS system is close to that of a 5G system, the RDSS system is very susceptible to interference from 5G out-of-band radiation. This paper analyzes the compatibility of 5G interference with an RDSS system from the perspective of the signal and the system. Firstly, the compatibility assessment is carried out from the perspective of the signal, the impact of interference on the capture and tracking performance of BeiDou is illustrated, and the safe coexistence distance of the two systems from the perspective of capture probability is obtained from the perspective of the signal. Subsequently, based on the link budget criterion, the interference of 5G base stations and 5G terminals to RDSS receivers under different frequency isolation and the required distance isolation for safe coexistence are analyzed from the system perspective. Finally, from the perspective of civil aviation safety, the aggregate interference is used as an evaluation index to evaluate the interference suffered by the aircraft during takeoff and landing and to obtain the interference suffered by the ground-based 5G base station during the takeoff and landing of the aircraft on different routes and in different 5G propagation environments. The simulation results show that when the airplane is closer to the ground, the ground 5G base stations will cause harmful interference to the RDSS receiver. In this study, the real flight data are combined with the simulation model to obtain the exact influence range of 5G interference on the RDSS system under different viewpoints. [ABSTRACT FROM AUTHOR]

Leveraging the dispatchability of 5G base station energy storage (BSES) not only enables the mobile network operator (MNO) to gain additional revenue, but also facilitates the integration of renewable energy sources in distribution network (DN). However, since BSES and DN are owned by different stakeholders, integrating BSES into DN operations poses significant challenges. In this regard, this paper proposes a DN optimal dispatch model that incorporates the adaptive aggregation of 5G base stations (BSs) through a cooperative game framework. Firstly, the dispatchability of BSESs is analyzed and modelled. Considering it is difficult to dispatch every single unit optimally, an adaptive aggregation model of 5G BSs is established, where the electrical coupling degree and the communication service similarity are taken as comprehensive metrics. On this basis, an optimal dispatch model of DN based on cooperative game is constructed, where the total operational costs of 5G BSs and DN are considered as the characteristic function. The number of 5G BS clusters and the aggregating results are adjusted adaptively during optimization. The optimal aggregation of 5G BSs is achieved using the Affinity Propagation (AP) clustering algorithm. Furthermore, to solve the optimal dispatch model of the DN with enhanced computational efficiency, the particle swarm optimization algorithm integrated with second-order cone programming (PSO-SOCP) is employed. After dispatching, the benefit allocation between MNO and distribution system operator (DSO) is conducted using the Shapley value method and the Equal Profit Method to obtain an entire range of allocation results. Finally, simulations are carried out with results proving the effectiveness of the proposed method.

5G base stations have experienced rapid growth, making their demand response capability non-negligible. However, the collaborative optimization of the distribution network and 5G base stations is challenging due to the complex coupling, competing interests, and information asymmetry among different stakeholders. In this paper, a distributed collaborative optimization approach is proposed for power distribution and communication networks with 5G base stations. Firstly, the model of 5G base stations considering communication load demand migration and energy storage dynamic backup is established. Afterward, a collaborative optimal operation model of power distribution and communication networks is designed to fully explore the operation flexibility of 5G base stations, and then an improved distributed algorithm based on the ADMM is developed to achieve the collaborative optimization equilibrium. Finally, the effectiveness of the proposed distributed collaborative optimization model is validated by a modified IEEE 33-bus power distribution and communication networks with 5G base stations.

To solve the issues of high energy consumption of traditional air conditioner (TAC) in communication cabinets and ineffective temperature control of baseband unit (BBU), integrated equipment of heat pipe and air conditioning (IEHA) is developed. After a year of the field test, the operational effects of IEHA in different seasons are explored, and the application of the integrated technology of heat pipe and air conditioner (ITHA) is analyzed. The results show that the working temperature of BBU regulated by IEHA meets the relevant standards. Compared with TAC, the IEHA achieves energy saving rates (ESR) of 57.3 %, 67.2 %, and 89.9 % in summer, transitional seasons, and winter, respectively, and the power use efficiency (PUE) is 1.34, 1.23, and 1.05, respectively. The annual ESR is 68.5 %, the annual PUE is reduced from 1.67 to 1.21, and the payback period is 1.15 years. The ESR of ITHA under different cities in China is 55.5–80.8 %, the payback period is 0.97–1.41 years, and the PUE is 1.13–1.30. The fitting functions of the three indexes and the annual average outdoor temperature of the cities are obtained, respectively. This study provides references for the temperature control and energy savings of communication cabinets and the wide application of ITHA.

The reliability of the power supply for 5G base stations (BSs) is increasing. A large amount of BS backup energy storage (BES) remains underutilized. This study establishes a double-layer optimization distribution network (DN) considering BS clusters. An energy consumption characteristics and scheduling ability model of the BSs was established to address the differences in the characteristics of different traffic flows. A double-tier planning model for BS-joining grid market ancillary services is proposed. The upper-layer model addresses optimal tidal flow problems in DNs to minimize integrated operating costs, while the lower-layer model focuses on BES economic optimization. The double-layer model changes into a single-layer linear model using the Karush–Kuhn–Tucker (KKT) condition and the Big M method. Simulation validation using the IEEE-33 node DN proves that this approach can reduce DN operating costs, regulate voltage fluctuations, and guarantee economical and safe DN operation.

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the growing demand for 5G, many countries have allocated additional spectrum above 3.7 GHz, potentially causing serious interference to radar altimeters operating at the 4.2–4.4 GHz band. Therefore, in this paper, a general mathematical model is proposed to estimate interference from 5G base stations to a radar altimeter which can be applied for aircraft, helicopters, unmanned aerial vehicles, satellites, and hot-air balloons. Using this model, the interference at the radar altimeter is evaluated in several environments such as rural, suburban, and urban. Two types of antennas are considered which are omnidirectional and multiple-input and multiple-output antennas (4-by-4, 8-by-8, and 16-by-16). Additionally, a power control-aided distance protection method is introduced to enable the coexistence of the 5G base stations and the radar altimeters. To validate the effectiveness of the proposed protection method, the Monte Carlo method is employed. Numerical results present the heights of the radar altimeter where the interference-to-noise ratio becomes higher than the interference protection threshold of −6 dB. In addition, it shows that the radar altimeter can coexist with the 5G base stations with the proposed protection scheme.

The explosive growth of mobile data traffic has resulted in a significant increase in the energy consumption of 5G base stations (BSs). However, the existing energy conservation technologies, such as traditional BS sleep strategy, rarely consider the dynamic real-time changes of users (UEs), which may make it difficult to maximize sleep idle or lightly loaded BSs, thereby affecting the reduction of BS energy consumption. Therefore, an energy consumption optimization strategy of 5G BSs considering variable threshold sleep mechanism (ECOS-BS) is proposed in this paper. Compared to current strategies, the ECOS-BS strategy can dynamically adjust BSs’ optimal sleep threshold on the premise of considering UEs’ dynamic changes, which is conducive to maximize sleep available BSs and realize the optimal management of BS energy consumption. Taking a heterogeneous cellular network as an example, numerical simulations are conducted to validate the effectiveness of the proposed strategy.

The extensive construction and promotion of 5G base stations (5GBSs) have led to a surge in communication energy consumption, as 5G energy consumption is about three to five times that of 4G. To reduce the energy consumption of 5GBS, this article incorporates 5GBS into power demand side management and proposes a flexible resource collaborative optimization method that integrates 5GBS with virtual power plants (VPPs). Firstly, starting from the basic structure of 5GBS, the adjustable potential of 5GBS and the paths for participating in VPP optimization were analyzed. Secondly, with the minimum operating cost as the optimization objective and considering the constraints of 5GBS and various decentralized resources, a demand side decentralized resource collaborative optimization model for VPP integrating 5GBS was established. This model can be solved using the Non-dominated sorting genetic algorithm II (NSGA-II) algorithm. The results indicate that the participation of 5GBS in power demand side management can reduce their comprehensive energy consumption and operating costs. [ABSTRACT FROM AUTHOR]

A multifunctional microwave absorber with high thermal conductivity for 5G base station packaging comprising silylated GO/FeSiAl epoxy composites were fabricated by a simple solvent-handling method, and its microwave absorption properties and thermal conductivity were presented. It could act as an applicable microwave absorber for highly integrated 5G base station packaging with 5G antennas within a range of operating frequency of 2.575–2.645 GHz at a small thickness (2 mm), as evident from reflection loss with a maximum of −48.28 dB and an effective range of 3.6 GHz. Such a prominent microwave absorbing performance results from interfacial polarization resonance attributed to a nicely formed GO/FeSiAl interface through silylation. It also exhibits a significant enhanced thermal conductivity of 1.6 W/(mK) by constructing successive thermal channels. [ABSTRACT FROM AUTHOR]

The widespread installation of 5G base stations has caused a notable surge in energy consumption, and a situation that conflicts with the aim of attaining carbon neutrality. Numerous studies have affirmed that the incorporation of distributed photovoltaic (PV) and energy storage systems (ESS) is an effective measure to reduce energy consumption from the utility grid. The optimization of PV and ESS setup according to local conditions has a direct impact on the economic and ecological benefits of the base station power system. An improved base station power system model is proposed in this paper, which takes into consideration the behavior of converters. And through this, a multi-faceted assessment criterion that considers both economic and ecological factors is established. Then, the PV and ESS capacity optimization for base stations under multiple scenarios is realized. The case study indicates that the optimization process of PV and ESS is significantly influenced by the behavior of the converter. [ABSTRACT FROM AUTHOR]

The proportion of traditional frequency regulation units decreases as renewable energy increases, posing new challenges to the frequency stability of the power system. The energy storage of base station has the potential to promote frequency stability as the construction of the 5G base station accelerates. This paper proposes a control strategy for flexibly participating in power system frequency regulation using the energy storage of 5G base station. Firstly, the potential ability of energy storage in base station is analyzed from the structure and energy flow. Then, the framework of 5G base station participating in power system frequency regulation is constructed, and the specific steps are described. Finally, with the objective to minimize the power vacancy, the optimization model of the 5G base station auxiliary power system frequency response is established. Considering two cases of power system frequency rises and drops, the response proportion of base station in different operating states is solved from the proposed model. The simulation results show that the proposed method can not only help the system frequency recover quickly, but also reduce overshoot when the frequency fluctuates of power system. [ABSTRACT FROM AUTHOR]

The electricity cost of 5G base stations has become a factor hindering the development of the 5G communication technology. This paper revitalized the energy storage resources of 5G base stations to achieve the purpose of reducing the electricity cost of 5G base stations. First, it established a 5G base station load model considering the communication load and a 5G base station energy storage capacity schedulable model considering the energy storage backup power demand of the 5G base station and the power supply reliability of the distribution network. Then, it proposed a 5G energy storage charge and discharge scheduling strategy. It also established a model for 5G base station energy storage to participate in coordinated and optimized dispatching of the distribution network. Finally, it compared the economy of optimized dispatch of 5G base station energy storage of different schemes. The analysis results show that the participation of idle energy storage of 5G base stations in the unified optimized dispatch of the distribution network can reduce the electricity cost of 5G base stations, alleviate the pressure on the power supply of the distribution network, increase the rate of new energy consumption in the system, and realize a win-win situation between the communication operator and the grid.

Radio Determination Satellite Service (RDSS) is a characteristic service of BeiDou, which can provide users with short message communication services. Since the working frequency of an RDSS system is close to that of a 5G system, the RDSS system is very susceptible to interference from 5G out-of-band radiation. This paper analyzes the compatibility of 5G interference with an RDSS system from the perspective of the signal and the system. Firstly, the compatibility assessment is carried out from the perspective of the signal, the impact of interference on the capture and tracking performance of BeiDou is illustrated, and the safe coexistence distance of the two systems from the perspective of capture probability is obtained from the perspective of the signal. Subsequently, based on the link budget criterion, the interference of 5G base stations and 5G terminals to RDSS receivers under different frequency isolation and the required distance isolation for safe coexistence are analyzed from the system perspective. Finally, from the perspective of civil aviation safety, the aggregate interference is used as an evaluation index to evaluate the interference suffered by the aircraft during takeoff and landing and to obtain the interference suffered by the ground-based 5G base station during the takeoff and landing of the aircraft on different routes and in different 5G propagation environments. The simulation results show that when the airplane is closer to the ground, the ground 5G base stations will cause harmful interference to the RDSS receiver. In this study, the real flight data are combined with the simulation model to obtain the exact influence range of 5G interference on the RDSS system under different viewpoints.

Based on a large amount of energy consumption, performance indicators and base station configuration data that can be collected in the 5G network management system, this paper uses machine learning algorithms to establish an energy consumption calculation model for common AAU equipment on the existing network, and verifies the accuracy of the model. The test results show that the accuracy of the energy consumption calculation models established by this scheme for several common AAU devices in the existing network has reached more than 97%, which fully proves that the energy consumption modeling method has high practicability and promotion value.

Copyright of Journal of Guangxi Normal University - Natural Science Edition is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this work, a dual-polarized broadband metasurface antenna is proposed. The antenna consists of a new Metasurface patch which is formed from different cross shapes to achieve wide bandwidth and expedite dual polarization features. The radiating metasurface patch is fed by a novel coplanar waveguide fed structure to facilitate achieving dual polarization. The proposed antenna has a wide bandwidth of 2.82 GHz over an operating frequency range between 3.36–6.2 GHz with 10 dBi maximum realized gain. The proposed antenna has been fabricated and the simulated results have been validated experimentally. It is believed that the proposed antenna is a good candidate for sub 6 GHz of 5G application. [ABSTRACT FROM AUTHOR]

Base stations (BSs) sleeping strategy has been widely analyzed nowadays to save energy in 5G cellular networks. 5G cellular networks are meant to deliver a higher data speed rate, ultra-low latency, more reliability, massive network capacity, more availability, and a more uniform user experience. In 5G cellular networks, BSs consume more power which is about 4 times that of 4G. To reduce average power consumption and save power in 5G, we have modelled the 5G BSs sleeping mechanism as an M/G/1 queue with two types of vacations (two different sleep modes), idle period (close-down), and set-up periods. Based on the traffic load, the BSs adjust their transmitting power in the active state, idle state (close down state), sleep mode 1 (type 1 vacation), sleep mode 2 (type 2 vacation) and set-up state. The length of sleep mode 1 is smaller than the length of sleep mode 2. Sleep mode 1 consists of a maximum M sleeps. When the BSs are in sleep mode or shut off, they will experience a state delay. To overcome this delay, it is necessary to optimize sleep in sleep mode 1 considering a small amount of set-up time. To optimize the maximum sleeps in sleep mode 1, the tradeoff between power consumption/power-saving and throughput is shown. Finally, the trade-off between power consumption and saving is presented to get the energy efficiency from 5G BSs. Without finding the energy efficiency i.e., optimal power consumption and power saving in 5G BSs, it will not be possible to say how much the model is effective for use in 5G BSs. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Utilizing the backup energy storage potential of 5G base stations (BSs) for economic regulation is an essential strategy to provide flexibility to the power grid and reduce operational costs. However, the dimensionality of the decision variables for centralized regulation of large-scale BSs is substantial, thereby increasing the computational complexity. Furthermore, the traditional clustering method, which could enhance solution speed, fails to account for the spatiotemporal dynamics of the regulation potential induced by the tidal effect and the sleep mechanism of 5G BSs. This limitation affects the accuracy of regulation and the utilization of the BSs' regulable potential. Therefore, a hierarchical regulation strategy based on dynamic clustering for economic optimization of large-scale 5G BSs is proposed, where BSs are regulated at two levels: cluster and individual. Focusing on the changes in 5G BSs' regulation potential, a dynamic clustering method based on K-means is proposed, which considers the regulable capacity and geographical location of BSs over time and space, thereby reducing the computational scale. The method accounts for changes in the regulable capacity to modify clusters and dynamically aggregates them for modeling. Furthermore, the clustering regulation economic optimization model and in-cluster power allocation control model are established respectively at the cluster and individual levels to solve the corresponding regulation schemes. Due to the interaction between the clustering and regulation in the overall strategy, the optimal clustering and regulation scheme are determined through the iteration of dynamic clustering, clustering regulation and in-cluster allocation. The simulation with 2916 BSs in a test area is conducted. The results show that the computation time of the proposed strategy is reduced to 2.34 % of the centralized regulation. The maximum error of the regulable capacity and regulation scheme decrease by 21.93 % and 9.32 %. It demonstrates that the proposed strategy enhances the speed of large-scale 5G BSs regulation while ensuring the accuracy of regulation and utilization of the regulable potential. • A dynamic clustering method to aggregates BSs and modify clusters dynamically is proposed. • A hierarchical regulation strategy based on dynamic clustering method for economic optimization is proposed. • The speed of large-scale 5G BS regulation is enhanced by the hierarchical regulation. • The accuracy of regulation and utilization of the regulable potential are ensured by the dynamic clustering. [ABSTRACT FROM AUTHOR]

The high-energy consumption and high construction density of 5G base stations have greatly increased the demand for backup energy storage batteries. To maximize overall benefits for the investors and operators of base station energy storage, we proposed a bi-level optimization model for the operation of the energy storage, and the planning of 5G base stations considering the sleep mechanism. A multi-base station cooperative system composed of 5G acer stations was considered as the research object, and the outer goal was to maximize the net profit over the complete life cycle of the energy storage. Furthermore, the power and capacity of the energy storage configuration were optimized. The inner goal included the sleep mechanism of the base station, and the optimization of the energy storage charging and discharging strategy, for minimizing the daily electricity expenditure of the 5G base station system. Additionally, genetic algorithm and mixed integer programming were used to solve the bi-level optimization model, analyze the numerical example test comparison of the three types of batteries and the net income of the configuration, and finally verify the validity of the model. Furthermore, the sleep mechanism, the charging and discharging strategy for energy consumption, and the economic benefits for the operators were investigated to provide reference for the 5G base station energy storage configuration.

The traffic activity of fifth generation (5G) networks demand for new energy management techniques that is dynamic deep and longer duration of sleep as compared to the fourth generation (4G) network technologies that demand always for varied control and data signalling based on control base station (CBS) and data base station (DBS). Hence, this paper discusses the energy management in wireless cellular networks using wide range of control for twice the reduction in energy conservation in non-standalone deployment of 5G network. As the new radio (NR) based 5G network is configured to transmit signal blocks for every 20 ms, the proposed algorithm implements withstanding capacity of on or off based energy switching, which in-turn operates in wide range control by carrying out reduced computational complexity. The proposed Wide range of control for base station in green cellular network using sleep mode for switch (WGCNS) algorithm toon and off the base station will work in heavy load with neighbouring base station. For reducing the overhead duration in air, heuristic versions of the algorithm are proposed at the base station. The algorithm operates based on the specification with suggested protocol-level to give best amount of energy savings. The proposed algorithm reduces 40% to 83% of residual energy based on the traffic pattern of the urban scenario. [ABSTRACT FROM AUTHOR]

In daily life, the most direct and important way of human communication is voice. With the rise of the Internet and the development of communication technology, the proportion of non voice signals such as image and data in communication system is increasing. However, in most communication systems, voice transmission function is generally required, so it is still one of the necessary functions for many communication systems to transmit voice information effectively. With the rapid development of the Internet, especially the recent 5G technology commercial and future civil, human–computer interaction will become more and more intelligent in the future, which also poses a greater challenge to speech recognition as a human–computer interface. Noise interference is one of the biggest obstacles to the practical application of speech system. Although a large number of noisy data based on deep learning can solve part of the noise robustness problem, non-stationary noise interference is still a great challenge for speech recognition system in very low SNR complex scenes. In addition, in the multi information fusion communication system, there are many kinds of data to be transmitted, and there are high requirements for bandwidth and storage space. Hence, this paper studies the construction of voice signal communication system based on the artificial intelligence and 5G technology. The model is designed and implemented considering the complex scenarios. The performance is validated through the simulations compared with the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

5G base stations (BSs), which are the essential parts of the 5G network, are important user-side flexible resources in demand response (DR) for electric power system. However, a 5G BS has little and difference dispatchable potential, how to make massive 5G BSs participate in DR conveniently is an urgent problem to be solved. Clustering is an effective solution. Aiming at the special requirements of big data analysis and dispatching difficulties brought by the massive and ultra-dense distribution of 5G BSs, this paper proposes a double-layer K-means++ clustering method for regional 5G BSs considering the main characteristics of 5G BSs. The proposed clustering method considers both the geographical location and power consumption characteristics of the regional 5G BSs to partition the 5G BSs into appropriate number of clusters. Besides, the comprehensive charging and discharging dispatchable potential evaluation indices are established based on the clustering results to evaluate the dispatchable potential of each cluster. The effectiveness of the proposed method and the dispatchable potential evaluation indices are verified through a case of 5000 5G BSs in Jiaxing, China. The simulation findings reveal that the performance of the proposed clustering method is better than classical clustering algorithm and the dispatchable potential of the 5G BSs clusters can be accurately analyzed by the proposed comprehensive indices, which lay the foundation for friendly and fine interaction between 5G BSs and the power grid.

According to the safety application requirements of coal mine 5G communication system, the safety application technology of 5G core network side and wireless access side is studied. On the core network side, a private network technology and a network slicing technology are adopted to realize the physical isolation of different coal mine business scenarios. A proportional fair algorithm is adopted to optimize the allocation of resource blocks in a slicing group to realize the slicing resource scheduling and guarantee the safe and reliable transmission of coal mine business data. On the wireless access side, the antenna isolation circuit is designed to realize the intrinsic safety of the output signal of the base station, and the RF threshold power of the 5G base station is limited to 6 W so as to eliminate the potential safety danger caused by radiated energy, and to realize the safe access of a variety of underground mine terminal device. The underground test results show that the wireless coverage radius of the 5G base station is 100 m, the signal strength in the coverage area is not less than 100 dB, the upload rate is not less than 520 Mbit/s, the average communication delay is 18.56 ms, and the user service performance is improved by 52.8% when the number of users is 200. On the basis of ensuring the safety and reliability of the communication system, the 5G base station meets the requirements of multiple concurrency, large capacity, high speed and low delay wireless communication of coal mine business data.

Abstract: a large number of 5G base station are connected, which provides a new possibility for the future low-carbon development of power systems. By encouraging 5G base station to participate in demand response and incorporating it into the Microgrid, it can reduce the power consumption cost of 5G base stations and promote the efficient utilization of renewable energy. Based on the microgrid operation structure, 5G base station and multi-objective problem algorithm, a multi-objective optimization operation model of microgrid access to 5G base station is built. Considering the physical constraints of Microgrid, the objective is to minimize the operating cost and carbon emission. Through the joint dispatching of distributed clean energy generation, micro gas turbine, energy storage system and 5G base station in Microgrid, the comprehensive optimization of system economy and low-carbon benefits can be achieved. In this paper, a microgrid in Beijing is taken as the research object, and the Whale Optimization Algorithm algorithm is used to solve the multiobjective problem. The analysis results show that 5G base station can flexibly respond to microgrid scheduling, which helps microgrid to improve the consumption and utilization efficiency of renewable energy, thus bringing higher economic benefits and low-carbon benefits, and helping China to achieve the goal of carbon peak shaving and carbon neutrality at an early date.

A differential dual‐polarized patch antenna with broadband, high isolation, and low cross‐polarization level for 5G base station is presented. The antenna is composed of the radiating element, feeding structure, and reflector. The radiating element is designed with four identical smaller quasi‐trapezoidal patches to achieve a wider bandwidth, which is capacitively driven by two trapezoidal feeding patches. Impedance matching of antennas can be adjusted by tuning the size of quasi‐trapezoidal patches in the feeding portion. Finally, a prototype antenna is fabricated based on the simulated model. The measured bandwidth of the proposed antenna is about 27.8% (3.19–4.22 GHz) with VSWR<1.5, and the port isolation is better than 39.5 dB over the whole operating band. Furthermore, the proposed antenna has a stable gain of 8.55 ± 0.8 dBi and a low cross‐polarization level (<−33 dB) within the operating band. [ABSTRACT FROM AUTHOR]

The Active Antenna Unit (AAU) on the outdoor tower is the key equipment to support the mobile communication of 5G. To suppress the overheating of AAU in summer, effective cooling measures are essential. In the present study, a numerical model of an AAU device with two chips in the outdoor environment was established to explore the surface temperature distribution under a coupling heat transfer process with natural convection and solar radiation was obtained. Moreover, the effects of the fin number, the fin height and the heat flux were discussed on the cooling performance. The results proved that the fins with a number of 12 presented the best cooling performance in this paper. By contrast, increasing the height of fins was still an effective way to improve the cooling performance of fins in outdoor conditions and to resist the thermal shock of chips. Besides, punching through holes on the fins, adding graphite heat spreader and reducing surface emissivity are effective ways to improve the cooling performance. After the optimizations, the maximum temperature decreased by 3.5°C in total. In other words, the contribution of these optimizations to the cooling performance was equivalent to an increase of fin height in 9 mm. [ABSTRACT FROM AUTHOR]

The basic architecture of 5G wireless communication system in coal mine is proposed: 5G core network, base band unit (BBU), remote radio unit hub (RHUB) and 5G base station are connected by 5G bearer network to realize signaling transmission among network elements. Underground 5G base stations and antenna are used to realize underground wireless signal coverage. After the base stations are converged through a RHUB, they are connected to BBU and connected to the 5G core network. The advantages and disadvantages of two kinds of 5G core network construction schemes are compared, namely user plane function/mobile edge computing (UPF/MEC) sinking and independent private network. This paper studies the bearer networks between 5G core network and BBU, between BBU and RHUB, between RHUB and 5G base station. This study focuses on the characteristics and application scenes of the three bearing methods commonly used in the bearer network between the 5G core network and the BBU, namely the optical fiber direct connection, the slicing packet network (SPN) and the 5th generation fixed network (F5G). The design schemes of coal mine 5G base stations, 5G terminals and 5G communication modules are proposed. Combining the characteristics of 5G communication technology and the requirements of coal mine intelligence development, the typical applications of 5G wireless communication systems in coal mines are discussed, such as integrated communication, high-bandwidth service applications, intelligent working face service application, remote control of mining vehicles or unmanned driving, etc. It is pointed out the further optimization directions of the coal mine 5G wireless communication system, including the design of miniaturization industry 5G core network, the low-power and intrinsically safe design of coal mine 5G base stations and other equipment, the underground application of 5G equipment in the 700 MHz frequency band to improve the coverage of 5G base stations, the customization of coal mine 5G mobile terminals and the development of industry APPs, the development of low-power 5G communication modules, industry application scenes in combination with on-site needs, etc.

The uncertainty of renewable energy necessitates reliable demand response (DR) resources for power system auxiliary regulation. Meanwhile, the widespread deployment of energy-consuming 5G base stations (gNBs) drives internet service providers (ISPs) to seek energy expenses reduction. This paper intelligently addresses these two complementary needs by integrating gNBs into the power system dynamic economic dispatch (DED). To achieve this, a combined DED model that incorporates both the power system and 5G communication network is developed, where numerous distributed gNBs and their backup energy storage systems (BESSs) are integrated as a virtual power plant (VPP) to offer power support and obtain economic incentives. Instead of traditional optimization methods, the combined DED model is solved by a cooperative game-based solution method in a benefit-balanced manner, facilitating the power system and 5G network to achieve a win-win DED solution. This method comprises a two-stage game model and a solution algorithm based on improved random drift particle swarm optimization (RDPSO). The improved RDPSO constructs an uncertainty set in each iteration, facilitating its solution of stochastic optimization involving power system uncertainties. Lastly, a VPP management function is developed within the 5G core network (5GC) to efficiently evaluate the VPP's dispatchable capacity and formulate optimal control policies that can minimize control costs. Simulations based on the IEEE 118-bus system and real device data demonstrate that the proposed method can simultaneously reduce the power system's operating costs and increase the ISP's economic revenue. • Addressing complementary needs by integrating gNBs into power system DED. • Game-based solution for DED balancing supply and demand sides benefits. • Improved RDPSO algorithm for power system DED considering uncertainties. • VPP function efficiently evaluating dispatchable capacity and formulating optimal control policy. • Economic and technical win-win results in simulation based on real data. [ABSTRACT FROM AUTHOR]

This paper proposes an electric load demand model of the 5th generation (5G) base station (BS) in a distribution system based on data flow analysis. First, the electric load model of a 5G BS is developed according to its components and their characteristics. Second, critical factors of the power consumption of 5G BS, including area, data flow with uncertainty number of activated terminals and data usage of the terminal, are discussed. A statistical model of the number of activated terminals and data usage of the terminal are established using a probability distribution, and Monte Carlo sampling is used to handle the uncertainties. Then, the model is extended for multiple terminal connections. A case study is conducted to analyze the impact of the critical factors on the load of 5G BS and the influence of 5G BSs load on the other loads in three typical areas. Numerical results demonstrate that the proposed model is effective and can be employed as an accurate representation of the 5G BS load profile for the analysis of load characteristics. Case studies also show that the 5G BS loads have diverse impact on different typical areas in a distribution system. [ABSTRACT FROM AUTHOR]

The 5G communication system used in coal mines must obtain a safety mark certificate. In order to better promote the intelligent construction of coal mines and the development of 5G technology in coal mines, help the companies to understand the technical requirements of coal mine 5G communication system and inspection requirements in advance, shorten the review period, this paper studies the safety technical requirements and inspection methods of coal mine 5G communication system. The safety technical requirements of coal mine 5G communication systems are discussed in terms of basic requirements, networking requirements, 5G communication technology requirements, explosion-proof safety requirements and anti-interference requirements. Moreover, relevant suggestions are made for the issues that need to be focused on. In terms of the coal mine 5G communication system, this paper focuses on the system networking mode discrimination, core network inspection and anti-interference performance inspection. In terms of 5G base stations and terminals, this paper focuses on the inspection of 5G technical indicators and explosion-proof safety requirements. The issues such as coal mine 5G communication system management issues, 5G base station multi-antenna power superposition threshold power calculation issues, anti-interference technical difficulties, the technical requirements and inspection methods of transmission rate and delay, the inspection of antenna-integrated base stations, and the problems of 5G upstream and downstream bandwidth in mines are also discussed in this paper.

In this article, a concept of a phased antenna array based on substrate integrated waveguide (SIW) technology for 5G base stations is proposed. The array has a cosecant radiation pattern in the vertical plane for uniform illumination in a sector area. The array itself consists of 16 SIW traveling wave subarrays of 12 slot-coupled microstrip patch antennas associated with a pair of reflection-canceling vias and phasing elements to get the tapered distribution both in amplitude and phase for the cosecant-shaped radiation pattern. The array is designed to be operational at 28 GHz with a bandwidth of more than 10%, a candidate mm-wave frequency band for 5G. The phased antenna array supports wide-angle scanning of +/−60° in azimuth and exhibits good active impedance properties. The array design is successfully verified experimentally. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This work presents a wideband hybrid-fed ±45º linear dual-polarized patch antenna design for sub6 GHz 5G base stations. Two polarizations are created by a slot-coupling with rectangular H-slot (+45) and a capacitive coupling with modified L-probe (−45). Antenna exhibits wideband −10 dBimpedance bandwidths of 40.7% and 35.6% for slot-fed and probe-fed ports, respectively. Due to the special design of suspended stacked patches with hybrid-fed excitations, high port isolation (< −47 dB) and high cross-polar discrimination (> 38 dB) are achieved. Symmetric and directional radiation patterns with stable gain are obtained in E and H planes for each polarization. Compared to its bandwidth, antenna is low-profile (10.6 mm) with front-to-back ratio greater than 22 dB. Simulations and experimental results are reported and discussed. [ABSTRACT FROM AUTHOR]

For time and space constraints, 5G base stations will have more serious energy consumption problems in some time periods, so it needs corresponding sleep strategies to reduce energy consumption. Based on the analysis of 5G super dense base station network structure, through the analysis of current situation and user demand, a cluster sleep method based on genetic algorithm is constructed under the support of genetic algorithm, which can realize the dynamic matching of energy consumption in time domain and space, and the low load base station enters the sleep state. In order to verify the performance of the algorithm, the simulation network structure is built on the MATLAB platform, and the advantages of the algorithm in this study are obtained through comparative analysis, and the relevant test parameters are set for the technical performance analysis of this study. The research shows that the method proposed in this paper has a certain energy-saving effect, can meet the energy efficiency requirements of 5G ultra dense base station, and in the ultra dense base station group, the complexity can also meet the system operation requirements, which has a certain degree of practicality, and can provide reference for the follow-up related research.