Muti-Fusion Swarm Intelligence Optimization Algorithm in Base Station Coverage Optimization Problems

As millimeter waves will be widely used in the Internet of Things(IoT)and Telematics to provide high bandwidth communication and mass connectivity,the coverage optimization of base stations can effectively improve the quality of communication services.How to optimize the convergence speed of the base station coverage solution is crucial for IoT service providers.This paper proposes the Muti-Fusion Sparrow Search Algorithm(MFSSA)optimize the situation to address the problem of discrete coverage maximization and rapid convergence.Firstly,the initial swarm diversity is enriched using a sine chaotic map,and dynamic adaptive weighting is added to the discoverer location update strategy to improve the global search capability.Diverse swarms have a more remarkable ability to forage for food and avoid predation and are less likely to fall into a“precocious”state.Such a swarm is very suitable for solving NP-hard problems.Secondly,an elite opposition-based learning strategy is added to expand the search range of the algorithm,and a t-distribution-based one-fifth rule is introduced to reduce the probability of falling into a local optimum.This fusion mutation strategy can significantly optimize the adaptability and searchability of the algorithm.Finally,the experimental results show that the MFSSA algorithm can effectively improve the coverage of the deployment scheme in the base station coverage optimization problem,and the convergence speed is better than other algorithms.MFSSA is improved by more than 10%compared to the original algorithm.

An Enhanced Group Key-Based Security Protocol to Protect 5G SON Against FBS

Network operators are attempting many innovations and changes in 5G using self-organizing networks(SON).The SON operates on the measurement reports(MR),which are obtained from user equipment(UE)and secured against malware and userspace programs.However,the synchronization signal block that the UE relies on to measure the wireless environment configured by a base station is not authenticated.As a result,the UE will likely gauge the wrong wireless environment configured by a false base station(FBS)and transmit the corresponding MR to the serving base station,which poisons the data used for 5G SONs.Therefore,the serving base stations must verify the authenticity of the MR.The 3GPP has advocated numerous solutions for this issue,including the use of public key certificates,identity-based keys,and group keys.Although the solution leveraging group keys have better efficiency and practicality than the other two,they are vulnerable to security threats caused by key leaks via insiders or malicious UE.In this paper,we analyze these security issues and propose an improved group key protocol that uses a new network function,called a broadcast message authentication network function(BMANF),which validates broadcasted messages on behalf of the UE.The protocol operates in two phases:initial and verification.During the initial phase,the 5G core network distributes a shared secret key to the BMANF and UE,allowing the latter to request an authentication ticket from the former.During the verification phase,the UE requests the BMANF to validate the broadcasted messages received from base stations using the ticket and its corresponding shared key.For evaluation,we formally verified the proposed protocol,which was then compared with alternative methods in terms of computing cost.As a result,the proposed protocol fulfills the security requirements and shows a lower overhead than the alternatives.

Base Station Energy Management in 5G Networks Using Wide Range Control Optimization

The traffic activity offifth 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.

多变点检测问题的Shape-based BS算法

BS算法是时间序列多变点检测中最经典的算法之一,但是基于全局CUSUM统计量的识别过程会带来过多误判和较高的时间复杂度.BS算法是一种离线的序贯方法,因此没有充分利用数据的时序信息;另一方面,BS算法识别变点的原则是CUSUM统计量最大化,也没有考虑统计量构成序列的形态特性.鉴于此,提出一种基于局部形态识别的BS改进算法,命名为Shape-based BS算法.基于局部形态识别统计量,不仅大大降低计算复杂度,且降低了因变点间的互相干扰而带来的误判率,进而提升变点识别的稳健性.最后,将此算法应用到了电力系统的"场景压缩"问题上,具有满意的实用效果.

Probe Selection for Over-the-Air Test in 5G Base Stations with Massive Multiple-Input Multiple-Output

In 5G systems, massive multiple-input multiple-output (MIMO) has been adopted in base stations (BSs) to improve spectral efficiency and coverage. The traditional conductive performance test techniques are challenging due to the unaffordable cost and high complexity when testing a large number of antennas. To solve this problem, the over-the-air (OTA) test has been presented, in which probe selection is the key to reduce the number of channel emulators and probes. In this paper, a novel artificial bee colony (ABC) algorithm is introduced to enhance the efficiency and accuracy of probe selection procedure. A sectoring- based multi-probe anechoic chamber (MPAC) is built to evaluate the throughput performance of massive MIMO equipped in 5G BS. In addition, link level simulation is carried out to evaluate the proposal’s performance gain under the commercial network assumptions, where the average throughput of three velocity is given with different SNR region. The results suggest that OTA chamber and multi-probe wall are available not only for 5G BSs, but also for user equipments (UEs) with end-to-end communication.

Optimal configuration for photovoltaic storage system capacity in 5G base station microgrids

Base station operators deploy a large number of distributed photovoltaics to solve the problems of high energy consumption and high electricity costs of 5G base stations.In this study,the idle space of the base station’s energy storage is used to stabilize the photovoltaic output,and a photovoltaic storage system microgrid of a 5G base station is constructed.Aiming at the capacity planning problem of photovoltaic storage systems,a two-layer optimal configuration method is proposed.The inner layer optimization considers the energy sharing among the base station microgrids,combines the communication characteristics of the 5G base station and the backup power demand of the energy storage battery,and determines an economic scheduling strategy for each photovoltaic storage system with the goal of minimizing the daily operation cost of the base station microgrid.The outer model aims to minimize the annual average comprehensive revenue of the 5G base station microgrid,while considering peak clipping and valley filling,to optimize the photovoltaic storage system capacity.The CPLEX solver and a genetic algorithm were used to solve the two-layer models.Considering the construction of the 5G base station in a certain area as an example,the results showed that the proposed model can not only reduce the cost of the 5G base station operators,but also reduce the peak load of the power grid and promote the local digestion of photovoltaic power.

Optimal configuration of 5G base station energy storage considering sleep mechanism

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.

Design and Implementation of Dynamic High-Speed Switches in Super Base Station Architectures

Novel centralized base station architectures integrating computation and communication functionalities have become important for the development of future mobile communication networks.Therefore,the development of dynamic high-speed interconnections between baseband units(BBUs)and remote radio heads(RRHs)is vital in centralized base station design.Herein,dynamic high-speed switches(HSSs)connecting BBUs and RRHs were designed for a centralized base station architecture.We analyzed the characteristics of actual traffic and introduced a switch traffic model suitable for the super base station architecture.Then,we proposed a data-priority-aware(DPA)scheduling algorithm based on the traffic model.Lastly,we developed the dynamic HSS model based on the OPNET platform and the prototype based on FPGA.Our results show that the DPA achieves close to 100%throughput with lower latency and provides better run-time complexity than iOCF and HE-iSLIP,thereby demonstrating that the proposed switch system can be adopted in centralized base station architectures.

RF Technologies and Challenges for Future MBR Systems in Cellular Base Stations

This paper describes the advances and features of future cellular base stations. Software defined radio （SDR） evolves to cognitive radio （CR）, which is smart and has wideband, and multiband radio （MBR） with reconfigurable wideband can be regarded as the basis of CR and an advanced level of SDR. Based on the SDR platform, several radio frequency （RF） solutions for implementing MBR systems are proposed, and some challenges to MBR implementation are discussed.

Interference Management for DS-CDMA Systems through Closed-Loop Power Control, Base Station Assignment, and Beamforming

In this paper, we propose a smart step closed-loop power control (SSPC) algorithm and a base station assignment method based on minimizing the transmitter power (BSA-MTP) technique in a direct sequence-code division multiple access (DS-CDMA) receiver with frequency-selective Rayleigh fading. This receiver consists of three stages. In the first stage, with constrained least mean squared (CLMS) algorithm, the desired users’ signal in an arbitrary path is passed and the inter-path interference (IPI) is reduced in other paths in each RAKE finger. Also in this stage, the multiple access interference (MAI) from other users is reduced. Thus, the matched filter (MF) can use for more reduction of the IPI and MAI in each RAKE finger in the second stage. Also in the third stage, the output signals from the matched filters are combined according to the conventional maximal ratio combining (MRC) principle and then are fed into the decision circuit of the desired user. The simulation results indicate that the SSPC algorithm and the BSA-MTP technique can significantly reduce the network bit error rate (BER) compared to the other methods. Also, we observe that significant savings in total transmit power (TTP) are possible with our methods.

Malicious Base Station and Detecting Malicious Base Station Signal

This paper introduces the background,illustrates the hardware structure and software features of malicious base station,explains its work principle,presents a method of detecting malicious base station,analyses the experiment and evaluates the experimental results to verify the reliability of this method.Finally proposes the future work.

Energy-Efficient Joint Content Caching and Small Base Station Activation Mechanism Design in Heterogeneous Cellular Networks

Heterogeneous cellular networks(HCNs), by introducing caching capability, has been considered as a promising technique in 5 G era, which can bring contents closer to users to reduce the transmission delay, save scarce bandwidth resource. Although many works have been done for caching in HCNs, from an energy perspective, there still exists much space to develop a more energy-efficient system when considering the fact that the majority of base stations are under-utilized in the most of the time. Therefore, in this paper, by taking the activation mechanism for the base stations into account, we study a joint caching and activation mechanism design to further improve the energy efficiency, then we formulate the optimization problem as an Integer Linear Programming problem(ILP) to maximize the system energy saving. Due to the enormous computation complexity for finding the optimal solution, we introduced a Quantum-inspired Evolutionary Algorithm(QEA) to iteratively provide the global best solution. Numerical results show that our proposed algorithm presents an excellent performance, which is far better than the strategy of only considering caching without deactivation mechanism in the actual, normal situation. We also provide performance comparison amongour QEA, random sleeping algorithm and greedy algorithm, numerical results illustrate our introduced QEA performs best in accuracy and global optimality.

Multibeam Antenna Based on Butler Matrix for 3G/LTE/5G/B5G Base Station Applications

With the rapid development of mobile communication technology and the explosion of data traffic,high capacity communication with high data transmission rate is urgently needed in densely populated areas.Since multibeam antennas are able to increase the communication capacity and support a high data transmission rate,they have attracted a lot of research interest and have been actively investigated for base station applications.In addition,since multi-beam antennas based on Butler matrix(MABBMs)have the advantages of high gain,easy design and low profile,they are suitable for base station applications.The purposes of this paper is to provide an overview of the existing MABBMs.The specifications,principles of operation,design method and implementation of MABBMs are presented.The challenge of MABBMs for 3G/LTE/5G/B5G base station applications is discussed in the end.

基于MBSE的月球科研站任务分析

月球探测完成“绕落回”三步走后,从单点短期探测向建设月面基础设施的月球科研站长期探测转变,给月球探测任务的规划论证、总体设计、系统研制和在轨探测等提出了更高要求。采用基于模型的系统工程(MBSE)思想,提出基于模型的月球科研站系统分析正向流程,以系统模型为载体深入剖析任务总体、任务使命需求和任务应用场景。通过开展基于模型的月球科研站任务分析,初步实现了月球科研站任务分析过程正向化、设计要素定义全量化、设计要素之间的关联表达显性化、月球科研站工程总体单位下发的研制要求有源化。

Multilevel Power Modeling of Base Station and Its ICs

A new power estimation method is proposed for base station(BS) in this paper.Based on this method,a software platform for power estimation is developed.The proposed method models power consumption on different abstraction levels by splitting a typical base station into several basic components at different levels in the view of embedded system design.In particular,our focus is on baseband IC(Integrate Circuit) due to it's the dominant power consumer in small cells.Baseband power model is based on arithmetic computing costs of selected algorithms.All computing and storage costs are calibrated using algorithm complexity,hardware architecture,activity ratio,silicon technology,and overheads on all hierarchies.Micro architecture and IC technology are considered.The model enables power comparison of different types of base stations configured with different baseband algorithms,micro architectures,and ICs.The model also supports cellular operators in power estimation of different deployment strategies and transmission schemes.The model is verified by comparing power consumption with a real LTE base station.By exposing more configuration freedoms,the platform can be used for power estimation of current and future base stations.

Energy Estimation and Optimization Platform for 4G and the Future Base Station System Early-Stage Design

There are already several power models to estimate the power consumption of base stations at system level. However, there is so far no model that can predict power consumption of the future base station designs based on algorithms and hardware selections with insufficient physical information. We present such an energy model for typical base stations. This model can help designers in estimating, evaluating and optimizing energy/power consumption of candidate designs in early design stages. The proposed model is verified by an LTE extreme scenario. The estimated results show that digital front-end, channel equalization and channel decoding are three major power greedy modules(consuming 39.4%, 16.3%, 13.4%) in a digital baseband subsystem. The power estimation error of the proposed power amplifier(PA) power model is 3.5%(macro cell). The major contribution of this paper is that the proposed models can rapidly estimate energy/power consumption of 4G and the future base stations(such as 5G) in early design stages with well acceptable precision, even without sufficient implementation information.

Rule Based Collector Station Selection Scheme for Lossless Data Transmission in Underground Sensor Networks

There are fundamentally two different communication media in wireless underground sensor networks. The first of these is a solid medium where the sensor nodes are buried underground and wirelessly transmit data from underground to aboveground. The second is an underground medium such as tunnel, cave etc. and the data is transmitted from underground to the aboveground through partially solid medium. The quality of communication is greatly influenced by the humidity of the soil in both environments. The placement of wireless underground sensor nodes at hard-to-reach locations makes energy efficient work compulsory. In this paper, rule based collector station selection scheme is proposed for lossless data transmission in underground sensor networks. In order for sensor nodes to transmit energy-efficient lossless data, rulebased selection operations are carried out with the help of fuzzy logic. The proposed wireless underground sensor network is simulated using Riverbed software, and fuzzy logic-based selection scheme is implemented utilizing Matlab software. In order to evaluate the performance of the sensor network;the parameters of delay, throughput and energy consumption are investigated. Examining performance evaluation results, it is seen that average delay and maximum throughput are accomplished in the proposed underground sensor network. Under these conditions, it has been shown that the most appropriate collector station selection decision is made with the aim of minimizing energy consumption.

Effects of Exposure to GSM Mobile Phone Base Station Signals on Salivary Cortisol,Alpha-Amylase,and Immunoglobulin A

Objective The present study aimed to test whether exposure to radiofrequency electromagnetic fields （RF-EMF） emitted by mobile phone base stations may have effects on salivary alpha-amylase, immunoglobulin A （IgA）, and cortisol levels. Methods Fifty seven participants were randomly allocated to one of three different experimental scenarios （22 participants to scenario 1, 26 to scenario 2, and 9 to scenario 3）. Each participant went through five 50-minute exposure sessions. The main RF-EMF source was a GSM-900-MHz antenna located at the outer wall of the building. In scenarios 1 and 2, the first, third, and fifth sessions were ＂low＂ （median power flux density 5.2 μW/m^2） exposure. The second session was ＂high＂ （2126.8 μW/m^2）, and the fourth session was ＂medium＂ （153.6 μW/m^2） in scenario 1, and vice versa in scenario 2. Scenario 3 had four ＂low＂ exposure conditions, followed by a ＂high＂ exposure condition. Biomedical parameters were collected by saliva samples three times a session. Exposure levels were created by shielding curtains. Results In scenario 3 from session 4 to session 5 （from ＂low＂ to ＂high＂ exposure）, an increase of cortisol was detected, while in scenarios 1 and 2, a higher concentration of alpha-amylase related to the baseline was identified as compared to that in scenario 3. IgA concentration was not significantly related to the exposure. Conclusions RF-EMF in considerably lower field densities than ICNIRP-gnidelines may influence certain psychobiological stress markers.

Analysis of Lightning Disaster of Eight Mobile Base Stations in a County Suffering Thunderstorm on June 23,2015 and Countermeasures

During the process of thunderstorm in a county on June 23,2015,eight mobile base stations in the region were damaged.The reasons for the damage caused by the thunderstorm were discussed through on-the-spot investigation,and some countermeasures were proposed.