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.

Location correction technique based on mobile communication base station for earthquake population heat map

China has mobile phone penetration rate of over 96.2%.Mobile phone has become the largest Internet terminal for Chinese Internet users.Population geographic distribution in earthquake zones can be got based on mobile phone positioning and map matching.For reducing earthquake black-box stage,we propose a real-time collection,correction and schedule algorithm of population position data by four stream processing environments(Redis,Hbase,Kafka,and Spark Streaming)in this paper.For labeling precisely population geographic distribution on the network map,matching of population geographic coordinates and map coordinates are optimized by sample comparison based on location data of mobile communication base stations and prefecture level cities.The test result shows the proposed system is high efficient and can rapidly respond to any emerging parallel tasks during the earthquake.A high-precision heat map of affected population can be produced and published on-line within 2 min after the devastating earthquake happened.

SMDP-based sleep policy for base stations in heterogeneous cellular networks

A dense heterogeneous cellular network can effectively increase the system capacity and enhance the network coverage.It is a key technology for the new generation of the mobile communication system.The dense deployment of small base stations not only improves the quality of network service,but also brings about a significant increase in network energy consumption.This paper mainly studies the energy efficiency optimization of the Macro-Femto heterogeneous cellular network.Considering the dynamic random changes of the access users in the network,the sleep process of the Femto Base Stations(FBSs)is modeled as a Semi-Markov Decision Process(SMDP)model in order to save the network energy consumption.And further,this paper gives the dynamic sleep algorithm of the FBS based on the value iteration.The simulation results show that the proposed SMDP-based adaptive sleep strategy of the FBS can effectively reduce the network energy consumption.

Source localization based on field signatures:Laboratory ultrasonic validation

Location awareness in wireless networks is essential for emergency services,navigation,gaming,and many other applications.This article presents a method for source localization based on measuring the amplitude-phase distribution of the field at the base station.The existing scatterers in the target area create unique scattered field interference at each source location.The unique field interference at each source location results in a unique field signature at the base station which is used for source localization.In the proposed method,the target area is divided into a grid with a step of less than half the wavelength.Each grid node is characterized by its field signature at the base station.Field signatures corresponding to all nodes are normalized and stored in the base station as fingerprints for source localization.The normalization of the field signatures avoids the need for time synchronization between the base station and the source.When a source transmits signals,the generated field signature at the base station is normalized and then correlated with the stored fingerprints.The maximum correlation value is given by the node to which the source is the closest.Numerical simulations and results of experiments on ultrasonic waves in the air show that the ultrasonic source is correctly localized using broadband field signatures with one base station and without time synchronization.The proposed method is potentially applicable for indoor localization and navigation of mobile robots.

A long-term-based handover decision algorithm for dense macro-femto coexistence networks

For the dense macro-femto coexistence networks scenario, a long-term-based handover（LTBH） algorithm is proposed. The handover decision algorithm is jointly determined by the angle of handover（AHO） and the time-tostay（TTS） to reduce the unnecessary handover numbers.First, the proposed AHO parameter is used to decrease the computation complexity in multiple candidate base stations（CBSs） scenario. Then, two types of TTS parameters are given for the fixed base stations and mobile base stations to make handover decisions among multiple CBSs. The simulation results show that the proposed LTBH algorithm can not only maintain the required transmission rate of users, but also effectively reduce the unnecessary numbers of handover in the dense macro-femto networks with the coexisting mobile BSs.

Node deployment strategy optimization for wireless sensor network with mobile base station

The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.

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.

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.

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.

Design of intelligent detecting system based on wireless transmission

An intelligent detecting system based on wireless transmission is designed. Its hardware includes the card reading module, the wireless digital transmission module, the LCD module, the random password keyboard module and a 16×16 lattice word database based on e-Flash MM36SB020. Its software is a communication protocol between the central control computer and the entrance management base station. To resolve the conflicting problems occurred during the data transmission, a method of delaying time at random is proposed.

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.

A Path-Based Approach for Data Aggregation in Grid-Based Wireless Sensor Networks

Sensor nodes in a wireless sensor network （WSN） are typically powered by batteries, thus the energy is constrained. It is our design goal to efficiently utilize the energy of each sensor node to extend its lifetime, so as to prolong the lifetime of the whole WSN. In this paper, we propose a path-based data aggregation scheme （PBDAS） for grid-based wireless sensor networks. In order to extend the lifetime of a WSN, we construct a grid infrastructure by partitioning the whole sensor field into a grid of cells. Each cell has a head responsible for aggregating its own data with the data sensed by the others in the same cell and then transmitting out. In order to efficiently and rapidly transmit the data to the base station （BS）, we link each cell head to form a chain. Each cell head on the chain takes turn becoming the chain leader responsible for transmitting data to the BS. Aggregated data moves from head to head along the chain, and finally the chain leader transmits to the BS. In PBDAS, only the cell heads need to transmit data toward the BS. Therefore, the data transmissions to the BS substantially decrease. Besides, the cell heads and chain leader are designated in turn according to the energy level so that the energy depletion of nodes is evenly distributed. Simulation results show that the proposed PBDAS extends the lifetime of sensor nodes, so as to make the lifetime of the whole network longer.

RSS-Based Selective Clustering Technique Using Master Node for WSN

Wireless sensor networks(WSN)are designed to monitor the physical properties of the target area.The received signal strength(RSS)plays a significant role in reducing sensor node power consumption during data transmission.Proper utilization of RSS values with clustering is required to harvest the energy of each network node to prolong the network life span.This paper introduces the RSS-based energy-efficient selective clustering technique using a master node(RESCM)to improve energy utilization using a master node.The master node positioned at the center of the network area and base station(BS)is placed outside the network area.During cluster head(CH)selection,the node with a high RSS value is more likely to become CH.The network is divided into segments according to the distance from the master node.All nodes near BS or master node transmit their data using direct transmission without the clustering process.The simulation results showed that the RESCM method improves the total network lifespan effectively.

TDOA based assisted GNSS positioning algorithm

In order to improve the location performance of User Equipment (UE) , enhance the availability of satellites navigation systems, an assisted Global Navigation Satellite System (GNSS) positioning algorithm based on Time Difference of Arrival (TDOA) technology is proposed for only three visible satellites in this paper. Using the structure of assisted satellite position system, UE was guaranteed to acquire navigation information of the three visible satellites rapidly, and three satellite observation equation were acquired, then the arrival time difference between UE and two adjacent base stations was used as an auxiliary, and a full-rank equation was constructed to achieve positioning by least squares method. The results showed that the algorithm had good convergence ability and positioning accuracy, and the confidence of this method's positioning error, according to 3GPP request of assisted satellite navigation accuracy error within 50 m, reaches 94.56%, the average positioning accuracy was 16.8 m. The validity of this algorithm was demonstrated.

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.

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.

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.

General Galois Processor for Transmitters in 5G/6G Base Stations

This paper proposes a flexible eight-mode high parallel Galois SIMD ASIP(Application Specific Instruction Set Processor).It supports parallel executions of Gold,Scrambling,CRC,CC,Turbo,RM,PSS,SSS encoding LFSR(linear feedback shift registers)algorithms with high performance and flexibility.It can perform also general bit processing and m-sequence.Our design is based on proposed table conversion and a datapath for unified eight-mode encoding.Based on 28 nm digital CMOS technology,the total area is 0.177 mm2 and the clock frequency can be up to 1 GHz.The throughputs of Gold,Scrambling,CRC32,CRC24,CRC16,CRC8,CC,Turbo are 64 Gb/s,64 Gb/s,128 Gb/s,168 Gb/s,256 Gb/s,512 Gb/s,3×80 Gb/s,and 72 Gb/s,respectively.

Switching Delay Aware Computing Resource Allocation in Virtualized Base Station

In centralized cellular network architecture,the concept of virtualized Base Station(VBS) becomes attracting since it enables all base stations(BSs) to share computing resources in a dynamic manner. This can significantly improve the utilization efficiency of computing resources. In this paper,we study the computing resource allocation strategy for one VBS by considering the non-negligible effect of delay introduced by switches. Specifically,we formulate the VBS's sum computing rate maximization as a set optimization problem. To address this problem,we firstly propose a computing resource schedule algorithm,namely,weight before one-step-greedy(WBOSG),which has linear computation complexity and considerable performance. Then,OSG retreat(OSG-R) algorithm is developed to further improve the system performance at the expense of computational complexity. Simulation results under practical setting are provided to validate the proposed two algorithms.