Register Allocation Compilation Technique for ASIP in 5G Micro Base Stations

The currently available compilation techniques are for general computing and are not optimized for physical layer computing in 5G micro base stations.In such cases,the foreseeable data sizes and small code size are application specific opportunities for baseband algorithm optimizations.Therefore,the special attention can be paid,for example,the specific register allocation algorithm has not been studied so far.The compilation for kernel sub-routines of baseband in 5G micro base stations is our focusing point.For applications of known and fixed data size,we proposed a compilation scheme of parallel data accessing,while operands can be mainly allocated and stored in registers.Based on a small register group(48×32b),the target of our compilation scheme is the optimization of baseband algorithms based on 4×4 or smaller matrices,maximizing the utilization of register files,and eliminating the extra register data exchanging.Meanwhile,when data is allocated into register files,we used VLIW(Very Long Instruction Word)machine to hide the time of data accessing and minimize the cost of data accessing,thus the total execution time is minimum.Experiments indicate that for algorithms with small data size,the cost of data accessing and extra addressing can be minimized.

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.

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.

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.

Practical Non-Uniform Channelization for Multistandard Base Stations

A multistandard software-defined radio base station must perform non-uniform channelization of multiplexed frequency bands. Non-uniform channelization accounts for a significant portion of the digital signal processing workload in the base station receiver and can be difficult to realize in a physical implementation. In non-uniform channelization methods based on generalized DFT filter banks, large prototype filter orders are a significant issue for implementation. In this paper, a multistage filter design is applied to two different non-uniform generalized DFT-based channelizers in order to reduce their filter orders. To evaluate the approach, a TETRA and TEDS base station is used. Experimental results show that the new multistage design reduces both the number of coefficients and operations and leads to a more feasible design and practical physical implementation.

A Broadband45°Dual-Polarized Multiple-Input Multiple-Output Antenna for 5G Base Stations with Extra Decoupling Elements

A dual-polarized multiple-input multiple-output(MIMO)antenna is proposed for 5G base stations.Each antenna element consists of two orthogonally placed fan-shaped dipole elements and45°dual-polarized feed-ing structures are used to achieve broadband operation.The resonant frequency of the array element is from 3.3 to 4.2 GHz,which covers the mainstream spectrum allocations of 5G mobile networks.H-shaped coupling elements are used to improve the isolation between the neighboring antenna elements and the mutual coupling is reduced by over 4 dB.The envelope correlation of a 2×2 array is provided for verification.

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.

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.

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.

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.

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.

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.

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.

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.

On selecting transmission mode for D2D transmitter in underlay cellular network with a multi-antenna base station

The Device-to-Device(D2D)communication underlaying cellular networks is considered in this study.The D2D transmitter in the D2D mode can directly transmit messages to a receiver,but it may interfere with the transmission of another cellular user who shares the same uplink channel.The transmitter can also operate in a cellular mode in which no interference to another cellular user occurs.We propose a mode selection scheme that aims to minimize the transmission power of the D2D transmitter subject to constraints on the minimum required data rate and maximum interference to other cellular users.The proposed scheme is based on bounds for transmission power and is less complex than the optimal scheme.Furthermore,it requires only a few statistics and does not need a fading channel distribution.The performance of the scheme is close to optimum when the number of Base Station(BS)antennas is large,and the mean absolute deviation of the fading terms is small.We verify this with numerical results of the Rician and Rayleigh fading channels by assuming that the BS antennas are independent.The simulation results for the two correlated BS antennas are presented herein.

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.