Mobility KPI definition based on 3GPP TS 32.450 and 32.45.
Conditions for source & target cell to increment performance counter during S1 HO procedure
Conditions for source & target cell to increment performance counter during X2 HO procedure
The document describes a localization system that uses sensor fusion with a Kalman filter. It inputs gyroscope and GPS data. It predicts position and heading by integrating velocity and yaw rate data. The GPS and gyroscope data are then fused using Kalman filters to update the position and heading estimates. This provides updated heading angle, latitude, longitude, and velocity outputs with improved accuracy compared to either sensor alone.
Optimizing the Grafana Platform for FluxInfluxData
Flux, the new InfluxData Data Scripting Language (formerly IFQL), super-charges queries both for analytics and data science. Matt will give a quick overview of the language features as well as the moving parts for a working deployment. Grafana is an open source dashboard solution that shares Flux’s passion for analytics and data science. For that reason, they are very excited to showcase the new Flux support within Grafana, and a couple of common analytics use cases to get the most out of your data.
In this talk, Matt Toback from Grafana Labs will share the latest updates they have made with their Flux builder in Grafana.
Paul will outline his vision around the platform and give the latest updates on Flux (a new query language), the decoupling of query and storage, the impact of hybrid cloud environments on architecture, cardinality, and discuss the technical directions of the platform. This talk will walk through the vision and architecture with demonstrations of working prototypes of the projects.
The document summarizes changes to flight plan content and format implemented in 2012, including:
- Item 10 was expanded to include additional equipment/capability descriptors up to 20 characters
- Item 18 order was changed and new data fields were added, such as 24 PBN descriptors and 13 special handling codes
- Maximum en route delay or holding time in Item 18 DOF was increased to 120 hours
This report summarizes the results of a single site verification test for a Wi tribe LTE TDD project. Key findings include:
1) Throughput targets were met or exceeded at near points for all sectors, with averages of 68.1-77.7 Mbps downlink and 7.6-10.4 Mbps uplink.
2) Far point throughput was lower as expected but still met requirements, with averages of 30.4-39.6 Mbps downlink and 2-9.6 Mbps uplink.
3) Latency was below targets, with averages of 46-548 ms for 32 byte and 46 ms for 128 byte tests.
4) KPI targets for R
- There are three primary tanker markets: petroleum (crude oil and refined products), gas, and chemicals.
- The petroleum market carries crude oil and refined products like gasoline. It is the largest market.
- The gas market carries liquefied natural gas via specialized gas carriers between production and regasification facilities.
- The chemical market carries organic and vegetable based chemicals on specialized tankers.
EPOSA - real time positioning in austriaRobert Karas
description of the eposa-network of austria, we work with gps and glonass simultaneously, homogeneous accuracy throughout austria, http://www.eposa.at, made in 2012
The document describes a localization system that uses sensor fusion with a Kalman filter. It inputs gyroscope and GPS data. It predicts position and heading by integrating velocity and yaw rate data. The GPS and gyroscope data are then fused using Kalman filters to update the position and heading estimates. This provides updated heading angle, latitude, longitude, and velocity outputs with improved accuracy compared to either sensor alone.
Optimizing the Grafana Platform for FluxInfluxData
Flux, the new InfluxData Data Scripting Language (formerly IFQL), super-charges queries both for analytics and data science. Matt will give a quick overview of the language features as well as the moving parts for a working deployment. Grafana is an open source dashboard solution that shares Flux’s passion for analytics and data science. For that reason, they are very excited to showcase the new Flux support within Grafana, and a couple of common analytics use cases to get the most out of your data.
In this talk, Matt Toback from Grafana Labs will share the latest updates they have made with their Flux builder in Grafana.
Paul will outline his vision around the platform and give the latest updates on Flux (a new query language), the decoupling of query and storage, the impact of hybrid cloud environments on architecture, cardinality, and discuss the technical directions of the platform. This talk will walk through the vision and architecture with demonstrations of working prototypes of the projects.
The document summarizes changes to flight plan content and format implemented in 2012, including:
- Item 10 was expanded to include additional equipment/capability descriptors up to 20 characters
- Item 18 order was changed and new data fields were added, such as 24 PBN descriptors and 13 special handling codes
- Maximum en route delay or holding time in Item 18 DOF was increased to 120 hours
This report summarizes the results of a single site verification test for a Wi tribe LTE TDD project. Key findings include:
1) Throughput targets were met or exceeded at near points for all sectors, with averages of 68.1-77.7 Mbps downlink and 7.6-10.4 Mbps uplink.
2) Far point throughput was lower as expected but still met requirements, with averages of 30.4-39.6 Mbps downlink and 2-9.6 Mbps uplink.
3) Latency was below targets, with averages of 46-548 ms for 32 byte and 46 ms for 128 byte tests.
4) KPI targets for R
- There are three primary tanker markets: petroleum (crude oil and refined products), gas, and chemicals.
- The petroleum market carries crude oil and refined products like gasoline. It is the largest market.
- The gas market carries liquefied natural gas via specialized gas carriers between production and regasification facilities.
- The chemical market carries organic and vegetable based chemicals on specialized tankers.
EPOSA - real time positioning in austriaRobert Karas
description of the eposa-network of austria, we work with gps and glonass simultaneously, homogeneous accuracy throughout austria, http://www.eposa.at, made in 2012
The document discusses the X2 interface and X2 handover procedure in LTE networks. The X2 interface connects two neighboring eNodeBs and establishes an X2 connection through the X2 setup procedure. The X2 handover procedure allows handing over a UE's connection from a source eNodeB to a target eNodeB, involving preparation where the target allocates resources and the UE connects to it, and execution including a path switch to route data to the target eNodeB. Key information like UE context and bearers is exchanged between eNodeBs through the X2 interface to enable smooth handover.
The document describes an eNodeB handover procedure between two eNodeBs connected to the same MME without S-GW relocation. It involves a handover preparation phase where the source eNodeB requests admission control from the target eNodeB. In the handover execution phase, the UE detaches from the old cell and synchronizes to the new cell. Finally, in the handover completion phase, the bearers are modified and the source eNodeB releases the UE context.
The document describes a release with redirect call flow in LTE. It involves the following key steps:
1. The UE sends a measurement report to the eNodeB indicating bad coverage.
2. The eNodeB sends a connection release message with redirect to the UE, causing it to search for a new cell in 2G/3G.
3. The UE re-establishes data flow on the new 2G/3G cell while the LTE connection is released and set to idle state. Downlink and uplink traffic is possible during the handover process.
This document provides an overview of the key components and protocols in 3G and 4G mobile networks. It includes a high-level diagram of the overall 4G architecture and summaries of protocols like S1, X2, NAS, RRC. Key concepts covered include the PDCP, RLC, MAC and PHY layers, QoS classes, paging, attachment, handover procedures between eNodeBs and between 4G and 3G networks.
This document provides a summary of key concepts in LTE network architecture and protocols:
1) It describes the LTE network architecture including nodes like the eNB, MME, S-GW and P-GW as well as interfaces like S1, S3, S6a and S11.
2) It explains the protocol stack used in the UE and network, covering layers like PDCP, RLC, MAC and PHY.
3) It outlines the main software blocks and functions of the eNB including call processing, O&M, and packet forwarding.
Chap 4. call processing and handover.engsivakumar D
This document provides a 3-sentence summary of the key information:
The document outlines the network architecture and protocol stacks used in LTE networks, including components like the UE, eNB, MME, S-GW and P-GW. It describes the software architecture of eNBs and the call processing blocks. It also summarizes several important procedures in LTE networks like attach, detach, handover, and basic parameter configuration.
The document discusses key performance indicators (KPIs) for the E-UTRAN and EPC components of an LTE network, including accessibility, retainability, integrity, availability, and mobility metrics for E-UTRAN and accessibility, mobility, and utilization KPIs for EPC. It provides definitions and formulas for calculating various KPIs related to EPS attach success rate, dedicated bearer creation success rate, handover success rates, and other measures of network and service performance.
Taking Security Groups to Ludicrous Speed with OVS (OpenStack Summit 2015)Thomas Graf
Open vSwitch (OVS) has long been a critical component of the Neutron's reference implementation, offering reliable and flexible virtual switching for cloud environments.
Being an early adopter of the OVS technology, Neutron's reference implementation made some compromises to stay within the early, stable featureset OVS exposed. In particular, Security Groups (SG) have been so far implemented by leveraging hybrid Linux Bridging and IPTables, which come at a significant performance overhead. However, thanks to recent developments and ongoing improvements within the OVS community, we are now able to implement feature-complete security groups directly within OVS.
In this talk we will summarize the existing Security Groups implementation in Neutron and compare its performance with the Open vSwitch-only approach. We hope this analysis will form the foundation of future improvements to the Neutron Open vSwitch reference design.
The document summarizes the key procedures and signaling flows involved in setting up an LTE session for a UE:
1) The UE establishes an RRC connection with the eNodeB through random access and preamble signaling.
2) The UE then attaches to the core network through the MME, which also handles authentication.
3) Finally, the default bearer is established through signaling between the UE, eNodeB, MME, SGW and PGW, allowing user data transfer.
The document discusses self-optimization techniques for 4G mobile networks. It describes the motivation for self-organizing networks as manual configuration and optimization becomes too complex. It outlines requirements for self-configuration, self-optimization, and self-healing. The vision is for fully distributed self-management without manual network element management. Specific techniques discussed include mobility robustness optimization using parameters like time-to-trigger and handover margins. Simulation results show self-optimization algorithms improving handover success rates. Coverage and capacity optimization techniques like antenna tilt optimization are also summarized.
SW기업들 HW 영토로…“인공지능 시대, 문제는 데이터야”
구글, 픽셀폰 등 하드웨어 제품 무더기 발표
네이버도 스피커·스마트워치 등 출시
AI스피커 계기 ICT업계 새 트렌드로
사물인터넷시대, 온라인 플랫폼만으론 한계
다양한 하드웨어 통한 ‘데이터 수집’ 목적
“C-P-N-D 융합하는 기업이 생태계 주도”
‘made by Google’ 쏟아낸 구글
세계적 트렌드, 하드웨어 진출
데이터는 온라인에만 있지 않다
목차
1 2차 년도 개발의 배경
2 LTE 의 무선 자원 구성
3 LTE 의 채널 품질 측정
3.1 Reference Signal 전력 측정
3.2 Reference Signal 품질 측정
4 2차년도 개발 내용
4.1 Autonomous Multi-Cell Interference Management
4.2 Coordinated Multi-Cell Capacity and Coverage Optimization
4.3 Coordinated Multi-Cell Interference Management
4.4 Mobility Load Balancing
4.5 Mobility Robustness Optimization
5 2차 년도 개발 참고 사항
5.1 X2 Interface
5.2 X2 Interface, Load Information
5.3 X2 Interface, Load Information, Message Types
5.4 X2 Interface, Load Information, Cell ID
5.5 X2 Interface, Load Information, UL Interference Overload Indication
5.6 X2 Interface, Load Information, UL High Interference Indication
5.7 X2 Interface, Load Information, Relative Narrowband Tx Power (RNTP)
5.8 X2 Interface, ABS Information
5.9 X2 Interface, Invoke Indication
5.10 LTE 이동 통신 망 구성
5.10 eNB 하드웨어 및 소프트웨어 구성
5.11 Key Performance Indicator (KPI)
5.13 MRO 가 적용되는 핸드오버 절차
5.14 MRO 가 적용되는 핸드오버를 위한 이벤트
SON 기술 소개
4G America 에 기술된 Benefit 내용을 적음
Release 8
Automatic Inventory
Automatic Software Download
Automatic Neighbor Relation
Automatic Physical Cell ID (PCI) assignment
Release 9
Mobility Robustness/Hand Over optimization
RACH optimization
Load Balancing optimization
Inter-Cell Interference Coordination
Release 10
Coverage & Capacity optimization
Enhanced Inter-Cell Interference Coordination
Cell Outage Detection and Compensation
Self-healing functions
Minimization of Drive Testing
Energy Savings
Release 11
multi-layer troubleshooting and optimization
multi-RAT HetNet troubleshooting and optimization
SON 전략의 상위 레벨을 요구 사항
Plug & Play Installation
Automatic Neighbor Relation configuration
OSS (Operating Support System) Integration
Handover Optimization
Minimization of Drive Tests
Cell Outage Compensation
Load Balancing
Energy Savings
Interaction home/macro BTS
QoS Optimization
QoS 관련 파라미터
Number of successful sessions per QoS Class Identifier (QCI)
Number of dropped sessions per QCI
Cell specific customer satisfaction rate
Min/Avg/Max throughput per QCI
Min/Avg/Max round trip delay per QCI
Packet loss per QCI
Mean number of Radio Resource Control (RRC) connected users
Mean number of RRC connected UEs with data to send per QCI
Percentage of UEs per cell that is not achieving their required GBR and not achieving the required service data unit (SDU) error ratio per QCI
Percentage of UEs for which transfer delay per IP packet was above a particular threshold
Percentage of UEs for which average throughput measured at RLC layer for each non-real time (nRT) QCI was below a particular threshold
Percentage of UEs per QCI for which the SDU error ratio is above a certain level
Number of RRC connected UEs with measurement gaps configured.
SON Architecture, Distributed vs Centralized
eNodeB software architecture for dual core SoC
Scheduler interface
Core 0: Soft real time function
Core 1: Hard real time function
PHY control
Receive data from PHY
1. 배경 1
1.1. 표준화 및 기술 동향 1
1.2. 국내 재난망 동향 2
1.2.1. 국내 재난망 추진 과정 2
1.2.2. 국내 재난망 구축 현황 (2014년 12월) 2
1.2.3. 삼성전자의 재난망 구축 3
1.2.4. 주요 이슈 4
1.3. 일본 재난망 동향 4
1.4. 미국의 PS-LTE 정책 동향 4
1.5. 미국의 PS-LTE 기술 동향 5
1.5.1. 요구 사항 5
1.5.2. 공공 민간 협력 운영 모델 6
1.6. MVNO 기술 동향 8
1.7. MVNO 필요성 8
1.8. MVNO 타입 8
1.9. MVNO 사업 동향 9
1.9.1. 한국 9
1.9.2. 미국 9
1.9.3. 유럽 10
1.9.4. 구글 10
1.9.5. 애플 10
2. 목표 11
2.1 망 구성 11
2.2 당사의 기술 보유 11
2.3 기술 요구 사항과 시장 수요의 괴리 12
2.4 당사 기술의 제한 사항 12
2.5 제안하는 개발 목표 12
3. 방안 12
4. 일정 12
5. 비용 12
I've read white paper, "{18ca3d99-f643-4f3b-9f38-c8e2ab910ce8}_SenzaFili_Densification.pdf" that describes direction of mobile network densification based on interview with following companies
; network equipment vendors
; test equipment vendors
; mobile netowork operator
; communication network broker, neutral hosts
I have following questions
- yhkim: How many middleprise will deploy mobile network densification?
- yhkim: Multiple backhaul usage: fiber is primary, wireless is secondary. Is it right?
- yhkim: Is there possibility for small cell to be deployed without additional bands?
Lte tdd femto cell for usage of tv white spaceYoung Hwan Kim
This document discusses using TV white space spectrum and technologies like Super WiFi (802.11af), 802.22, and LTE-TDD to support wireless internet hotspots. It compares Super WiFi and LTE-TDD for supporting hotspots and outlines both the technical and business challenges of using LTE-TDD femtocells deployed on TV white space to provide wireless internet access, such as developing an O&M system, satisfying spectrum regulations, and finding partners and customers.
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The document discusses the X2 interface and X2 handover procedure in LTE networks. The X2 interface connects two neighboring eNodeBs and establishes an X2 connection through the X2 setup procedure. The X2 handover procedure allows handing over a UE's connection from a source eNodeB to a target eNodeB, involving preparation where the target allocates resources and the UE connects to it, and execution including a path switch to route data to the target eNodeB. Key information like UE context and bearers is exchanged between eNodeBs through the X2 interface to enable smooth handover.
The document describes an eNodeB handover procedure between two eNodeBs connected to the same MME without S-GW relocation. It involves a handover preparation phase where the source eNodeB requests admission control from the target eNodeB. In the handover execution phase, the UE detaches from the old cell and synchronizes to the new cell. Finally, in the handover completion phase, the bearers are modified and the source eNodeB releases the UE context.
The document describes a release with redirect call flow in LTE. It involves the following key steps:
1. The UE sends a measurement report to the eNodeB indicating bad coverage.
2. The eNodeB sends a connection release message with redirect to the UE, causing it to search for a new cell in 2G/3G.
3. The UE re-establishes data flow on the new 2G/3G cell while the LTE connection is released and set to idle state. Downlink and uplink traffic is possible during the handover process.
This document provides an overview of the key components and protocols in 3G and 4G mobile networks. It includes a high-level diagram of the overall 4G architecture and summaries of protocols like S1, X2, NAS, RRC. Key concepts covered include the PDCP, RLC, MAC and PHY layers, QoS classes, paging, attachment, handover procedures between eNodeBs and between 4G and 3G networks.
This document provides a summary of key concepts in LTE network architecture and protocols:
1) It describes the LTE network architecture including nodes like the eNB, MME, S-GW and P-GW as well as interfaces like S1, S3, S6a and S11.
2) It explains the protocol stack used in the UE and network, covering layers like PDCP, RLC, MAC and PHY.
3) It outlines the main software blocks and functions of the eNB including call processing, O&M, and packet forwarding.
Chap 4. call processing and handover.engsivakumar D
This document provides a 3-sentence summary of the key information:
The document outlines the network architecture and protocol stacks used in LTE networks, including components like the UE, eNB, MME, S-GW and P-GW. It describes the software architecture of eNBs and the call processing blocks. It also summarizes several important procedures in LTE networks like attach, detach, handover, and basic parameter configuration.
The document discusses key performance indicators (KPIs) for the E-UTRAN and EPC components of an LTE network, including accessibility, retainability, integrity, availability, and mobility metrics for E-UTRAN and accessibility, mobility, and utilization KPIs for EPC. It provides definitions and formulas for calculating various KPIs related to EPS attach success rate, dedicated bearer creation success rate, handover success rates, and other measures of network and service performance.
Taking Security Groups to Ludicrous Speed with OVS (OpenStack Summit 2015)Thomas Graf
Open vSwitch (OVS) has long been a critical component of the Neutron's reference implementation, offering reliable and flexible virtual switching for cloud environments.
Being an early adopter of the OVS technology, Neutron's reference implementation made some compromises to stay within the early, stable featureset OVS exposed. In particular, Security Groups (SG) have been so far implemented by leveraging hybrid Linux Bridging and IPTables, which come at a significant performance overhead. However, thanks to recent developments and ongoing improvements within the OVS community, we are now able to implement feature-complete security groups directly within OVS.
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The document summarizes the key procedures and signaling flows involved in setting up an LTE session for a UE:
1) The UE establishes an RRC connection with the eNodeB through random access and preamble signaling.
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3) Finally, the default bearer is established through signaling between the UE, eNodeB, MME, SGW and PGW, allowing user data transfer.
The document discusses self-optimization techniques for 4G mobile networks. It describes the motivation for self-organizing networks as manual configuration and optimization becomes too complex. It outlines requirements for self-configuration, self-optimization, and self-healing. The vision is for fully distributed self-management without manual network element management. Specific techniques discussed include mobility robustness optimization using parameters like time-to-trigger and handover margins. Simulation results show self-optimization algorithms improving handover success rates. Coverage and capacity optimization techniques like antenna tilt optimization are also summarized.
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SW기업들 HW 영토로…“인공지능 시대, 문제는 데이터야”
구글, 픽셀폰 등 하드웨어 제품 무더기 발표
네이버도 스피커·스마트워치 등 출시
AI스피커 계기 ICT업계 새 트렌드로
사물인터넷시대, 온라인 플랫폼만으론 한계
다양한 하드웨어 통한 ‘데이터 수집’ 목적
“C-P-N-D 융합하는 기업이 생태계 주도”
‘made by Google’ 쏟아낸 구글
세계적 트렌드, 하드웨어 진출
데이터는 온라인에만 있지 않다
목차
1 2차 년도 개발의 배경
2 LTE 의 무선 자원 구성
3 LTE 의 채널 품질 측정
3.1 Reference Signal 전력 측정
3.2 Reference Signal 품질 측정
4 2차년도 개발 내용
4.1 Autonomous Multi-Cell Interference Management
4.2 Coordinated Multi-Cell Capacity and Coverage Optimization
4.3 Coordinated Multi-Cell Interference Management
4.4 Mobility Load Balancing
4.5 Mobility Robustness Optimization
5 2차 년도 개발 참고 사항
5.1 X2 Interface
5.2 X2 Interface, Load Information
5.3 X2 Interface, Load Information, Message Types
5.4 X2 Interface, Load Information, Cell ID
5.5 X2 Interface, Load Information, UL Interference Overload Indication
5.6 X2 Interface, Load Information, UL High Interference Indication
5.7 X2 Interface, Load Information, Relative Narrowband Tx Power (RNTP)
5.8 X2 Interface, ABS Information
5.9 X2 Interface, Invoke Indication
5.10 LTE 이동 통신 망 구성
5.10 eNB 하드웨어 및 소프트웨어 구성
5.11 Key Performance Indicator (KPI)
5.13 MRO 가 적용되는 핸드오버 절차
5.14 MRO 가 적용되는 핸드오버를 위한 이벤트
SON 기술 소개
4G America 에 기술된 Benefit 내용을 적음
Release 8
Automatic Inventory
Automatic Software Download
Automatic Neighbor Relation
Automatic Physical Cell ID (PCI) assignment
Release 9
Mobility Robustness/Hand Over optimization
RACH optimization
Load Balancing optimization
Inter-Cell Interference Coordination
Release 10
Coverage & Capacity optimization
Enhanced Inter-Cell Interference Coordination
Cell Outage Detection and Compensation
Self-healing functions
Minimization of Drive Testing
Energy Savings
Release 11
multi-layer troubleshooting and optimization
multi-RAT HetNet troubleshooting and optimization
SON 전략의 상위 레벨을 요구 사항
Plug & Play Installation
Automatic Neighbor Relation configuration
OSS (Operating Support System) Integration
Handover Optimization
Minimization of Drive Tests
Cell Outage Compensation
Load Balancing
Energy Savings
Interaction home/macro BTS
QoS Optimization
QoS 관련 파라미터
Number of successful sessions per QoS Class Identifier (QCI)
Number of dropped sessions per QCI
Cell specific customer satisfaction rate
Min/Avg/Max throughput per QCI
Min/Avg/Max round trip delay per QCI
Packet loss per QCI
Mean number of Radio Resource Control (RRC) connected users
Mean number of RRC connected UEs with data to send per QCI
Percentage of UEs per cell that is not achieving their required GBR and not achieving the required service data unit (SDU) error ratio per QCI
Percentage of UEs for which transfer delay per IP packet was above a particular threshold
Percentage of UEs for which average throughput measured at RLC layer for each non-real time (nRT) QCI was below a particular threshold
Percentage of UEs per QCI for which the SDU error ratio is above a certain level
Number of RRC connected UEs with measurement gaps configured.
SON Architecture, Distributed vs Centralized
eNodeB software architecture for dual core SoC
Scheduler interface
Core 0: Soft real time function
Core 1: Hard real time function
PHY control
Receive data from PHY
1. 배경 1
1.1. 표준화 및 기술 동향 1
1.2. 국내 재난망 동향 2
1.2.1. 국내 재난망 추진 과정 2
1.2.2. 국내 재난망 구축 현황 (2014년 12월) 2
1.2.3. 삼성전자의 재난망 구축 3
1.2.4. 주요 이슈 4
1.3. 일본 재난망 동향 4
1.4. 미국의 PS-LTE 정책 동향 4
1.5. 미국의 PS-LTE 기술 동향 5
1.5.1. 요구 사항 5
1.5.2. 공공 민간 협력 운영 모델 6
1.6. MVNO 기술 동향 8
1.7. MVNO 필요성 8
1.8. MVNO 타입 8
1.9. MVNO 사업 동향 9
1.9.1. 한국 9
1.9.2. 미국 9
1.9.3. 유럽 10
1.9.4. 구글 10
1.9.5. 애플 10
2. 목표 11
2.1 망 구성 11
2.2 당사의 기술 보유 11
2.3 기술 요구 사항과 시장 수요의 괴리 12
2.4 당사 기술의 제한 사항 12
2.5 제안하는 개발 목표 12
3. 방안 12
4. 일정 12
5. 비용 12
I've read white paper, "{18ca3d99-f643-4f3b-9f38-c8e2ab910ce8}_SenzaFili_Densification.pdf" that describes direction of mobile network densification based on interview with following companies
; network equipment vendors
; test equipment vendors
; mobile netowork operator
; communication network broker, neutral hosts
I have following questions
- yhkim: How many middleprise will deploy mobile network densification?
- yhkim: Multiple backhaul usage: fiber is primary, wireless is secondary. Is it right?
- yhkim: Is there possibility for small cell to be deployed without additional bands?
Lte tdd femto cell for usage of tv white spaceYoung Hwan Kim
This document discusses using TV white space spectrum and technologies like Super WiFi (802.11af), 802.22, and LTE-TDD to support wireless internet hotspots. It compares Super WiFi and LTE-TDD for supporting hotspots and outlines both the technical and business challenges of using LTE-TDD femtocells deployed on TV white space to provide wireless internet access, such as developing an O&M system, satisfying spectrum regulations, and finding partners and customers.
Explain LTE RACH Configuration and Capacity.
My Question:
- How many UE preambles can be handled in 10 ms frame by eNodeB?
- How many UE preambles can be handled in T300 by eNodeB?
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
2. Mobility, S1 HO procedure
UE
Source
eNB
Target
eNB MME S-GW
Measuremnt Report
HO Decision
HO Required
HO Command
Modify Bearer Request
Modify Bearer Response
UE Context Release Command
HO
Preparation
HO
ExecutionSync and Random Access Procedure
HO Request
HO Request Ack
Admission Control
eNB status transfer
eNB status transfer
RRC Conn Reconfiguration
RRC Conn Reconfiguration Complete
HO Notify
Bearer Setup
Tracking Area Update
UE Context Release Complete
HO.ExeSucc++
HO.ExeAtt++
HO.PrepSucc[QCI]++
HO.PrepAtt[QCI]++
HO.PrepAtt[QCI]++
HO.ExeSucc++
HO.PrepAtt[QCI]++
HO.ExeAtt++
3. Mobility, X2 HO procedure
UE
Source
eNB
Target
eNB MME S-GW
Measuremnt Report
HO Decision
HO Request
Admission Control
HO Ack/Command
RRC Conn Reconfiguration
SN Status Transfer
Forward User Plane Data
Buffer Packet
RRC Conn Reconfiguration Complete
Path Switch Request
Modify Bearer Request
Modify Bearer Response
Path Switch Request Ack
UE Context Release Command
HO
Preparation
HO
Execution
Sync and Random Access Procedure
Bearer Setup
UE Context Release Complete
HO.ExeSucc++
HO.ExeAtt++
HO.PrepSucc[QCI]++
HO.PrepAtt[QCI]++
HO.PrepAtt[QCI]++
HO.PrepSucc[QCI]++
HO.ExeSucc++
HO.ExeAtt++