Upload
others
View
3
Download
0
Embed Size (px)
Citation preview
Peio López-Iturri, Erik Aguirre, Leire Azpilicueta, Carlos Fernández-
Valdivielso, Ignacio Raúl Matías, Francisco Falcone Universidad Pública de Navarra
Campus Arrosadia, 31006 Pamplona, Spain.
2
Introduction and Motivation
Simulation Techniques and Scenario
Description
Results
Conclusions
3
Introduction and Motivation
Simulation Techniques and Scenario
Description
Results
Conclusions
4
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
Increasing adoption of Context Aware Scenarios:
Augmented Reality
Home/Building Automation
Ambient Assisted Living
Smart Cities
Connectivity is greatly dependent on wireless systems:
Massive adoption of mobile terminals and Internet
Access
Strong presence of Wireless Sensor Networks, WLAN
and emerging 4G mobile networks
New trends in the way people interact (social
networking, Web 2.0/Web 3.0, e-Gov)
New and exciting opportunities appear in the context of
IoT/Smart City Deployment
• Interoperability
• Big Data Management
• Seamless Interaction
• User Centric: Usabilty and Adoption
http://www.ibm.com
http://www.hitachi.com
6
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
A. Solanas et al., “Smart Health: A Context-Aware Health Paradigm within Smart
Cities”, IEEE Communications Magazine, August 2014
• In order to achieve context aware scenarios, wireless systems
play a key role
• Perfomance depends on coverage/capacity considerations,
determined by topo-morphological characteristics
7
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
Analyze Propagation Characteristics in a complex
Urban Scenario
Evaluation of the Impact of Wireless Channel Behviour
in Overall System Performance
Characterization of the propagation channel and
wireless systems, with the impact of material parameter
changes (Sources as well as Interferers)
To achieve this goal:
Simulations with a deterministic method based
on 3D Ray Launching technique
Analysis of topo-morphological impact in
wireless system performance
System Level Analysis
8
Introduction and Motivation
Simulation Techniques and Scenario
Description
Results
Conclusions
9 ACCURACY
CO
MP
UTA
TIO
NA
L T
IME
Okumura
Hata
COST 231
Anderson 2D
Ray Tracing
EM Software: FDTD, MoM,
FITD…
Deterministics
Empirics
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
10
f = 4.52 GHz f = 4.95 GHz Full 3D Ray Tracing algorithm
Ray-Launching Technique
Solid angle of departure
Tetrahedral resolution
EM Phenomena considered:
Reflection
Refraction
First Order of Diffraction
Configuration:
Frequency
Antenna (power, gain,
polarization,directivity)
Symbol Time (bit rate)
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
11
Urban Scenario
Buildings + Streets
Interior Structure
3D Ray Launching Model
Implemented
Materials
Topological
Considerations
12
Introduction and Motivation
Simulation Techniques and Scenario
Description
Results
Conclusions
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
13
Ray Launching Simulation Parameters
Frequency 2.4 GHz
Transmitter Power 30 dBm
Reflections 6
Vertical plane angle
resolution Δθ
1°
Horizontal plane angle
resolution Δϕ
1°
Estimation of PRX and comparison with Sensitivity
Levels (Path Loss estimation)
PRX = PTX – Lcables, feed + GTX – Lprop + GRX – Lcables, feed
Sensitivity levels depend on: Modulation, Coding, Bit
Rate, Diversity Techniques
Propagation Losses (for sources as well as for
interferers) are determined by RL (complex scenario)
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
14
SLOW FADING
FAST FADING (MULTIPATH)
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
15 DEPENDENCE ON AVAILABLE TX POWER
AP
MIN Mote TX
MAX Mote TX
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
16
AP
MIN Mote TX
MAX Mote TX
ROOF LEVEL (INTERCONNECTION/TRANSPORT NW)
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
17
AP
MIN Mote TX
MAX Mote TX
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
18
t(ns)
PR
X(d
Bm
) P
RX(d
Bm
)
t(ns)
Power Delay
Profiles, for two
locations within
the scenario
(2.4GHz)
Variability due to
strong multipath
component
effects
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
19
2D Power Delay
Profile Estimations
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
20
AP (active TX)
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
21
Estimation of RX Power Level
Complete Scenario
AP (active TX)
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
22
TX Ant 3 TX Ant 4
TX Ant 5 TX Ant 6
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
23
Sensitivity levels: f(bit rate|coding scheme|electronics)
Solution: TX power increase, but….
Increase in Interference Levels and TRX power
consumption
Coverage-Capacity Relations (Indoor Scenario)
E. Aguirre et al., “Analysis of Wireless Sensor Network Topology and Estimation of Optimal Network Deployment by Deterministic
Radio Channel Characterization”, Sensors, Under Review
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
24
Coverage-Capacity:WSN Clustering Algorithms
J. J. Astrain, L. Azpilicueta, F. Falcone, J. Villadangos, “Analysis of Topological Influence in Air Interface Characterization of
Superimposed Cluster Architectures for WSNs”, Ad-Hoc and Sensor Wireless Networks, October 2014
Node Density
directly modifies
SNR
Coverage-Capacity Relations (Indoor Scenario)
E. Aguirre et al., “Analysis of Wireless Sensor Network Topology and Estimation of Optimal Network Deployment by Deterministic
Radio Channel Characterization”, Sensors, Under Review
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
26
TRX Current Consumption
E. Aguirre et al., “Analysis of Wireless Sensor Network Topology and Estimation of Optimal Network Deployment by Deterministic
Radio Channel Characterization”, Sensors, Under Review
3 TRX 4 TRX
8 TRX
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
27
L. Azpilicueta et al, “Analysis of Radio Wave Propagation for ISM 2.4GHz Wireless Sensor Networks in Inhomogeneous
Vegetation Environments”, Sensors, Under Review
Smart City Context-Urban Outdoor
Context Aware Urban
Outdoor
Static/MANET
Environment/Users
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
28
29
Introduction and Motivation
Simulation Techniques and Scenario
Description
Results
Conclusions
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
30
1. Introduction and
Motivation
2. Simulation
Techniques and
Scenario Description
3. Results
4. Conclusions
Topo-Morphological considerations in the impact of
RF channel is relevant in the overall performance
and connectivity of wireless systems within an
Urban Scenario.
Node modifications imply changes in RF power
levels of sources and interferers, modyfing
coverage/capacity ratios
The trend: increase in number of nodes and HetNet
operation
Future Scenario: Context Aware + IoT = Big
challenge!
Peio López-Iturri, Erik Aguirre, Leire Azpilicueta, Carlos Fernández-
Valdivielso, Ignacio Raúl Matías, Francisco Falcone Universidad Pública de Navarra
Campus Arrosadia, 31006 Pamplona, Spain.