EE359 – Lecture 3 Outline Announcements Log Normal Shadowing

Slides:



Advertisements
Similar presentations
Empirical Model Building I: Objectives: By the end of this class you should be able to: find the equation of the “best fit” line for a linear model explain.
Advertisements

Data Communication lecture10
EE359 – Lecture 9 Outline Announcements: Project proposals due this Friday at 5pm; create website Midterm date: Thurs Nov. 7, 5:30-7:30 or 6-8pm? Practice.
EE359 – Lecture 10 Outline Announcements: Project proposals due today at 5pm (post, link) Midterm will be Nov. 4, 6-8pm, Room TBD, no HW due that.
EE359 – Lecture 3 Outline Log Normal Shadowing
Authors: David N.C. Tse, Ofer Zeitouni. Presented By Sai C. Chadalapaka.
SYSC4607 – Lecture 2 (Cont.) Announcements 1 st Assignment posted, due Thursday, Jan. 18, 4:00 p.m. TA office hours Importance of reading the required.
EE359 – Lecture 2 Outline Announcements 1 st HW posted, due next Thursday at 5pm. Discussion section starts next week (4-5 pm in Y) My OHs today.
Wireless Channel and Models YUN AI. The ‘Mobile Age’ Vatican City, 2005/4/4 Vatican City, 2013/3/12 Source:
Florida Institute of technologies ECE 5221 Personal Communication Systems Prepared by: Dr. Ivica Kostanic Lecture 4: Estimation of coverage reliability.
Probability distribution functions Normal distribution Lognormal distribution Mean, median and mode Tails Extreme value distributions.
Propagation Characteristics
Ray Tracing A radio signal will typically encounter multiple objects and will be reflected, diffracted, or scattered These are called multipath signal.
1 SYSC4607 – Lecture 5 Outline Announcements: Tutorial important: Review of Probability Theory and Random Processes Review of Last Lecture Narrowband Fading.
EELE 5490, Fall, 2009 Wireless Communications
1 OUTLINE Motivation Distributed Measurements Importance Sampling Results Conclusions.
EE360: Lecture 15 Outline Cellular System Capacity
Wireless Communication Channels: Small-Scale Fading
Wireless Communication Channels: Large-Scale Pathloss
Cellular System Capacity Maximum number of users a cellular system can support in any cell. Can be defined for any system. Typically assumes symmetric.
WIRELESS COMMUNICATIONS Assist.Prof.Dr. Nuray At.
Chapter 7 Probability and Samples: The Distribution of Sample Means
ECE 5221 Personal Communication Systems
NETW 707 Modeling and Simulation Amr El Mougy Maggie Mashaly.
Probability distribution functions
QBM117 Business Statistics Estimating the population mean , when the population variance  2, is known.
Exponent Rules 1 Assignment
Physical Layer Fundamentals Physical MAC Physical LLC Data Link Network Transport Session Presentation Application OSI Ref ModelWireless Network Network.
Path loss & shadowing By eng : mahmoud abdel aziz.
Probabilistic Coverage in Wireless Sensor Networks Authors : Nadeem Ahmed, Salil S. Kanhere, Sanjay Jha Presenter : Hyeon, Seung-Il.
EE383 – Lecture 2 Outline Review of Last Lecture Signal Propagation Overview TX and RX Signal Models Complex baseband models Path Loss Models Free-space.
1 Introduction to Fading Channels, part 1 Dr. Essam Sourour Alexandria University, Faculty of Engineering, Dept. Of Electrical Engineering.
Point Estimation of Parameters and Sampling Distributions Outlines:  Sampling Distributions and the central limit theorem  Point estimation  Methods.
EE359 – Lecture 15 Outline Announcements: HW posted, due Friday MT exam grading done; l Can pick up from Julia or during TA discussion section tomorrow.
EE359 – Lecture 4 Outline Announcements: 1 st HW due tomorrow 5pm Review of Last Lecture Model Parameters from Empirical Measurements Random Multipath.
EE359 – Lecture 3 Outline Announcements HW posted, due Friday 5pm Discussion section starts tomorrow, 4-5pm, 364 Packard TA OHs start this week mmWave.
Sampling Theory and Some Important Sampling Distributions.
Midterm Review Midterm only covers material from lectures and HWs
ECE637 : Fundamentals of Wireless Communications
Numericals.
Chapter 7 Probability and Samples
EE359 – Lecture 15 Outline Announcements: MIMO Channel Capacity
Adv. Wireless Comm. Systems - Cellular Networks -
Aaker, Kumar, Day Ninth Edition Instructor’s Presentation Slides
EE359 – Lecture 2 Outline Announcements Review of Last Lecture
EE359 – Lecture 3 Outline Announcements Log Normal Shadowing
Chapter 4. Inference about Process Quality
A Problem in LTE Communication
EE359 – Lecture 15 Outline Announcements: MIMO Channel Capacity
Midterm Review Midterm only covers material from lectures and HWs
EE359 – Lecture 2 Outline Announcements Review of Last Lecture
Chapter 7: Sampling Distributions
Concept of Power Control in Cellular Communication Channels
Physics 114: Exam 2 Review Material from Weeks 7-11
Section 9.4: Normal Distributions
Probability & Statistics Probability Theory Mathematical Probability Models Event Relationships Distributions of Random Variables Continuous Random.
Chapter 6 Confidence Intervals.
EE359 – Lecture 4 Outline Announcements: Review of Last Lecture
Sampling Distribution of a Sample Proportion
EE359 – Lecture 4 Outline Announcements: Review of Last Lecture
MITP 413: Wireless Technologies Week 3
EE359 – Lecture 10 Outline Announcements: MGF approach for average Ps
EE359 – Lecture 4 Outline Announcements: Review of Last Lecture
The lognormal distribution
Determining Which Method to use
EE359 – Lecture 2 Outline Announcements Review of Last Lecture
EE359 – Lecture 10 Outline Announcements: Average Ps (Pb)
Midterm Review Midterm only covers material from lectures and HWs
EE359 – Lecture 11 Outline Announcements Introduction to Diversity
Chapter 6 Confidence Intervals.
Presentation transcript:

EE359 – Lecture 3 Outline Announcements Log Normal Shadowing First discussion section Tuesday, HW due Thursday. Log Normal Shadowing Combined Path Loss and Shadowing Cell Coverage Area Models Parameters from Empirical Measurements

Lecture 2 Review Ray Tracing Models Free Space Model Two Ray Model Power falloff with distance proportional to d-2 Two Ray Model Power falloff with distance proportional to d-4 General Ray Tracing Used for site-specific models Empirical Models Simplified Model: Pr=PtK[d0/d]g, 2g8. Captures main characteristics of path loss

Shadowing Models attenuation from obstructions Xc Models attenuation from obstructions Random due to random # and type of obstructions Typically follows a log-normal distribution dB value of power is normally distributed m=0 (mean captured in path loss), 4<s2<12 (empirical) LLN used to explain this model Decorrelated over decorrelation distance Xc

Combined Path Loss and Shadowing Linear Model: y lognormal dB Model 10logK Slow Pr/Pt (dB) Very slow -10g log d

Outage Probability and Cell Coverage Area Path loss: circular cells Path loss+shadowing: amoeba cells Tradeoff between coverage and interference Outage probability Probability received power below given minimum Cell coverage area % of cell locations at desired power Increases as shadowing variance decreases Large % indicates interference to other cells

Model Parameters from Empirical Measurements K (dB) log(d0) sy 2 Fit model to data Path loss (K,g), d0 known: “Best fit” line through dB data K obtained from measurements at d0. Exponent is MMSE estimate based on data Captures mean due to shadowing Shadowing variance Variance of data relative to path loss model (straight line) with MMSE estimate for g Pr(dB) 10g log(d)

Main Points Random attenuation due to shadowing modeled as log-normal (empirical parameters) Shadowing decorrelates over decorrelation distance Combined path loss and shadowing leads to outage and amoeba-like cell shapes Cellular coverage area dictates the percentage of locations within a cell that are not in outage Path loss and shadowing parameters are obtained from empirical measurements