1 / 11

EE383 – Lecture 2 Outline

This lecture outlines key concepts in signal propagation and path loss modeling relevant to wireless communications. It begins with a review of previous lectures and transitions into an overview of transmission (TX) and reception (RX) signal models. The lecture discusses complex baseband models, free-space path loss, and various empirical models, including the Okumura and Hata models. Understanding these models is critical for addressing technical challenges in wireless system design and meeting multimedia requirements. The lecture also highlights the significance of geometry and site-specific parameters in signal assessment.

meghan
Télécharger la présentation

EE383 – Lecture 2 Outline

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. EE383 – Lecture 2 Outline • Review of Last Lecture • Signal Propagation Overview • TX and RX Signal Models • Complex baseband models • Path Loss Models • Free-space Path Loss • Ray Tracing Models • Simplified Path Loss Model • Empirical Models

  2. Lecture 1 Review • Course Information • Wireless Vision • Technical Challenges • Multimedia Requirements • Current Wireless Systems • Spectrum Regulation and Standards

  3. Slow Fast Very slow Propagation Characteristics • Path Loss (includes average shadowing) • Shadowing (due to obstructions) • Multipath Fading Pr/Pt Pt Pr v d=vt d=vt

  4. Path Loss Modeling • Maxwell’s equations • Complex and impractical • Free space path loss model • Too simple • Ray tracing models • Requires site-specific information • Simplified power falloff models • Main characteristics: good for high-level analysis • Empirical Models • Don’t always generalize to other environments

  5. d=vt Free Space (LOS) Model • Path loss for unobstructed LOS path • Power falls off : • Proportional to 1/d2 • Proportional to l2 (inversely proportional to f2)

  6. Ray Tracing Approximation • Represent wavefronts as simple particles • Geometry determines received signal from each signal component • Typically includes reflected rays, can also include scattered and defracted rays. • Requires site parameters • Geometry • Dielectric properties

  7. Two Path Model • Path loss for one LOS path and 1 ground (or reflected) bounce • Ground bounce approximately cancels LOS path above critical distance • Power falls off • Proportional to d2 (small d) • Proportional to d4 (d>dc) • Independent of l (f)

  8. General Ray Tracing • Models all signal components • Reflections • Scattering • Diffraction • Requires detailed geometry and dielectric properties of site • Similar to Maxwell, but easier math. • Computer packages often used

  9. Simplified Path Loss Model • Used when path loss dominated by reflections. • Most important parameter is the path loss exponent g, determined empirically.

  10. Empirical Models • Okumura model • Empirically based (site/freq specific) • Awkward (uses graphs) • Hata model • Analytical approximation to Okumura model • Cost 231 Model: • Extends Hata model to higher frequency (2 GHz) • Walfish/Bertoni: • Cost 231 extension to include diffraction from rooftops Commonly used in cellular system simulations

  11. Main Points • Path loss models simplify Maxwell’s equations • Models vary in complexity and accuracy • Power falloff with distance is proportional to d2 in free space, d4 in two path model • Main characteristics of path loss captured in simple model Pr=PtK[d0/d]g • Empirical models used in simulations • Low accuracy (15-20 dB std) • Capture phenomena missing from formulas • Awkward to use in analysis

More Related