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EE359 – Lecture 10 Outline
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  1. EE359 – Lecture 10 Outline • Announcements: • Project proposals due this Friday at 5pm (post, email link) • Midterm will be Nov. 7, 6-8pm, Room TBD, no HW due that week. Exam is open book/notes. • More MT announcements next week (practice MTs) • Example of P_out • Average Ps (Pb) • MGF approach for average Ps • Combined average and outage Ps

  2. Ts Outage Ps Ps(target) t or d Review of Last Lecture • Linear modulation more spectrally efficient but less robust than nonlinear modulation • Psapproximation in AWGN: • Probability of error in fading is random • Characterized by outage, average Ps, combination • Outage probability • Probability Ps is above target; Probability gs below target • Fading severely degrades performance • Used when Tc>>Ts

  3. Average Ps • Expected value of random variable Ps • Used when Tc~Ts • Error probability much higher than in AWGN alone • Alternate Q function approach: • Simplifies calculations (Get a Laplace Xfm) Ts Ps Ps t or d

  4. Ps(gs) Ps(gs) Combined outage and average Ps Outage • Used in combined shadowing and flat-fading • Ps varies slowly, locally determined by flat fading • Declare outage when Ps above target value Ps(gs) Pstarget

  5. Main Points • In fading Psis a random variable, characterized by average value, outage, or combined outage/average • Fading greatly increases average Ps or required power for a given target Ps with some outage • Alternate Q function approach simplifies Pscalculation, especially its average value in fading • Average Psbecomes a Laplace transform. • In fast/slow fading, outage due to shadowing, probability of error averaged over fast fading pdf • Need to combat flat fading or waste lots of power • Adaptive modulation and diversity are main techniques to combat flat fading: adapt to fading or remove it