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Practical Issues in Adaptive Modulation for MIMO Communications

Explore practical constraints, estimation errors, MIMO systems benefits, and decomposition techniques in adaptive modulation for wireless communications. Includes midterm announcements and review details.

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Practical Issues in Adaptive Modulation for MIMO Communications

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  1. EE359 – Lecture 14 Outline • Announcements: • MT announcements. • HW postedtoday, due next Friday at noon • Will send project feedback in the next week • Practical Issues in Adaptive Modulation • Finite constellations and update rate • Estimation error and delay • Introduction to MIMO Communications • MIMO Channel Decomposition

  2. Midterm Announcements • Midterm today Nov. 7, 6-8pm, Thornton 110 • Open book/notes (bring textbook/calculators) • Covers Chapters 1-7 • No computers, cell phones, tablets (no communications) • Turn in practice midterms before exam ends for credit.

  3. Midterm Announcements • Midterm Thur Nov. 7, 6-8pm, Thornton 110 • Open book/notes (bring textbook/calculators) • Covers Chapters 1-7 • No computers • Short review today • OHs this week: • Andrea: Tuesday 5-6pm and Wednesday 6-7pm • Mainak: Mainak’s: Tues 6-7 pm, Packard 364, Wed 7-8pm Packard 106, Thurs 1:30-2:30 pm, Packard 106 • No HW this week (new HW posted Thurs) • Midterms from past 3 MTs posted, 10 pts for taking one and solns to all exams

  4. Review of Last Lecture • Introduction to adaptive modulation • Variable-rate variable-power MQAM • Optimal power adaptation is water-filling • Optimal rate adaptation is R/B=log(g/gk)

  5. Constellation Restriction M3 M(g)=g/gK* MD(g) M3 M2 M2 M1 M1 Outage 0 g0 g1=M1gK* g2 g3 g • Power adaptation: • Average rate:

  6. Efficiency in Rayleigh Fading Spectral Efficiency (bps/Hz) Average SNR (dB)

  7. Practical Constraints • Constellation updates: fade region duration • Estimation error • Estimation error at RX can cause error in absence of noise (e.g. for MQAM) • Estimation error at TX can be caused by estimator and/or delay in the feedback path • Causes mismatch of adaptive power and rate to actual channel • Can lead to large errors

  8. Multiple Input Multiple Output (MIMO)Systems • MIMO systems have multiple (r) transmit and receiver antennas • With perfect channel estimates at TX and RX, decomposes into r independent channels • RH-fold capacity increase over SISO system • Demodulation complexity reduction • Can also use antennas for diversity (beamforming) • Leads to capacity versus diversity tradeoff in MIMO

  9. MIMO Decomposition • Decompose channel through transmit precoding (x=Vx) and receiver shaping (y=UHy) • Leads to RHmin(Mt,Mr) independent channels with gain si (ith singular value of H) and AWGN • Independent channels lead to simple capacity analysis and modulation/demodulation design ~ ~ ~ ~ ~ y=S x+n y=Hx+n H=USVH ~ ~ ~ yi=six+ni

  10. Main Points • Discretizing the constellation size results in negligible performance loss in adaptive modulation • Constellations cannot be updated faster than 10s to 100s of symbol times: OK for most dopplers. • Estimation error/delay causes error floor • MIMO systems exploit multiple antennas at both TX and RX for capacity and/or diversity gain • With TX and RX channel knowledge, channel decomposes into independent channels

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