EE445S Real-Time Digital Signal Processing Lab Spring 2014 Lecture 16 Quadrature Amplitude Modulation (QAM) Receiver Prof. Brian L. Evans Dept. of Electrical.

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EE445S Real-Time Digital Signal Processing Lab Spring 2014 Lecture 16 Quadrature Amplitude Modulation (QAM) Receiver Prof. Brian L. Evans Dept. of Electrical and Computer Engineering The University of Texas at Austin

Outline Introduction Automatic gain control Carrier detection Symbol clock recovery Channel equalization QAM demodulation

Introduction Channel impairments Linear and nonlinear distortion of transmitted signal Additive noise (often assumed to be Gaussian) Mismatch in transmitter/receiver analog front ends Receiver subsystems to compensate for impairments FadingAutomatic gain control (AGC) Additive noiseMatched filters Linear distortionChannel equalizer Carrier mismatchCarrier recovery Symbol timing mismatchSymbol clock recovery

Baseband QAM Receive Filter A/D Symbol Clock Recovery LPF Carrier Detect AGC X X r0(t)r0(t) r1(t)r1(t) r(t)r(t) r[m]r[m] Channel Equalizer L L L samples/symbol m sample index n symbol index QAM Demodulation c(t)c(t) 2 cos(  c m) -2 sin(  c m) Receiver i[n]i[n] gT[m]gT[m] L + cos(  c m) q[n]q[n] gT[m]gT[m] L sin(  c m) Serial/ parallel converter 1 Bits Map to 2-D constellation J Pulse shapers (FIR filters) Index s[m]s[m] D/A s(t)s(t) Transmitter fsfs Carrier recovery is not shown i[m]i[m] q[m]q[m]

Automatic Gain Control Scales input voltage to A/D converter Increase gain for low signal level Decrease gain for high signal level Consider A/D converter with 8-bit signed output When c(t) is zero, A/D output is 0 When c(t) is infinity, A/D output is -128 or 127 Let f -128, f 0 and f 127 represent how frequently outputs -128, 0 and 127 occur over a window of previous samples Each frequency value is between 0 and 1, inclusive Update: c(t) = (1 + 2 f 0 – f -128 – f 127 ) c(t –  ) Initial values: f -128 = f 0 = f 127 = 1 / 256. Zero also works A/D AGC r1(t)r1(t) r(t)r(t)r[m]r[m] c(t)c(t)

Carrier Detection Detect energy of received signal (always running) c is a constant where 0 < c < 1 and r[m] is received signal Let x[m] = r 2 [m]. What is the transfer function? What values of c to use? If receiver is not currently receiving a signal If energy detector output is larger than a large threshold, assume receiving transmission If receiver is currently receiving signal, then it detects when transmission has stopped If energy detector output is smaller than a smaller threshold, assume transmission has stopped

Symbol Clock Recovery Two single-pole bandpass filters in parallel One tuned to upper Nyquist frequency  u =  c  sym Other tuned to lower Nyquist frequency  l =  c – 0.5  sym Bandwidth is B/2 (100 Hz for 2400 baud modem) A recovery method Multiply upper bandpass filter output with conjugate of lower bandpass filter output and take the imaginary value Sample at symbol rate to estimate timing error  Smooth timing error estimate to compute phase advancement when Lowpass IIR filter Pole locations? See Reader handout M

Channel Equalizer Mitigates linear distortion in channel When placed after A/D converter Time domain: shortens channel impulse response Frequency domain: compensates channel distortion over entire discrete-time frequency band instead of transmission band Ideal channel Cascade of delay  and gain g Impulse response: impulse delayed by  with amplitude g Frequency response: allpass and linear phase (no distortion) Undo effects by discarding  samples and scaling by 1/g z-z- g

Channel Equalizer IIR equalizer Ignore noise n m Set error e m to zero H(z) W(z) = g z -  W(z) = g z -  / H(z) Issues? FIR equalizer Adapt equalizer coefficients when transmitter sends training sequence to reduce measure of error, e.g. square of e m Discrete-Time Baseband System z-z- h + w - xmxm ymym emem rmrm nmnm + Equalizer Channel g Ideal Channel + Receiver generates x m Training sequence

Adaptive FIR Channel Equalizer Simplest case: w[m] =  [m] + w 1  [m-1] Two real-valued coefficients w/ first coefficient fixed at one Derive update equation for w 1 during training Using least mean squares (LMS) Step size 0 <  < 1 z-z- h + w - xmxm ymym emem rmrm nmnm + Equalizer Channel g Ideal Channel + Receiver generates x m Training sequence smsm

Baseband QAM Demodulation Recovers baseband in-phase/quadrature signals Assumes perfect AGC, equalizer, symbol recovery QAM modulation followed by lowpass filtering Receiver f max = 2 f c + B and f s > 2 f max Lowpass filter has other roles Matched filter Anti-aliasing filter Matched filters Maximize SNR at downsampler output Hence minimize symbol error at downsampler output LPF X X 2 cos(  c m) -2 sin(  c m) x[m]x[m]

Baseband QAM Demodulation QAM baseband signal QAM demodulation Modulate and lowpass filter to obtain baseband signals baseband high frequency component centered at 2  c baseband high frequency component centered at 2  c