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MRC Issues

MRC Issues. Mobile Radio Channel (MRC) Impairments: 1) ACI/CCI  system generated interference 2) Shadowing  large-scale path loss from LOS obstructions 3) Multipath Fading  rapid small-scale signal variations 4) Doppler Spread  channel conditions change rapidly

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MRC Issues

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  1. MRC Issues • Mobile Radio Channel (MRC) Impairments: 1) ACI/CCI  system generated interference 2) Shadowing  large-scale path loss from LOS obstructions 3) Multipath Fading  rapid small-scale signal variations 4) Doppler Spread  channel conditions change rapidly due to motion of mobile unit • All can lead to significant distortion or attenuation of Rx signal • Degrade BER of digitally modulated signal ECE 4730: Lecture #16

  2. MRC Issues • Three techniques to improve Rx signal quality and/or lower BER: 1) Equalization 2) Diversity 3) Channel Coding • Used independently or together ECE 4730: Lecture #16

  3. Equalization • Equalization  Primary goal is to reduce ISI by compensating for finite BW of MRC • MRC is frequency selective when Bc < Bs • Some signal frequencies undergo significant fading • In time domain  multipath signals cause significant ISI when time delay (st) > 0.1 Ts • Equalizers compensate for selective fading by enhancing certain frequencies of Rx signal • Must be adaptive since MRC is time-varying !! ECE 4730: Lecture #16

  4. Diversity • Diversity  Primary goal is to reduce depth & duration of signal fades in flat fading channel • Flat fading Bs < Bc no ISI from multipath ! • Spatial or antenna diversity  most common • Use multiple Rx antennas in mobile or base station • One antenna with signal null while another antenna may have signal peak • Small antenna separation (l) changes phase of signal  constructive /destructive nature is changed • Other diversity types  polarization, frequency, & time ECE 4730: Lecture #16

  5. Channel Coding • Channel coding  Primary goal is to reduce BER by detecting & correcting some (or all) bit errors • Correction data bits are added to original (source) Tx data stream • Data errors are corrected in Rx after demodulation • Coding results in: 1) Lower data rate for same signal BW OR 2) Higher signal BW for same data rate • Reduced spectral efficiency ECE 4730: Lecture #16

  6. MRC Improvement • All 3 techniques improve mobile radio link performance • Effectiveness of each varies widely in practical wireless systems • Cost & complexity are also important issues • Mobile vs. base station implementation • Some techniques may be implemented in base station or mobile only ECE 4730: Lecture #16

  7. Equalization • Equalization Fundamentals • ISI is the major obstacle to high speed data transmission over MRC  “Darth Vader” • Time domain perspective  caused by multipath interference • Frequency domain perspective  frequency selective fading • Combat ISI by “equalizing” frequency response of MRC  transform to flat fading channel ECE 4730: Lecture #16

  8. Equalization Rx Signal Spectrum (w/ Tx Spectrum overlay) Before Equalization After Equalization Bc Bc f f fc fc ECE 4730: Lecture #16

  9. Equalization • Combat ISI by “equalizing” frequency response of MRC • Reduce ISI  increase Bc increase allowable signal BW (Bs)  increase data rate • Equalization actually done @ baseband (after demodulation) • Figure 7.1, pg. 358 ECE 4730: Lecture #16

  10. Adaptive Equalizer ECE 4730: Lecture #16

  11. Adaptive Equalizer • Define: • x(t) : baseband source data • f(t) : impulse response of Tx + MRC + Rx • heq(t): impulse response of equalizer • : output response of equalizer (want = x(t) !) • Now and for = x(t) ECE 4730: Lecture #16

  12. Adaptive Equalizer • In Frequency Domain: •  unity at all frequencies • Ideal frequency response • Cannot be achieved in practice due to practical limitations • Heq ( f ) is inverse filter of MRC • Enhances weak frequency components • Attenuates strong frequency components • Yields “flat” output frequency response ECE 4730: Lecture #16

  13. Adaptive Equalizer • MRC is time-varying due to motion of mobile or nearby objects • Heq (f)must vary in time as well • Adaptive equalization • Can’t use R/C/L analog filters • Must implement using DSP in time domain • FIR filters • Time-varying discrete filter  Fig. 7.2, pg. 359 ECE 4730: Lecture #16

  14. Generic Adaptive Equalizer Time-varying discrete filter Discrete time = k N Delay Elements N+1 taps N+1 variable filter coefficients or “weights” wN k ECE 4730: Lecture #16

  15. Generic Adaptive Equalizer • Adaptive algorithm • Update filter coefficients (weights) continuously • Two basic operating modes: 1) Training 2) Tracking • Training • Fixed length known sequence sent by Tx • Typically a PN sequence • Flat spectral response at Tx output • Rx input shows frequency selective fading • Equalizer adjusts weights to obtain flat output • Weights near optimal value for reception of user data at end of training sequence ECE 4730: Lecture #16

  16. Generic Adaptive Equalizer • Tracking • Tx data follows training sequence • Adaptive algorithm tracks changing channel and updates weights to compensate • Periodic retraining required for effective ISI cancellation since MRC response is time-varying • Very common in digital communication systems where data is segmented in time blocks • TDMA systems use fixed-length time blocks with training sequence contained in each block ECE 4730: Lecture #16

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