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Welcome to EQ2430/EQ2440 RF lecture

Welcome to EQ2430/EQ2440 RF lecture

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Welcome to EQ2430/EQ2440 RF lecture

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  1. Welcome toEQ2430/EQ2440 RF lecture Per Zetterberg School of Electrical Engineering

  2. Objective of this lecture • Give an overview of radio communications. • Review

  3. What is RF ? • RF = Radio Frequency. • For us: 2-6GHz.

  4. What is the ”channel” ? Propagation channel TX A/D D/A RX RX =receiver chain TX = Transmitter chain Communication channel

  5. Transmitter chain (TX) D/A LPF BPF HPA =Mixer LPF = Low Pass Filter BPF = Band Pass Filter HPA = High Power Amplifier =Local oscillator

  6. Receiver chain (RX) BPF LNA LPF A/D LPF = Low Pass Filter BPF = Band Pass Filter LNA =Low Noise Amplifier =Mixer =Local oscillator

  7. Basic Channel Model Combined effect ot low-pass and band-pass filters in TX and RX. Unknown offset between clocks at TX and TX Frequency offset between TX and RX. Propagation channel

  8. Handling basic channel model Discrete time: TRAIN TRAIN Data Sliding correlation. Sliding correlation, several frequency offsets, FFT. Several short correlations. Self-correlation.

  9. Inter-symbol interference 16QAM: Blur. QPSK: No problem.

  10. Inter-symbol interference sources Radio propagation. Narrow and sharp low-pass and band-pass filters !!!!!! (narrow=narrow compared with the bandwidth of the desired signal) Pulse-shaping, sampling offsets. So why do we use these narrow filters ? Limit spectrum of transmitted signal. Improve adjacent channel performance. Reduce requirements on A/D converters.

  11. Ways to combat inter-symbol interference Interpolation between samples. Equalizers (linear, decision feedback, viterbi, ...) OFDM

  12. Next problem Power amplifier non-linearity

  13. Power-Amplifier Non-linearity

  14. Input/output power

  15. AM/AM and AM/PM model AM/AM AM/PM AM: Amplitude Modulation PM: Phase Modulation

  16. Intuition AM/AM and AM/PM model Let’s say our communication signal has 1MHz bandwidth. The carrier frequency is 1GHz=1000MHz. Then every symbol lasts 1000 cycles. During one symbol the input signal can be seen as a CW. A CW which is sent through a non-linearity will always appear at the output (together with harmonics), but with a differentamplitude and phase. The AM/AM and AM/PM models are functions of this phase offset.

  17. Solid State Power Amplifier Model: SSPA :Output saturation level (unit dependent e.g. volt, dBm, LSB) :Smoothness parameter. LSB: Least significant bit.

  18. Matlab function: SSPA.m Available on course homepage. Applies non-linearity to the input signal. The parameter A0 is hardcoded inside the function. The patameter A0 is referenced i units of LSB (least-significant bit) of the signal sent from the D/A converter. The smoothness parameter p is an input to the function. Three present values of p are proposed 1,10,100 (bad, fair, good)

  19. Amplifier non-linearity effects Link 1 BS1 MS1 Link 2 BS2 MS2 In-band disrtorion: Detoriation of own link. Out-of-band distortion: Detoration of the others link.

  20. In-band/out-of-band In-band distortion Out-of-band distortion

  21. Example of in-band distortion influence Without distortion With distortion

  22. Next problem Phase-noise

  23. Phase-noise: Imperfect LO BPF LNA LPF A/D This phase offset is a stocastic process = phase noise.

  24. Phase-Noise Spectrum

  25. Matlab-file: add_phase_noise.m • Link on course homepage • Generates phase-noise from given phase-noise spectrum, and multiplies it to the desired signal. • The phase-noise spectrum is specified by input parameters phase_noise_freq and phase_noise_power. • Three different ”pre-set” values given on course homepage (bad, fair, good) given in phase_noise_param.m. * *) The function is written by Alex Bar-Guy and is available on matlab central.

  26. Example: Influence of phase-noise With phase-noise Without phase-noise

  27. How should you simulate ? • Start with basic channel model • You should be able to do this yourself. • Introduce AM/AM and AM/PM using SSPA.m. • Introduce phase-noise using add_phase_noise.m.

  28. SNR and SINAD Signal power SNR= Thermal noise power Signal power SINAD= Distortion + Thermal noise Dominates at close distance. Often proportional to transmitted power

  29. SINAD and SNR versus range

  30. Estimating SNR and SINAD Estimate thermal noise power from part 1. Estimate signal power and distortion power from part 2 e.g. Using training sequence. Part1: Before transmission: Thermal noise only. Part2: Signal present X= S + N + E

  31. Theory versus Reality What theory ? Generally: Basic channel model. Present results versus SNR not SINAD

  32. Voice Band Transmission In Out FM modulator AM modulator FM de-modulator Out In AM de-modulator Power of output may be unrelated power of input. Difficult to use previous slides in this scenario.

  33. Wrap-up Propagation channel versus communication channel distinction. Basic channel model. Power amplifier distortion (AM/AM and AM/PM). Phase-noise (in up-/down-converters) Matlab functions SINAD versus SNR Voice-band transmission