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Wireless Communication Elec 534 Set III October 11, 2007

Wireless Communication Elec 534 Set III October 11, 2007. Behnaam Aazhang. Reading for Set 3. Tse and Viswanath Chapters 5.4,6 Appendices B.8,B.9 Goldsmith Chapters 4. Model. A simple discrete time model where h is a complex Gaussian distributed fading coefficient

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Wireless Communication Elec 534 Set III October 11, 2007

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  1. Wireless CommunicationElec 534Set IIIOctober 11, 2007 Behnaam Aazhang

  2. Reading for Set 3 • Tse and Viswanath • Chapters 5.4,6 • Appendices B.8,B.9 • Goldsmith • Chapters 4

  3. Model • A simple discrete time model where h is a complex Gaussian distributed fading coefficient • Channel distribution information (CDI) at transmitter and receiver • Channel state information at receiver (and CDI) • Channel state information at transmitter and receiver (and CDI)

  4. Channel Distribution Information (CDI) • Achievable rate • Finding the maximizer is non trivial • For Rayleigh independent channel coefficients • Maximizing input is discrete with finite number of mass points • Mass at zero

  5. Channel Distribution Information (CDI) • Achievable rate computed numerically • Maximizing input distribution computed numerically • Not much to discuss—little analytical results

  6. CSI Model • State of the channel S (a function of h ) • Known to the receiver as V • Known to the transmitter as U

  7. CSIR • Channel state as a part of channel output since fading (or more precisely CSIR) is independent of the channel input r b v n

  8. CSIR • Proof

  9. Ergodic • The achievable rate when CSIR but no CSI at transmitter

  10. Ergodic Capacity • The model • Perfect channel state information at receiver

  11. Ergodic • The achievable rate is not a variable in time • If channel gain changes instantaneously the rate does not change • The rate is achieved over a long long codebook across different realizations of the channel • Long long decoding delay

  12. Fading • Fading does not improve Ergodic capacity • The key to the proof is Jensen’s inequality

  13. Example • A flat fading (frequency nonselective) with independent identically distributed channel gain as

  14. Example • CSIR no CSIT • Other system assumptions

  15. Example • The three possible signal to noise ratios

  16. Example • Ergodic capacity

  17. Example • Average SNR • The capacity of AWGN channel with the average SNR

  18. CSITR r b v u n

  19. CSITR • The mutual information • Capacity when there is CSI at transmitter and receiver • The original definition is not applicable • Define fading channel capacity

  20. CSITR • A result for multi-state channel due to Wolfowitz capacity for each state • Applied to CSITR

  21. Ergodic Capacity • Channel state information at transmitter and receiver • Power adjusted with constraint

  22. Achievable Rate with CSITR • Constraint optimization • Solving via differentiation

  23. Power Control • The solution is • Temporal water filling • Variable rate and variable power • Different size code books • Multiplexing encoders and decoders

  24. Power Control Minimum Channel Quality Threshold Allocated Power Better Channels

  25. Water Filling Solution

  26. Capacity with CSITR • The maximized rate • The threshold not a function of average power limit

  27. Power Control for Fading Channels

  28. Example • A flat fading (frequency nonselective) with independent identically distributed channel gain as

  29. Example • CSITR • Other system assumptions

  30. Example • The three possible signal to noise ratios

  31. Example • Calculate the threshold • If the weakest channel is not used a consistent threshold emerges

  32. Example • Ergodic capacity

  33. Example • Average SNR • The capacity of AWGN channel with the average SNR

  34. Probability of Outage • Achieving ergodic channel capacity • Codewords much be longer than coherence time • Slow fading channels have long coherence times • Ergodic capacity more relevant in fast fading cases

  35. Outage • A burst with signal to noise ratio • Probability of outage • Capacity with outage • Information sent over a burst • Limited decoding delay • Nonzero probability of decoding error

  36. Outage • The minimum required channel gain depends on the target rate. • When instantaneous mutual information is less than target rate depends on the channel realization

  37. Outage • Probability of outage (CSIR) • Fading channel (CSIR)

  38. CSI at Transmitter and Receiver • Use CSITR to meet a target rate • Channel inversion • Minimize outage • Truncated channel inversion

  39. Outage • Probability of outage with CSITR • Fading channel with CSITR

  40. Power Control • Outage minimization • The solution for CSITR • Truncation with channel inversion

  41. Power Control Minimum Channel Quality Threshold Rayleigh PDF Allocated Power Better Channels

  42. Minimum Channel Quality Threshold Power Control Realization

  43. Outage Capacity • Target probability of outage • Fixed power • The outage capacity

  44. Frame Error Rate • An appropriate performance metric • In many examples, probability of outage is a lower bound to Frame Error Rate

  45. Frequency Selective • Recall the input output relationship

  46. Capacity for Frequency Selective Channels • Consider a time invariant channel • CSI is available at transmitter and receiver • Block frequency selective fading • An equivalent parallel channel model

  47. CSITR: Frequency Selective • The sum of rates • The power distribution

  48. Power Control • The power distribution threshold • Spectral water filling • Variable rate and variable power across channels • Different size code books • Multiplexing encoders and decoders

  49. Achievable Rate • The rate

  50. Frequency Selective Fading • Continuous transfer function • Power distribution across spectrum

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