Supposing we have multiple samples of a scaled signal $x$ given by $y_i=a_ix+n_i$ where $n_i$ is AWGN how does the bit accuracy of estimation of $x$ improve with averaging of samples $y_i$ (number of bits per sample)? Assume we know $a_i$.

Say I want $x$ with an error affecting only $m$ bits does $\log m$ samples of $y_i$ suffice?

  • $\begingroup$ Can you clarify more (mathematically), what you mean by bit accuracy and what you would average to increase accuracy? Do the $a_i$ change over time/measurements? $\endgroup$ Commented Jan 8, 2017 at 9:19
  • $\begingroup$ @MaximilianMatthé $a_i$ changes but we know $a_i$ and so for all purposes we can think of $a_i=1$ I think. $\endgroup$
    – Turbo
    Commented Jan 8, 2017 at 9:57


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Browse other questions tagged or ask your own question.