1. EEE 461 1 Chapter 6 Matched Filters Huseyin Bilgekul EEE 461 Communication Systems II Department of Electrical and Electronic Engineering Eastern Mediterranean University  Matched Filters  Matched filters for white noise  Integrate and Dump matched filter  Correlation processing

2. EEE 461 2 Matched Filter The Matched Filter is the linear filter that maximizes: Recall Matched Filter h(t) H(f) r(t)=s(t)+n(t) R(f) r o (t)=s o (t)+n o (t) R o (f)

3. EEE 461 3 Matched Filter Design a linear filter to minimize the effect of noise while maximizing the signal. s(t) is the input signal and s 0 (t) is the output signal. The signal is assumed to be known and absolutely time limited and zero otherwise. The PSD, P n (f) of the additive input noise is also assumed to be known. Design the filter such that instantaneous output signal power is maximized at a sampling instant t 0, compared with the average output noise power:

4. EEE 461 4 Matched Filter The goal is maximize (S/N) out s(t)s(t) T T h(t)H(f)h(t)H(f) Threshold Detector Sampler t = t o r(t)=s(t)+n(t) R(f) r o (t)=s o (t)+n o (t) R o (f) s o (t) r(t)=s(t)+n(t) r o (t)=s o (t)+n o (t)

5. EEE 461 5 Matched Filter The matched filter does not preserve the input signal shape. The objective is to maximize the output signal-to-noise ratio. The matched filter is the linear filter that maximizes (S/N) out and has a transfer function given by: where S(f) = F[s(t)] of duration T sec. t 0 is the sampling time K is an arbitrary, real, nonzero constant. The filter may not be realizable.

6. EEE 461 6 Signal and Noise Calculation Signal output: Output noise power or variance Putting the pieces together gives: Simplify Using Schwartz’ Inequality. Equality occurs only if A(f) = K B*(f)

7. EEE 461 7 Signal and Noise Calculation Apply the Schwartz Inequality: Then we obtain: Maximum (S/N) out is attained when equality occurs if we choose:

8. EEE 461 8 Matched Filter for White Noise For a white noise channel, P n (f ) = N o /2 Here E s is the energy of the input signal. The filter H(f ) is: The output SNR depends on the signal energy E s and not on the particular shape that is used. Impulse response is the known signal wave shape played “Backwards” and shifted by t o.

9. EEE 461 9 Matched Filter for White Noise Increase in the time-bandwidth product does not change the output SNR. If a symbol lasts for T seconds, then there are 3 cases: (t o T) –t o < T gives a NONCAUSAL input response –t o > T gives a DELAY in deciding what was sent –t o = T gives the MINIMUM DELAY for a decision plus it is REALIZABLE.

10. EEE 461 10 Impulse Response of Matched Filter Thus, s(t) and h(t) have duration T. The delay is also T The output has duration 2T because s 0 (t) = s(t)*h(t). Note that the peak value is at T. 2T s(t)+n(t) so(t)so(t)

11. EEE 461 11 Impulse Response of Matched Filter The output is obtained by performing convolution s 0 (t) = s(t)*h(t).

12. EEE 461 12 MF Example for White Noise Consider the set of signals: Draw the matched filter for each signal and sketch the filter responses to each input T/2 T s1(t)s1(t) T s2(t)s2(t)

13. EEE 461 13 T/2 T h1(t)h1(t) T s1(t)s1(t) T s2(t)s2(t) MF Example for White Noise T/2 T h2(t)h2(t) T y 11 (t)=s 1 (t)*h 1 (t) T/2 T y 21 (t)=s 2 (t)*h 1 (t)

14. EEE 461 14 Integrate and Dump (Matched) Filter

15. EEE 461 15 Integrate and Dump (Matched) Filter Input Signal Backward Signal Matched Filter Impulse Response Matched Filter Output Signal

16. EEE 461 16 Integrate and Dump Realization of Matched Filter

17. EEE 461 17 Correlation Processing

18. EEE 461 18 Correlation Processing Theorem: For the case of white noise, the matched filter can be realized by correlating the input with s(t) where r(t) is the received signal and s(t) is the known signal wave shape. Correlation is often used as a matched filter for Band pass signals.

19. EEE 461 19 Correlation (Matched Filter) Detection of BPSK