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Diversity-Combining Techniques

Module by: Sinh Nguyen-Le, Tuan Do-Hong. E-mail the authorsTranslated By: Sinh Nguyen-Le, Tuan Do-Hong

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The most common techniques for combining diversity signals are selection, feedback, maximal ratio, and equal gain.

Selection combining used in spatial diversity systems involves the sampling of MM size 12{M} {} antenna signals, and sending the largest one to the demodulator. Selection-diversity combining is relatively easy to implement but not optimal because it does not make use of all the received signals simultaneously.

With feedback or scanning diversity, the MM size 12{M} {} signals are scanned in a fixed sequence until one is found that exceeds a given threshold. This one becomes the chosen signal until it falls below the established threshold, and the scanning process starts again. The error performance of this technique is somewhat inferior to the other methods, but feedback is quite simple to implement.

In maximal-ratio combining, the signals from all of the MM size 12{M} {} branches are weighted according to their individual SNRs and then summed. The individual signals must be cophased before being summed.

Maximal-ratio combining produces an average SNR γM¯γM¯ size 12{ {overline {γ rSub { size 8{M} } }} } {} equal to the sum of the individual average SNRs, as shown below:

γ M ¯ = ∑ i = 1 M γ i ¯ = ∑ i = 1 M Γ = MΓ γ M ¯ = ∑ i = 1 M γ i ¯ = ∑ i = 1 M Γ = MΓ size 12{ {overline {γ rSub { size 8{M} } }} = Sum cSub { size 8{i=1} } cSup { size 8{M} } { {overline {γ rSub { size 8{i} } }} } = Sum cSub { size 8{i=1} } cSup { size 8{M} } {Γ} =MΓ} {}

where we assume that each branch has the same average SNR given by γi¯=Γγi¯=Γ size 12{ {overline {γ rSub { size 8{i} } }} =Γ} {}.

Thus, maximal-ratio combining can produce an acceptable average SNR, even when none of the individual i γγ size 12{γ} {} is acceptable. It uses each of the MM size 12{M} {} branches in a cophased and weighted manner such that the largest possible SNR is available at the receiver.

Equal-gain combining is similar to maximal-ratio combining except that the weights are all set to unity. The possibility of achieving an acceptable output SNR from a number of unacceptable inputs is still retained. The performance is marginally inferior to maximal ratio combining.

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