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Flat fading occurs when there are obstacles moving in the path between the transmitterand receiver or when the transmitter and receiver are moving with respect to each other. It ismost commonly modelled as a time-varying channel gain that attenuates the received signal.The modifier “flat” implies that the loss in gain is uniform over all frequencies. In communications jargon, it is not frequency selective . This section begins by studying the loss of performance caused by a time-varying channel gain (using a modifiedversion of idsys.m ) and then examines the ability of an adaptive element (the automatic gain control, AGC)to make things right.

In the ideal system of the preceding section, the gain between the transmitter and the receiver wasimplicitly assumed to be unity. What happens when this assumptionis violated, when flat fading is experienced in midmessage? To examine this question, suppose that the channel gainis unity for the first 20% of the transmission, but that for the last 80% it drops by half.This flat fade can easily be studied by inserting the following code between the transmitterand the receiver parts of idsys.m .

lr=length(r);                % length of transmitted signal vector fp=[ones(1,floor(0.2*lr)),...    0.5*ones(1,lr-floor(0.2*lr))];  % flat fading profiler=r.*fp;                     % apply profile to transmitted signal vector
idsysmod1.m modification of idsys.m with time-varying fading channel (download file)

The resulting plot of the soft decisions in [link] (via plot([1:length(z)], z,'.') ) shows the effect of the fade in the latter 80% of the response. Shrinking the magnitude of the symbols ± 3 by half puts it in the decision region for ± 1 , which generates a large number of symbol errors. Indeed, the recovered message looks nothinglike the original.

Soft decisions with uncompensated flat fading.
Soft decisions with uncompensated flat fading.

[link] has already introduced an adaptive element designed to compensate for flat fading:the automatic gain control, which acts to maintain the power of a signal at a constant knownlevel. Stripping out the AGC code from agcvsfading.m >and combining it with the fading channel just discussed creates a simulation inwhich the fade occurs, but in which the AGC can actively work to restore the power of the received signalto its desired nominal value ds 1 .

ds=pow(r);                      % desired average power of signal lr=length(r);                   % length of transmitted signal vectorfp=[ones(1,floor(0.2*lr)),...     0.5*ones(1,lr-floor(0.2*lr))];  % flat fading profile r=r.*fp;                        % apply profile to transmitted signal vectorg=zeros(1,lr); g(1)=1;          % initialize gain nr=zeros(1,lr);mu=0.0003; % stepsizefor i=1:lr-1 % adaptive AGC element  nr(i)=g(i)*r(i); % AGC output  g(i+1)=g(i)-mu*(nr(i)^2-ds); % adapt gainend r=nr;                           % received signal is still called r
idsysmod2.m modification of idsys.m (download file) with fading plus automatic gain control

Inserting this segment into idsys.m (immediately after the time-varying fading channel modification) results in only a small number of errorsthat occur right at the time of the fade. Very quickly, the AGC kicks in to restore the received power.The resulting plot of the soft decisions (via plot([1:length(z)],z,'.') ) in [link] shows how quickly after the abrupt fade the soft decisions return to the appropriate sector. (Look for where thelarger soft decisions exceed a magnitude of 2.)

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Source:  OpenStax, Software receiver design. OpenStax CNX. Aug 13, 2013 Download for free at http://cnx.org/content/col11510/1.3
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