delay profile and fluorescent lighting effects -凯发k8网页登录

delay profile effects

create vht configuration object. set the sample rate to 80 mhz.

cfgvht = wlanvhtconfig;
fs = 80e6;

generate random binary data and create a transmit waveform parameterized by the vht configuration object.

d = randi([0 1],8*cfgvht.psdulength,1);
testwaveform = wlanwaveformgenerator(d,cfgvht);

create a tgac channel object. set the delay profile to 'model-a', which corresponds to flat fading. disable large-scale fading effects.

tgacchan = wlantgacchannel('samplerate',fs, ...
    'channelbandwidth',cfgvht.channelbandwidth, ...
    'delayprofile','model-a', ...
    'largescalefadingeffect','none');

pass the transmitted waveform through the tgac channel.

rxmodela = tgacchan(testwaveform);

set the delay profile to model-c, which corresponds to a multipath channel with 14 distinct paths and a 30 ns rms delay spread. the maximum delay spread is 200 ns, which corresponds to a coherence bandwidth of 2.5 mhz.

release(tgacchan)
tgacchan.delayprofile = 'model-c';

pass the waveform through the model-c channel.

rxmodelc = tgacchan(testwaveform);

create a spectrum analyzer and use it to visualize the spectrum of the received signals.

sascope = spectrumanalyzer(samplerate=fs, ...
    showlegend=true,channelnames={'model-a','model-c'},...
    averagingmethod='exponential',forgettingfactor=0.99);
sascope([rxmodela rxmodelc])

as expected, the frequency response of the model-a signal is flat across the 80 mhz bandwidth. conversely, the model-c frequency response varies because its coherence bandwidth is much smaller than the channel bandwidth.

fluorescent effects

release the tgac channel, and set its delay profile to 'model-d'. disable the fluorescent lighting effect.

release(tgacchan)
tgacchan.delayprofile = 'model-d';
tgacchan.fluorescenteffect = false;

to better illustrate the doppler effects of fluorescent lighting, change the bandwidth and sample rate of the channel. generate a test waveform of ones.

tgacchan.channelbandwidth = 'cbw20';
fs = 20e6;
tgacchan.samplerate = fs;
testwaveform = ones(5e5,1);

to ensure repeatability, set the global random number generator to a fixed value.

rng(37)

pass the waveform through the tgac channel.

rxsig0 = tgacchan(testwaveform);

enable the fluorescent lighting effect. reset the random number generator, and pass the waveform through the channel.

release(tgacchan)
tgacchan.fluorescenteffect = true;
rng(37)
rxsig1 = tgacchan(testwaveform);

determine the time axis and channel filter delay.

t = ((1:size(rxsig0,1))'-1)/fs;
fdelay = tgacchan.info.channelfilterdelay;

plot the magnitude of the received signals while accounting for the channel filter delay.

plot(t(fdelay 1:end),[abs(rxsig0(fdelay 1:end)) abs(rxsig1(fdelay 1:end))])
xlabel('time (s)')
ylabel('magnitude (v)')
legend('fluorescent off','fluorescent on','location','best')

fluorescent lighting introduces a doppler component at twice the power line frequency (120 hz in the u.s.).

confirm that the peaks are separated by approximately 0.0083 s (inverse of 120 hz) by measuring distance between the second and third peaks.

[~,loc] = findpeaks(abs(rxsig1(1e5:4e5)));
peaktimes = loc/fs;
peakseparation = diff(peaktimes)

peakseparation = 0.0085