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moving channel propagation conditions

syntax

out = ltemovingchannel(model,in)

description

example

out = ltemovingchannel(model,in) implements the moving propagation conditions specified in ts 36.104 [1]. the filtered waveform is stored in matrix out, where each column corresponds to the waveform at each of the receive antennas. the columns of matrix in correspond to the channel input waveforms at each transmit antenna. the input waveforms are filtered with the delay profiles as specified in the parameter structure model. the delay profiles are resampled to match the input signal sampling rate. the modeling process introduces delay on top of the channel group delay.

the time difference between the first multipath component and the reference time (assumed to be 0) follows a sinusoidal characteristic.

δτ=a2(1 sin(δω(t t0)))

where the offset t0 is

t0=inittime 3π2(δω)

if model.inittime is 0, the delay of the first multipath component is 0. if t = 0, δτ=0. relative delay between all multipath components is fixed.

two moving propagation scenarios are specified in ts 36.104 [1], annex b.4:

  • scenario 1 implements an extended typical urban with 200 hz doppler shift (etu200) rayleigh fading model with changing delays. the rayleigh fading model can be modeled using two different methods as described in model.modeltype. for scenario 1, model.inittime also controls the fading process timing offset. changing this value produces parts of the fading process at different points in time.

  • scenario 2 consists of a single non-fading path with unit amplitude and zero phase degrees with changing delay. no awgn is introduced internally in this model.

examples

generate a frame and filter it with the lte moving propagation channel.

rmc = ltermcdl('r.10');
[txwaveform,txgrid,info] = ltermcdltool(rmc,[1;0;1]);
chcfg.seed = 1;
chcfg.nrxants = 1;
chcfg.movingscenario = 'scenario1';
chcfg.samplingrate = 100000;
chcfg.inittime = 0;
rxwaveform = ltemovingchannel(chcfg,txwaveform);

input arguments

moving channel model, specified as a structure containing these fields.

parameter fieldrequired or optionalvaluesdescription
seedrequiredscalar value

random number generator seed. to use a random seed, set seed to zero.

note

  • to produce distinct results, use seed values in the range

    [0,231 – 1 – k(k-1)/2],

    where k = p × model.nrxants, the product of the number of transmit and receive antennas. seed values outside of this recommended range should be avoided as they may result in random sequences that repeat results produced using seed values inside the recommended range.

  • the moving channel random seed behavior is not affected by the state of matlab® random number generators, .

nrxantsrequired

positive scalar integer

number of receive antennas

movingscenariorequired

'scenario1', 'scenario2'

moving channel scenario

samplingraterequirednumeric scalar

input signal sampling rate, the rate of each sample in the rows of the input matrix, in.

inittimerequired

scalar value

fading process and timing adjustment offset, in seconds

normalizetxantsoptional

'on' (default), 'off'

transmit antenna number normalization, specified as:

  • 'on', ltefadingchannel normalizes the model output by 1/sqrt(p), where p is the number of transmit antennas. normalization by the number of transmit antennas ensures that the output power per receive antenna is unaffected by the number of transmit antennas.

  • 'off', normalization is not performed.

the following fields are required or optional (as indicated) only if movingscenario is set to 'scenario1'.

 ntermsoptional

16 (default)

scalar power of 2

number of oscillators used in fading path modeling.

 modeltypeoptional

'gmeds' (default), 'dent'

rayleigh fading model type.

  • 'gmeds', the rayleigh fading is modeled using the generalized method of exact doppler spread (gmeds), as described in [3].

  • 'dent', the rayleigh fading is modeled using the modified jakes fading model described in [2]

note

modeltype = 'dent' is not recommended. use modeltype = 'gmeds' instead.

 normalizepathgainsoptional

'on' (default), 'off'

model output normalization.

  • 'on', the model output is normalized such that the average power is unity.

  • 'off', the average output power is the sum of the powers of the taps of the delay profile.

data types: struct

input samples, specified as a numeric matrix. in has size t-by-p, where p is the number of transmit antennas and t is the number of time-domain samples. these waveforms are filtered with the delay profiles as specified in the parameter structure model. these delay profiles are resampled to match the input signal sampling rate. each column of in corresponds to the waveform at each of the transmit antennas.

data types: double | single
complex number support: yes

output arguments

filtered waveform, returned as a numeric matrix. each column of out corresponds to the waveform at each of the receive antennas.

data types: double | single
complex number support: yes

references

[1] 3gpp ts 36.104. “evolved universal terrestrial radio access (e-utra); base station (bs) radio transmission and reception.” 3rd generation partnership project; technical specification group radio access network. url: .

[2] dent, p., g. e. bottomley, and t. croft. “jakes fading model revisited.” electronics letters. vol. 29, 1993, number 13, pp. 1162–1163.

[3] pätzold, matthias, cheng-xiang wang, and bjørn olav hogstad. “two new sum-of-sinusoids-based methods for the efficient generation of multiple uncorrelated rayleigh fading waveforms.” ieee transactions on wireless communications. vol. 8, 2009, number 6, pp. 3122–3131.

version history

introduced in r2013b

see also

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