nrPerfectTimingEstimate

Perfect timing estimation

Syntax

[offset,mag] = nrPerfectTimingEstimate(pathGains,pathFilters)

Description

[offset,mag] = nrPerfectTimingEstimate(pathGains,pathFilters) performs perfect timing estimation. To find the peak of the channel impulse response, the function first reconstructs the impulse response from the channel path gains pathGains and the path filter impulse response pathFilters. The channel impulse response is averaged across all channel snapshots and summed across all transmit and receive antennas before timing estimation. The function returns the estimated timing offset offset and the channel impulse response magnitude mag.

Examples

Plot Channel Impulse Magnitude and Timing Offset for TDL-C Channel Model

Define a channel configuration structure using an nrTDLChannel System object. Use delay profile TDL-C from TR 38.901 Section 7.7.2.

tdl = nrTDLChannel;
tdl.DelayProfile = 'TDL-C';
tdl.DelaySpread = 100e-9;

Create a random waveform with a duration of 1 subframe.

tdlInfo = info(tdl);
Nt = tdlInfo.NumTransmitAntennas;
in = complex(zeros(100,Nt),zeros(100,Nt));

Transmit the input waveform through the channel.

[~,pathGains] = tdl(in);

Obtain the path filters used in channel filtering.

pathFilters = getPathFilters(tdl);

Estimate timing offset. The function also returns the channel impulse response magnitude for each receive antenna, summed across all transmit antennas.

[offset,mag] = nrPerfectTimingEstimate(pathGains,pathFilters);

Plot the magnitude of the channel impulse response and the timing offset estimate.

[Nh,Nr] = size(mag);
plot(0:(Nh-1),mag,'o:');
hold on;
plot([offset offset],[0 max(mag(:))*1.25],'k:','LineWidth',2);
axis([0 Nh-1 0 max(mag(:))*1.25]);
legends = "|h|, antenna " + num2cell(1:Nr);
legend([legends "Timing offset estimate"]);
ylabel('|h|');
xlabel('Channel Impulse Response Samples');

Input Arguments

pathGains — Channel path gains of fading process

N_CS-by-N_P-by-N_T-by-N_R complex matrix

Channel path gains of the fading process, specified as an N_CS-by-N_P-by-N_T-by-N_R complex matrix, where:

• N_CS is the number of channel snapshots.

• N_P is the number of paths.

• N_T is the number of transmit antennas.

• N_R is the number of receive antennas.

Data Types: single | double
Complex Number Support: Yes

pathFilters — Path filter impulse response

N_H-by-N_P real matrix

Path filter impulse response, specified as an N_H-by-N_P real matrix, where:

• N_H is the number of impulse response samples.

• N_P is the number of paths.

Each column of the matrix contains the filter impulse response for each path of the delay profile.

Data Types: double

Output Arguments

offset — Timing offset in samples

nonnegative integer

Timing offset in samples, returned as a nonnegative integer. The number of samples is relative to the first sample of the channel impulse response reconstructed from pathGains and pathFilters.

Data Types: double

mag — Channel impulse response magnitude

N_H-by-N_R real matrix

Channel impulse response magnitude for each receive antenna, summed across all transmit antennas, returned as an N_H-by-N_R real matrix.

• N_H is the number of impulse response samples.

• N_R is the number of receive antennas.

mag inherits its data type from pathGains.

Data Types: single | double

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™. (since R2024b)

The nrPerfectTimingEstimate function fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray (Parallel Computing Toolbox). For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Version History

Introduced in R2018b

R2024b: GPU array support

The nrPerfectTimingEstimate function adds support for GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).