wlanPacketDetect

Estimate timing offset of OFDM packet

Syntax

startOffset = wlanPacketDetect(rxSig,cbw)

startOffset = wlanPacketDetect(rxSig,cbw,offset)

startOffset = wlanPacketDetect(rxSig,cbw,offset,threshold)

[startOffset,M] = wlanPacketDetect(___)

Description

startOffset = wlanPacketDetect(rxSig,cbw) estimates the timing offset between the start of received signal rxSig and the start of the detected preamble for channel bandwidth cbw. For more information, see Packet Detection Processing.

Note

This function supports packet detection of OFDM modulated signals only.

startOffset = wlanPacketDetect(rxSig,cbw,offset) specifies the sample at which the function begins autocorrelation processing relative to the start of the received signal.

startOffset = wlanPacketDetect(rxSig,cbw,offset,threshold) specifies the threshold that the decision statistic must meet or exceed to detect a packet.

[startOffset,M] = wlanPacketDetect(___) also returns the decision statistics of the packet detection algorithm for any of the input argument combinations in previous syntaxes.

Examples

Detect 802.11n Packet

Detect a received 802.11n™ packet at a signal-to-noise ratio (SNR) of 20 dB.

Create an HT configuration object and TGn channel object. Generate a transmit waveform.

cfgHT = wlanHTConfig;
tgn = wlanTGnChannel('LargeScaleFadingEffect','None');
txWaveform = wlanWaveformGenerator([1;0;0;1],cfgHT);

Pass the waveform through a TGn channel with an SNR of 20 dB. Detect the start of the packet.

snr = 20;
fadedSig = tgn(txWaveform);
rxWaveform = awgn(fadedSig,snr,0);
startOffset = wlanPacketDetect(rxWaveform,cfgHT.ChannelBandwidth)

startOffset = 4

Detect Delayed 802.11ac Packet

Detect a received 802.11ac™ packet that has been delayed. Specify an offset of 25 to begin the autocorrelation process.

Create an VHT configuration object and generate the transmit waveform.

cfgVHT = wlanVHTConfig;

txWaveform = wlanWaveformGenerator([1;0;0;1],cfgVHT,...
    'WindowTransitionTime',0);

Delay the signal by appending zeros at the start. Specify an offset of 25 for the beginning of autocorrelation processing. Detect the start of the packet.

rxWaveform = [zeros(100,1);txWaveform];
offset = 25;
startOffset = wlanPacketDetect(rxWaveform,cfgVHT.ChannelBandwidth,offset)

startOffset = 48

Calculate the detected packet offset by adding the returned startOffset and the input offset. This coarse approximation of the packet-start offset is useful for determining where to begin autocorrelation for the first packet and for subsequent packets when a multipacket waveform is transmitted.

pktOffset = offset + startOffset

pktOffset = 73

Detect Delayed 802.11a Packet

Detect a received 802.11a™ packet that has been delayed. No channel impairments are added. Set the input offset to 5 and use a threshold setting very close to 1.

Create an non-HT configuration object. Generate the transmit waveform.

cfgNonHT = wlanNonHTConfig;

txWaveform = wlanWaveformGenerator([1;0;0;1],cfgNonHT,...
    'WindowTransitionTime',0);

Delay the signal by appending zeros at the start. Set an initial offset of 5 and a threshold very close to 1. Detect the delayed packet.

rxWaveform = [zeros(20,1);txWaveform];

offset = 5;
threshold = 1-10*eps;
startOffset = wlanPacketDetect(rxWaveform,...
    cfgNonHT.ChannelBandwidth,offset,threshold)

startOffset = 15

Calculate the detected packet offset by adding the returned startOffset and the input offset.

totalOffset = offset + startOffset

totalOffset = 20

Generate WLAN Packet Decision Statistics

Return the decision statistics of a WLAN waveform that consists of five 802.11a packets.

Create a non-HT configuration object and a five-packet waveform. Delay the waveform by 4000 samples.

cfgNonHT = wlanNonHTConfig;
txWaveform = wlanWaveformGenerator([1;0;0;1],cfgNonHT, ...
    'NumPackets',5,'IdleTime',20e-6);
rxWaveform = [zeros(4000,1);txWaveform];

Generate and plot packet decision statistics for the waveform. The decision statistics show five peaks, which correspond to the first sample of each packet detected.

offset = 0;
threshold = 1;
[startOffset,M] = wlanPacketDetect(rxWaveform,cfgNonHT.ChannelBandwidth,...
    offset,threshold);
plot(M)
xlabel('Samples')
ylabel('Decision Statistics')

Input Arguments

rxSig — Received time-domain signal

complex-valued matrix

Received time-domain signal, specified as a complex-valued matrix of size N_S-by-N_R matrix. N_S is the number of time-domain samples in the received signal. N_R is the number of receive antennas.

Data Types: single | double
Complex Number Support: Yes

cbw — Channel bandwidth

'CBW5' | 'CBW10' | 'CBW20' | 'CBW40' | 'CBW80' | 'CBW160' | 'CBW320'

Channel bandwidth, specified as one of these values.

• 'CBW5' – Channel bandwidth of 5 MHz

• 'CBW10' – Channel bandwidth of 10 MHz

• 'CBW20' – Channel bandwidth of 20 MHz

• 'CBW40' – Channel bandwidth of 40 MHz

• 'CBW80' – Channel bandwidth of 80 MHz

• 'CBW160' – Channel bandwidth of 160 MHz

• 'CBW320' – Channel bandwidth of 320 MHz

Data Types: char | string

offset — Starting sample for autocorrelation process

0 (default) | nonnegative integer

Starting sample for the autocorrelation process, in samples after the start of the received signal, specified as a nonnegative integer. To detect startOffset for successive packets in multipacket waveforms, specify this input.

Note

Since the packet detection searches forward in time, the function cannot detect the first packet if the value of offset indicates a sample after the first L-STF.

Data Types: double

threshold — Decision statistic threshold

0.5 (default) | scalar in the interval (0, 1]

Decision statistic threshold that must be met or exceeded for the function to detect a packet, specified as a scalar in the interval (0, 1].

Data Types: double

Output Arguments

startOffset — Timing offset

nonnegative integer | [ ]

Timing offset, in samples, between the start of the received signal and the start of the detected preamble, returned as a nonnegative integer. This value, shifted by offset, indicates the detected start of a packet from the first sample of rxSig.

• The function returns this output as [] if it does not detect a packet, or if the threshold input is 1.

• The function returns this output as 0 if it detects the packet at the first sample of the waveform.

Data Types: double

M — Decision statistics

real-valued row vector

Decision statistics based on autocorrelation of the input signal, returned as a real-valued row vector of length N. The value of N depends on the starting location of the autocorrelation process and the number of samples before which the function detects a packet. When threshold is 1, the function returns this output as the decision statistics of the full waveform and the startOffset output as [].

For more information, see Packet Detection Processing.

Data Types: double

More About

L-STF

The legacy short training field (L-STF) is the first field of the 802.11™ OFDM PLCP legacy preamble. The L-STF is a component of EHT, HE, VHT, HT, and non-HT PPDUs.

The L-STF duration varies with channel bandwidth.

Channel Bandwidth (MHz)	Subcarrier Frequency Spacing, ΔF (kHz)	Fast Fourier Transform (FFT) Period (TFFT = 1 / ΔF)	L-STF Duration (TSHORT = 10 × TFFT / 4)
20, 40, 80, 160, and 320	312.5	3.2 μs	8 μs
10	156.25	6.4 μs	16 μs
5	78.125	12.8 μs	32 μs

Because the sequence has good correlation properties, receivers use it for start-of-packet detection, coarse frequency correction, and setting the AGC. The sequence uses 12 of the 52 subcarriers that are available per 20 MHz channel bandwidth segment. For 5 MHz, 10 MHz, and 20 MHz bandwidths, the number of channel bandwidth segments is one.

Algorithms

Packet Detection Processing

The packet detection algorithm is implemented as a double sliding window as described in OFDM Wireless LANs [1], Chapter 2. The autocorrelation of L-STF short training symbols is used to return an estimated packet-start offset. In a robust system, the next stage will refine this estimate with symbol timing detection using the L-LTF.

As shown in the figure, the received signal, r_n, is delayed then correlated in two sliding windows independently. The packet detection processing output provides decision statistics (m_n) of the received waveform.

• Window C autocorrelates between the received signal and the delayed version, c_n.

  $c_n={\displaystyle \sum }_{l=1}^{N_R}{\displaystyle \sum }_{K=0}^{D-1}{r}_{n+k,l}{r}_{n+k+D,l}^{*}$

• Window P calculates the energy received in the autocorrelation window, p_n.

  $p_n={\displaystyle \sum }_{l=1}^{N_R}{\displaystyle \sum }_{k=0}^{D-1}|r_{n+k+D,l}{|}^2$

• The decision statistics, m_n, normalize the autocorrelation by p_n so that the decision statistic is not dependent on the absolute received power level.

  $m_n=\frac{|c_n{|}^2}{{\left(p_n\right)}^2}$

  The decision statistics provide visual information resulting from the autocorrelation process that is useful when selecting the appropriate threshold value for the input waveform. The recommended default value of 0.5 for threshold favors false detections over missed detections considering a range of SNRs and various antenna configurations.

In the sliding window calculations, D is the period of the L-STF short training symbols and N_R is the number of receive antennas.

Packet detection processing follows this flow chart:

L_{STF_SYMBOL} is the length of an L-STF symbol.

Note

This function supports packet detection of OFDM modulated signals only.

References

[1] Terry, J., and J. Heiskala. OFDM Wireless LANs: A Theoretical and Practical Guide. Indianapolis, IN: Sams, 2002.

Extended Capabilities

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

Version History

Introduced in R2016b