Signal Structure of the Starlink Ku-Band Downlink Todd E. Humphreys Peter A. Iannucci Zacharias M. Komodromos Andrew M. Graff Department of Aerospace Engineering and Engineering Mechanics The University of Texas at Austin

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Signal Structure of the Starlink Ku-Band Downlink

Todd E. Humphreys∗, Peter A. Iannucci∗, Zacharias M. Komodromos†, Andrew M. Graff†

∗Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin

†Department of Electrical and Computer Engineering, The University of Texas at Austin

Abstract—We develop a technique for blind signal identiﬁca-

tion of the Starlink downlink signal in the 10.7 to 12.7 GHz

band and present a detailed picture of the signal’s structure. Im-

portantly, the signal characterization offered herein includes the

exact values of synchronization sequences embedded in the signal

that can be exploited to produce pseudorange measurements.

Such an understanding of the signal is essential to emerging

efforts that seek to dual-purpose Starlink signals for positioning,

navigation, and timing, despite their being designed solely for

broadband Internet provision.

Index Terms—Starlink, signal identiﬁcation, positioning, time

synchronization, low Earth orbit

I. INTRODUCTION

In addition to revolutionizing global communications,

recently-launched broadband low-Earth-orbit (LEO) mega-

constellations are poised to revolutionize global positioning,

navigation, and timing (PNT). Compared to traditional global

navigation satellite systems (GNSS), they offer higher power,

wider bandwidth, more rapid multipath decorrelation, and

the possibility of stronger authentication and zero-age-of-

ephemeris, all of which will enable greater accuracy and

greater resilience against jamming and spooﬁng [1]–[5].

With over 3000 satellites already in orbit, SpaceX’s Starlink

constellation enjoys the most mature deployment among LEO

broadband providers. Recent demonstrations of opportunistic

Doppler-based positioning with Starlink signals [6]–[8] open

up exciting possibilities. But whether Starlink signals are

more generally suitable for opportunistic PNT—not only via

Doppler positioning—and whether they could be the basis of a

full-ﬂedged GNSS, as proposed in [5], remains an open ques-

tion whose answer depends on details of the broadcast signals,

including modulation, timing, and spectral characteristics. Yet

whereas the orbits, frequencies, polarization, and beam pat-

terns of Starlink satellites are a matter of public record through

the licensing databases of the U.S. Federal Communications

Commission [9], details on the signal waveform itself and

the timing capabilities of the hardware producing it are not

publicly available.

We offer two contributions to address this knowledge gap.

First, we develop a technique for blind signal identiﬁcation

of the Starlink downlink signal in the 10.7 to 12.7 GHz

band. The technique is a signiﬁcant expansion of existing

blind orthogonal frequency division multiplexing (OFDM)

signal identiﬁcation methods (see [10]–[12] and the references

therein), which have only been successfully applied to simu-

lated signals. Insofar as we are aware, blind identiﬁcation of

operational OFDM signals, including exact determination of

synchronization sequences, has not been achieved previously.

The technique applies not only to the Starlink Ku-band down-

link but generally to all OFDM signals except as regards some

steps required to estimate synchronization structures that are

likely unique to Starlink.

Second, we present a detailed characterization of the Star-

link downlink signal structure in the 10.7 to 12.7 GHz band.

This applies for the currently-transmitting Starlink satellites

(versions 0.9, 1.0, and 1.5), but will likely also apply for

version 2.0 and possibly later generations, given the need to

preserve backward compatibility for the existing user base.

Our signal characterization includes the exact values of syn-

chronization sequences embedded in the signal that can be

exploited to produce pseudorange measurements. Combining

multiple pseudorange measurements to achieve multi-laterated

PNT, as is standard in traditional GNSS, enables faster and

more accurate opportunistic position ﬁxes than the Doppler-

based positioning explored in [6]–[8], [13]. and can addition-

ally offer nanosecond-accurate timing, whereas even under the

optimistic scenario envisioned in [13], extracting timing from

Doppler-based processing of LEO signals yields errors on the

order of 0.1 to 1 ms.

II. SIGNAL CAPTURE

To facilitate replication of our work, and as a prelude to

our presentation of the signal model, we begin with a detailed

description of our signal capture system.

One might reasonably wonder whether a standard consumer

Starlink user terminal (UT) could be modiﬁed to capture wide-

band (hundreds of MHz) raw signal samples for Starlink signal

identiﬁcation. Not easily: operating the UT as development

hardware, which would permit capture of raw signal samples,

requires defeating security controls designed speciﬁcally to

prevent this. Moreover, the clock driving the UT’s downmixing

and sampling operations is of unknown quality and would

therefore taint any timing analysis of received signals.

We opted instead to develop our own system for Starlink

signal capture. Composed of off-the-shelf hardware and cus-

tom software, the system enables signal capture from one

Starlink satellite at a time with downmixing and sampling

referenced to a highly-stable GPS-disciplined oscillator.

Whereas the consumer Starlink UT operates as a phased

array of many separate antenna elements, our antenna is a

steerable 90-cm offset parabolic dish with a beamwidth of

approximately 3 degrees. Starlink orbital ephemerides pro-

vided publicly by SpaceX guide our selection and tracking

of overhead satellites. Only one or two Starlink satellites

illuminate a coverage cell at any one time with a data-bearing

beam [5]. To guarantee downlink activity, we solicit data by

arXiv:2210.11578v3 [eess.SP] 30 Aug 2023

downloading a high-deﬁnition video stream through a standard

Starlink UT co-located with our signal capture system.

Fig. 1 outlines our signal capture hardware and signal

pathways. A parabolic dish focuses signals onto a feedhorn

connected to a low-noise block (LNB) with a conversion gain

of 60 dB and a noise ﬁgure of 0.8 dB. The LNB is dual-

band, downconverting either 10.7–11.7 GHz (the lower band)

to 950–1950 MHz, or 11.7–12.75 GHz (the upper band) to

1100–2150 MHz. The antenna’s nominal gain is 40 dBi at

12.5 GHz, but there are losses of at least 4-5 dB due to lack

of a circular-to-linear polarizer and to feedhorn misalignment.

The signal capture system allows selection between narrow-

band (∼60 MHz) and wideband (∼1 GHz) signal capture

modes. For the narrowband mode, the output of the LNB is

fed to a transfer switch that diverts the signal through a tunable

bandpass ﬁlter for image rejection. Downstream hardware then

performs downmixing (consistent with the selected band),

additional bandpass ﬁltering, and 16-bit complex sampling

at 62.5 Msps. The downmixing operation in the LNB and

the downmixing and sampling operations in the downstream

hardware are phase-locked to a common GPS-disciplined

oven-controlled crystal oscillator (OCXO) to minimize the

effects of receiver clock variations on the received signals.

A 3-TB data storage array permits archival of several hours

of continuous data.

Anti-alias ﬁltering prior to sampling reduces the usable

bandwidth of the narrowband mode to approximately 60

MHz. Although this is much narrower than a single Star-

link channel, multiple overlapping captures can be combined

for a comprehensive analysis of all embedded narrowband

structures, as will be shown. However, the narrowband mode

cannot support a synoptic signal analysis. A second capture

mode—the wideband mode—addresses this deﬁciency. Based

on direct digital downconversion of 12-bit samples at 4096

Msps (real), the wideband mode is capable of alias-free

capture of the LNB’s entire lower band and most of its upper

band. The wideband mode’s limitations are storage, timing,

and noise ﬁgure: our current hardware permits only 1-second

segments of contiguous data to be captured before exhausting

the onboard memory, the sampling is not driven by the same

clock used for LNB downmixing (due to hardware limitations),

and the noise ﬁgure results in captured signals with a signal-

to-noise ratio (SNR) that is signiﬁcantly worse than for the

narrowband mode.

For the analysis described subsequently, signal identiﬁca-

tion was based on narrowband-mode-captured data except for

estimation of the primary synchronization sequence.

III. SIGNAL MODEL

Given its widespread use in wireless communications, one

might expect OFDM [14]–[18] to be the basis of the Ku-

band Starlink downlink. However, OFDM has historically been

avoided in satellite communications systems because its high

peak-to-average-power ratio leads to inefﬁcient transmit power

conversion [19]. Nonetheless, inspection of the Starlink power

spectrum generated from captured data reveals spectrally-ﬂat

frequency blocks with sharp edges, hallmarks consistent with

an OFDM hypothesis. Proceeding under the assumption of

an OFDM model, the problem of general signal identiﬁcation

narrows to one of identifying the values of parameters fun-

damental to OFDM signaling. This section introduces such

parameters as it presents a generic OFDM signal model and

a received signal model.

A. Generic OFDM Signal Model

The serial data sequence carrying an OFDM signal’s infor-

mation is composed of complex-valued symbols drawn from

the set {Xmik ∈C:m, i, k ∈N, k < N, i < Nsf}at a

rate Fs, known as the channel bandwidth. The subscript kis

the symbol’s index within a length-Nsubsequence known as

an OFDM symbol, iis the OFDM symbol’s index within a

length-Nsf sequence of OFDM symbols known as a frame,

and mis the frame index. Each symbol Xmik encodes one

or more bits of information depending on the modulation

scheme (e.g., 1 for BPSK, 2 for 4QAM, 4 for 16QAM,

etc.), with higher-order modulation demanding higher SNR

to maintain reception at a given acceptably-low bit-error rate

(BER) [18]. OFDM is a highly spectrally efﬁcient case of

multicarrier signaling in which each Xmik modulates one of N

mutually orthogonal subcarriers with overlapping spectra. Let

T=N/Fsbe the interval over which Ninformation symbols

arrive, and F=Fs/N = 1/T be the subcarrier spacing,

chosen as indicated to ensure subcarrier orthogonality over the

interval T. Then the baseband time domain signal produced

by the ith OFDM symbol of the mth frame is expressed over

0≤t<T as

x′

mi(t) = 1

√N

N−1

k=0

Xmik exp (j2πF tk)(1)

One recognizes this expression as an inverse discrete Fourier

transform, commonly implemented as an IFFT. Thus, one

can think of each Xmik as a complex-valued frequency-

domain coefﬁcient. To prevent inter-symbol interference (ISI)

arising from channel multipath, OFDM prepends a cyclically-

extended guard interval of length Tg=Ng/Fs, called the

cyclic preﬁx, to each OFDM symbol. With the addition of

the cyclic preﬁx, the OFDM symbol interval becomes Tsym =

T+Tg, with Tbeing the useful (non-cyclic) symbol interval.

Due to the time-cyclic nature of the IFFT, the prepending

operation can be modeled by a simple modiﬁcation of (1)

over 0≤t<Tsym:

xmi(t) = 1

√N

N−1

k=0

Xmik exp (j2πF (t−Tg)k)(2)

The function xmi(t)is called a time-domain OFDM symbol,

or simply an OFDM symbol when there is little risk of

confusion with its frequency-domain representation.

In all wireless OFDM protocols, subsequences of OFDM

symbols are packaged into groups variously called slots,

frames, or blocks. We will use the term frame to describe the

smallest grouping of OFDM symbols that is self-contained

in the sense that it includes one or more symbols with

predictable elements to enable receiver time and frequency

Fig. 1: Block diagram of the Starlink signal capture process.

synchronization. Let Nsf be the number of OFDM symbols in

a frame, Tf≥NsfTsym be the frame period, and

gs(t) = 1,0≤t < Tsym

0,otherwise

be the OFDM symbol support function. Then the time-domain

signal over a single frame can be written

xm(t) =

Nsf−1

i=0

xmi(t−iTsym)gs(t−iTsym)(3)

Over an inﬁnite sequence of frames, this becomes

x(t) = X

m∈N

xm(t−mTf)(4)

B. Received Signal Model

As x(t)passes through the LEO-to-Earth channel and later

through the receiver signal conditioning and discretization

operations, it is subject to multipath-induced fading, noise,

Doppler, delay, ﬁltering, and digitization.

In our signal capture setup, the receiving antenna is highly

directional, positioned atop a building with a clear view

of the sky, and only used to track satellites with elevation

angles above 50 degrees. Accordingly, the received signal’s

delay spread is negligible—similar to the wooded case of

[20]. In this regime, the coherence bandwidth appears to be

limited primarily by atmospheric dispersion in the Ku-band,

which, as reported in [21], amounts to sub-millimeter delay

sensitivity to dry air pressure, water vapor, and surface air

temperature for a 200 MHz-wide signal. In view of these

favorable characteristics, we adopt a simple additive Gaussian

white noise model for the LEO-to-Earth channel.

Doppler effects arising from relative motion between the

satellite and ground receiver are considerable in the Ku band

for the LEO-to-Earth channel. In fact, they are so signiﬁcant

that, for a channel of appreciable bandwidth, Doppler cannot

be modeled merely as imposing a frequency shift in the

received signal, as in [10], [11], or simply neglected, as in [12].

Instead, a more comprehensive Doppler model is required,

consisting of both a frequency shift and compression/dilation

of the baseband signal.

Let vlos be the magnitude of the line-of-sight velocity

between the satellite and receiver, modeled as constant over

an interval Tf, and let β≜vlos/c, where cis the free-space

speed of light. Note that lack of frequency synchronization

between the transmitter and receiver clocks gives rise to an

effect identical to motion-induced Doppler. In what follows,

we treat βas parameterizing the additive effects of motion-

and clock-error-induced Doppler, and we refer to βas the

carrier frequency offset (CFO) parameter.

For an OFDM channel bandwidth Fs, the compres-

sion/dilation effects of Doppler are negligible only if

βFsTsync ≪1, where Tsync is an interval over which OFDM

symbol time synchronization is expected to be maintained to

within a small fraction of 1/Fs. Violation of this condition

causes ISI in OFDM receiver processing as the receiver’s

discrete Fourier transform operation, implemented as an FFT,

becomes misaligned with time-domain OFDM symbol bound-

aries. In the context of standard OFDM signal reception, Tsync

may be as short as Tsym, whereas for the signal identiﬁcation

process described in the sequel, Tsync > NsfTsym.

Consider a transmitter in LEO at 300 km altitude, a station-

ary terrestrial receiver, elevation angles above 50 degrees, and

relative (transmitter-vs-receiver) clock quality consistent with

a temperature-compensated crystal oscillator. The resulting β

is limited to |β|<2.5×10−5. Suppose Tsync = 1 ms.

Then, to ensure βFsTsync <0.1,Fswould be limited to 4

MHz, well below the Starlink channel bandwidth. Therefore

our Doppler model must include both a frequency shift and

compression/dilation of the baseband signal.

With these preliminaries, we may introduce the baseband

analog received signal model as

ya(t) = x((t−τ0)(1 −β)) (5)

×exp j2πFc(1 −β)−¯

Fc(t−τ0)+w(t)

where Fcis the center frequency of the OFDM channel,

Fc≈Fcis the center frequency to which the receiver is

tuned, τ0is the delay experienced by the signal along the least-

time path from transmitter to receiver, and w(t)is complex-

valued zero-mean white Gaussian noise whose in-phase and

quadrature components each have (two-sided) spectral density

N0/2. Let the symbols {Xmik}be scaled such that x(t)

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SignalStructureoftheStarlinkKu-BandDownlinkToddE.Humphreys∗,PeterA.Iannucci∗,ZachariasM.Komodromos†,AndrewM.Graff†∗DepartmentofAerospaceEngineeringandEngineeringMechanics,TheUniversityofTexasatAustin†DepartmentofElectricalandComputerEngineering,TheUniversityofTexasatAustinAbstract—Wedevelopatechniqu...

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Signal Structure of the Starlink Ku-Band Downlink Todd E. Humphreys Peter A. Iannucci Zacharias M. Komodromos Andrew M. Graff Department of Aerospace Engineering and Engineering Mechanics The University of Texas at Austin

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