principles of ultra-reliable low latency communications (URLLC) · 2018-06-11 · principles of ultra-reliable low latency communications (URLLC) Petar Popovski Aalborg University

principles of ultra-reliable low latency

communications (URLLC)

Petar PopovskiAalborg University

Denmark

[email protected]

5G V2X Communications @ KCL, London, June 11, 2018


outline

▪ future connectivity landscape

▪ URLLC performance and statistics

▪ URLLC building blocks

▪ wireless network slicing in 5G


the future wireless connectivity landscape

▪ can be seen as eigenvalues for composing services,

e.g. in Virtual Reality,

rather than three isolated services.


future wireless connectivity landscape

5G but a lot of (great!) other wireless systems

▪ connectivity type not necessarily provided by the 5G radio interface

▪ LPWA, 802.11ah, etc.


distilled service requirements

eMBB

▪ acceleration of 4G, large payloads, active over longer periods

▪ maximize rate, moderate reliability (e.g. 10E-3)

mMTC

▪ fix low rate, unknown active subset from a massive device set

▪ maximize arrival rate, low reliability (e.g. 10E-1)

URLLC

▪ intermittent transmissions, but from a much smaller device set

▪ offer high reliability (e.g. 10E-5) while localized in time


the IoT modes: massive and ultra-reliable access

100 Mbps 95% of the time

or100 kbps 99.999% of the

time

error probability

da

ta r

ate

reliability limit

for control

information

1 Mbps from 100 devices

or10 kbps from 10000 devices

# devices

da

ta r

ate

access

protocol

limit


adoption of ultra-reliable communication

we need to divide the applications into two groups

▪ cable replacement

how would we design a system

if we could trust to the wireless

as much as to the wired?

▪ ”native” wireless applications

which new systems can we think of once

we are empowered with wireless connectivity?


MTC use cases

mMTC▪ environmental monitoring

of large areas

▪ large infrastructuresroads, ports, industrial plants

▪ available parking places

▪ management of object fleets

vehicles, bicycles

URLLC▪ commercial and public safety

▪ industrial control and automation

▪ smart energy and smart grid

▪ V2X and UAV control

▪ Augmented Reality (AR) and digital interaction with physical objects


a communication engineer models known unknowns

channel

state

noise interference

objective: find 𝛼 and, if 𝛼 = 1, find also 𝑥

a simple communication-theoretic model

𝑦 = ℎ ∙ 𝛼 ∙ 𝑥 + 𝑧 + 𝑖

user activity


ultra-reliability requires to

▪ model accurately the known unknowns

▪ bound the impact of the unknown unknowns

▪ the standard culprit 𝑧 seems easy

▪ interference can be arbitrarily varying


𝑦 = ℎ ∙ 𝛼 ∙ 𝑥 + 𝑧 + 𝑖


sources of uncertainty

▪ activity 𝛼 is the problem of a MAC protocol

▪ ℎ is the problem of channel estimation

and channel knowledge

▪ 𝑖 is a matter of interference management

and spectrum regulation

– spectrum license is paid to acquire the right to

control interference.


𝑦 = ℎ ∙ 𝛼 ∙ 𝑥 + 𝑧 + 𝑖


the worst case is when there is no prior informationabout the user activity

▪ random access

grant-free access means thatthe packet reception in the uplink

is not conditioned on a correct downlink reception

▪ can improve latency, even reliability

its uncertainty is removed by

▪ scheduling

▪ the receiver predicts the activity variable

the user activity 𝛼


URLLC performance and statistics


latency-reliability characterization

latency t

tR: time of data reception

reliability Pr(𝑡𝑅 ≤ 𝑡)

11-Pe

diversity:

time?

frequency

antennas

interfaces


design targets

latency

reliability

1

broadband rate-

oriented systems

latency

reliability

1

ultra-reliable low latency

communication URLLC


▪ in absence of interference,

we need to characterize the lower tail of 𝛾𝑆

▪ if 𝛾𝑆 is known,

we need to characterize the upper tail of 𝛾𝐼

a simple error model

Pr 𝐸 = Pr𝛾𝑠

1 + 𝛾𝐼< 𝛾𝑡ℎ

SINR


▪ assume that the interference is absent.

▪ we (somehow) know that the channel is Rayleigh.

▪ the target error rate is 𝜀𝑈, average SNR is ҧ𝛾𝑆

how do we choose the rate R?

channel uncertainty in URLLC

Pr 𝐸 = Pr log2 1 + 𝛾𝑠 < 𝑅

𝑅 = log2 1 + ҧ𝛾𝑆 ln1

1 − 𝜀𝑈where is the problem?


▪ the knowledge of average SNR

is based on n collected samples

▪ when n is low,

the rate should R be chosen

very conservatively

▪ online update of the estimate

and rate (or power) adaptation

channel uncertainty in URLLC

P. Popovski et al., ”Ultra-Reliable Low Latency Communication is Difficult: A Statistical

Assessment”, in preparation


building blocks for URLLC


▪ channel models

▪ transmission of short packets

▪ high diversity

▪ lean protocol design with respect to latency

– focus on control information

▪ network architecture

▪ wireless slicing and coexistence with other services


▪ channel models

▪ transmission of short packets

▪ high diversity

▪ lean protocol design with respect to latency

– focus on control information

▪ network architecture

▪ wireless slicing and coexistence with other services


currently there is lack of experimental evidence

for URC-relevant statistics of wireless channels

initial analysis of common wireless channel models in

URC regime

▪ block fading

▪ 𝑃𝑅 is the minimal SNR to decode data rate 𝑅

▪ the analysis reveals the URC-behavior:

Pr𝑃𝑅ത𝑃< 𝐿 ≈ 𝜀 ≈ 𝛼

𝑃𝑅ത𝑃

𝛽

wireless channel model behavior

in ultra-reliable regime


two-wave model with equal amplitudes

represents one of the worst cases

deterministic two-path model

HTX

HRX

VTW =Gλ

4⇡dLe− j 2⇡

λdL + Γ

Gλ

4⇡dRe− j 2⇡

λdR

where dL/ dR is the direct/ reflected path distance.

envelope

r = |VTW | = |⇢1 + ⇢2 exp jφ|

P. Popovski (Aalborg Uni) ult ra-reliable wireless ITA, San Diego, Feb 2017 6 / 17

outdoor physical setupoutdoor physical setup


indoor case dominated by

diffuse components,

good for high reliability

indoor physical setup

P. Eggers, M. Angjelichinoski, and P. Popovski, ”Wireless Channel Modeling Perspectives for

Ultra-Reliable Low Latency Communications”, available on Arxiv, 2018.


an example of a short packet format

UNB (ultra narrowband) system

reliability of the packet reception is a product of the

reliabilities of different parts

Pr 𝑠𝑢𝑐𝑐𝑒𝑠𝑠 = Pr 𝑃𝐴 Pr 𝑠𝑦𝑛𝑐 Pr 𝐼𝐷 Pr 𝑑𝑎𝑡𝑎 …

5G V2X Communications @ KCL, London, June 11, 2018Philippe Petit,

http://www.msnbc.com/msnbc/philippe-petit-twin-towers-balancing-act-remembered#slide1

▪ repetition coding for control information inefficient

▪ the proverbial 1-bit feedback becomes questionable


communication theory and protocol information


at short blocklengths there is a penalty

that keeps the rate away from capacity.

AWGN

SNR 0 dB

fundamental theory of finite blocklength transmission


▪ low SNR

▪ 10 bytes control information

▪ 10 bytes data

▪ same amount of channel uses

probability of error

10e-3

probability of error

10e-6

gain in reliability


mixing data and control information has energy cost

M

D

time

M

Dfrequency

time

fre

qu

en

cy

the notion of frame in cellular

systems should be revisited


separated data and metadata

useful for energy efficiencydata for Bob, Carol turns off her

receiver after the metadata

Alice

Bob Carol

joint data and metadata

better coding of the metadata

however, everybody decodes

everything

Alice

Bob Carol

connection between packetization and energy efficiency


some observations

▪ basic tradeoff between

energy efficiency and ultra-reliability

▪ departure from the common causal relationship

metadata -> data

▪ low latency usually means sending with

few channel uses (DoF)

– DoF can be increased in e.g. frequency or space


downlink communication to K users

▪ a user is active and there is a packet for her

with probability q.

▪ the message for each active user is drawn randomly

from a set of predefined message sizes.

▪ metadata should inform about

▪ who is active

▪ the message size.

▪ K. F. Trillingsgaard and P. Popovski, "Downlink Transmission of Short Packets:

Framing and Control Information Revisited," in IEEE Transactions on

Communications, vol. 65, no. 5, pp. 2048-2061, May 2017.

example:

a theoretical treatment of downlink framing


conventional framing

with pointers

example:

a theoretical treatment of downlink framing

ptr 2

ptr 3 UG 1 UG 2 UG 3

ptr 4 UG 4

m essages withm essage sizes messages wit h

alternative framing


▪ new tradeoff arises for short packets– latency is minimized when all packets are jointly encoded;

– power is minimized when each packet is encoded separately.

K=32 users

latency-energy tradeoff


massive MIMO and ultra-reliability

pros

▪ very high SNR links

▪ quasi-deterministic links, fading immunity

▪ extreme spatial multiplexing capability

cons

▪ expensive CSI acquisition procedure

▪ additional protocol steps


massive MIMO/URLLC: mitigating the CSI problem

downlink beamforming based on channel structure

non-coherent energy detection in the uplink

A. Sabin-Bana, M. Angjelichinoski, E. de Carvalho and P. Popovski, ”Massive MIMO for Ultra-

reliable Communications with Constellations for Dual Coherent-noncoherent Detection”, in

IEEE WSA, Bochum, 2018.


1

latency:x

reliability:P(X≤x)

latencydistribution

Pe

timeout

TransmissionerrorsInfrastructurefailures

cloning

2-out-of-3

transmission

strategies

multi-interface transmission

interface diversity


results based on lab measurements▪ 1 day, 100 ms interval

▪ Wi-Fi– achieves 10 ms for 90% of

packets

– but 99% requires almost 100 ms

▪ cellular: LTE and HSPA– also requires ~100 ms for 99%

▪ cloning (1 copy per IF)– 99% at 25 ms

– 99.999% at 60 ms latency1 2 5 10 20 50 100 200 500

l [ms]

0.99999

0.9999

0.999

0.99

0.9

0

RTT

LTE

HSPA

Wi-Fi

Cloning all

2-out-of-3

interface diversity

experimental results

J. J. Nielsen, R. Liu, and P. Popovski, “Ultra-Reliable Low Latency Communication

(URLLC) using Interface Diversity”, IEEE Transactions on Communications,

accepted, available at ArXiv, 2017.


* Source: Ciscus Sarasota

final remarks: protocol challenge is immensely larger

9. RRC Conn. Reconf. Compl.

8. RRC Conn. Reconfiguration

7. RRC Security Mode Complete

6. RRC Security Mode Command

5. RRC Conn. Setup Complete

4.b. RRC Conn. Setup

4.a. Contention resolution

3. RRC Conn. Request

2. Random access response

1. Random Access preamble

UE eNB

10. Small Data Payload

access

Attempt

connection

establishment


summary and outlook

▪ ultra-reliable wireless has the potential to

profoundly change systems and devices

▪ essential:

▪ short packet transmission

▪ communication-theoretic attention to the control information

▪ every step in the protocol needs a careful reliability design

▪ careful use of diversity

▪ large number of steps in real protocols

impair reliability and latency

▪ lean protocol design

coexistence of URLLC

with the other 5G services

joint work with

Kasper F. Trillingsgaard, Aalborg University, Denmark

Osvaldo Simeone, King’s College London, UK

Giuseppe Durisi, Chalmers University, Sweden



reminder: distilled service requirements

eMBB

▪ acceleration of 4G, large payloads, active over longer periods

▪ maximize rate, moderate reliability (e.g. 10E-3)

mMTC

▪ fix low rate, unknown active subset from a massive device set

▪ maximize arrival rate, low reliability (e.g. 10E-1)

URLLC

▪ intermittent transmissions, but from a much smaller device set

▪ offer high reliability (e.g. 10E-1) while localized in time


the problem of slicing

slicing: share the resource while providing

heterogeneous guarantees to different services

uplink scenario

more challenging

due to lack of coordination

eMBB mMTCURLLC


two types of slicing

eMBB mMTC URLLC idle

fre

que

nc

y

t ime

fre

que

nc

y

t ime

fre

que

nc

ies

rese

rved

for

UR

LL

C

freq

ue

nc

ies

all

oc

ate

dfo

r U

RL

LC

non-orthogonal

eMBB mMTC URLLC idlefr

eq

ue

nc

y

t ime

fre

que

nc

y

t ime

fre

que

nc

ies

rese

rved

for

UR

LL

C

freq

ue

nc

ies

all

oc

ate

dfo

r U

RL

LC


fre

que

nc

y

t imefr

eq

ue

nc

yt ime

fre

que

nc

ies

rese

rved

for

UR

LL

C

freq

ue

nc

ies

all

oc

ate

dfo

r U

RL

LC

orthogonal


system model

▪ 𝐹 frequency radio resources

▪ 𝑆 minislots

▪ eMBB transmission takes one

frequency resource

▪ 𝑎𝑈 is the probability of active

URLLC device in a minislot

▪ an URLLC transmission

spreads over 𝐹𝑈 frequencies

▪ 𝐴𝑀 is the Poisson-distributed

number of active mMTCs

radio resource at a specific frequency channelfr

equ

en

cy

ch

an

ne

l

t imeminislot

t ime slot


1

2

3

4

5

6

7

Fig. 3. An example of time-frequency grid with F = 7 resources and nS = 6 minislots. A single resource (frequency channel)

is allocated for mMTC transmission. Each URLLC transmission is spread over FU = 4 frequency channels.

since this is the key transmission phase for this type of traffic, due to the massive population of

devices. Extensions of our model will be discussed in Section V-B.

Each radio resource f isassumed to bewithin the time- and frequency-coherence interval of the

wireless channel, so that the wireless channel coefficients are constant within each radio resource.

Furthermore, we assume that the channel coefficients fade independently across the F radio

resources. The channel coefficients of the eMBB, URLLC, and the mMTC devices, which we

denote by HB ,f , HU,f , and Hm,f , m 2 { 0, . . . , AM } ,1 are independent and Rayleigh distributed,

i.e., HB ,f ⇠ CN (0,ΓM ), HU,f ⇠ CN (0,ΓU ), and Hm,f ⇠ CN (0,ΓM ) for m 2 { 0, . . . , AM }

across all radio resources f 2 1, ..., F . The channel gains for the three services in a radio resource

f are denoted by GB ,f = |HB ,f |2, GU,f = |HU,f |2, and Gm,f = |Hm,f |2 for m 2 1, ..., AM .

The average transmission power of all devices is normalized to one. The differences in the

actual transmission power across various users and in the path loss are accounted for through

the average channel gains ΓB , ΓU , and ΓM . Furthermore, the power of the noise at the BS is

1Throughout, we use the convention that the subscripts B , U , and M indicate a quantity referring to eMBB, URLLC, and

mMTC, respectively.

8


the received signal in a minislot

𝐘𝑠,𝑓 = 𝐻𝐵,𝑓𝐗𝐵,𝑓 + 𝐻𝑈,𝑓𝐗𝑈,𝑠,𝑓 +

𝑚=1

𝐴𝑀

𝐻 𝑚 ,𝑓𝐗 𝑚 ,𝑠,𝑓 + 𝐙𝑠,𝑓

not a classical multiple access channel

▪ different arrivals, different decoding criteria, etc.

independent Rayleigh-faded 𝐻𝑖,𝑓

if there is no transmission, 𝐗𝑖,𝑓 = 0


some more bits and pieces about the model

eMBB

▪ has a full CSI and transmits with channel inversion

▪ not transmitting w.p. 1 − 𝑎𝐵 results in outage

𝑟𝐵,𝑓 = log2 1 + 𝐺𝐵,𝑓tar

URLLC

▪ find maximal rate 𝑟𝑈 that satisfies 𝜀𝑈

▪ no CSIT and no power adaptation

Pr 𝐸𝑈 =Pr1

𝐹𝑈

𝑓=1

𝐹𝑈

log2 1 + 𝐺𝑈,𝑓 < 𝑟𝑈 ≤ 𝜀𝑈


some more bits and pieces about the model

mMTC: use of successive interference cancellation (SIC)

SNRs: 𝐺[1] ≥ 𝐺[2] ≥ ⋯ ≥ 𝐺[𝐴𝑀]

SINR: 𝜎 𝑚0=

𝐺[𝑚0]

1+σ𝑚=𝑚0+1𝐴𝑀 𝐺[𝑚]

decoding condition: log2 1 + 𝜎 𝑚0≥ 𝑟𝑀


the reliability diversity

𝜀𝑈 ≪ 𝜀𝐵 ≪ 𝜀𝑀design that benefit from heterogeneous reliability requirements

example of interfering eMBB and URLLC:

(1 − 𝜀𝑈)1 − 𝜀𝑈 1 − 𝜀𝐵

′

≥ (1 − 𝜀𝐵)


the reliability diversity

𝜀𝑈 ≪ 𝜀𝐵 ≪ 𝜀𝑀design that benefit from heterogeneous reliability requirements

example of interfering eMBB and URLLC:

(1 − 𝜀𝐵) always ≤ (1 − 𝜀𝑈)


slicing for eMBB and URLLC

orthogonal non-orthogonal

with SIC

Pr1

𝐹𝑈

𝑓=1

𝐹𝑈

log2 1 +𝐺𝑈,𝑓

1 + 𝐺𝐵,𝑓tar < 𝑟𝑈 ≤ 𝜀𝑈


slicing for eMBB and URLLC

non-orthogonal

with puncturing

perspective of the

eMBB

eMBB uses erasure code of rate 1 −𝑘

𝑆

and thus has a decreased rate


slicing for eMBB and URLLC: results

Γ𝑈 > Γ𝐵

0 2 4 6 8 10 12

r B ,sum

0.0

0.5

1.0

1.5

2.0

2.5

3.0

r U

orthogonal

orthogonal (LB)

SIC

SIC (LB)

puncturing

puncturing (LB)


slicing for eMBB and URLLC: results

Γ𝑈 < Γ𝐵

0 5 10 15 20 25 30 35 40

r B ,sum

0.0

0.2

0.4

0.6

0.8

1.0

1.2

r Uorthogonal

orthogonal (LB)

SIC

SIC (LB)

puncturing

puncturing (LB)


slicing for eMBB and mMTC

we look into a single radio frequency resource

▪ orthogonal slicing achieved by time-sharing

▪ non-orthogonal slicing achieved by SIC

SINR: 𝜎 𝑚0=

𝐺[𝑚0]

1+𝐺𝐵,𝑓tar+σ𝑚=𝑚0+1

𝐴𝑀 𝐺[𝑚]


slicing for eMBB and mMTC: results

three regimes

(1) small 𝑟𝐵 (2) intermediate 𝑟𝐵 (3) large 𝑟𝐵

0 1 2 3 4 5 6 7

r B

0

20

40

60

80λ

M

SIC, ΓB = 10 dB

SIC, ΓB = 20 dB

SIC, ΓB = 30 dB

orthogonal, ΓB = 10 dB

orthogonal ΓB = 20 dB

orthogonal, ΓB = 30 dB


summary and outlook

▪ simple model that captures the features of the 3 services

▪ non-orthogonal slicing can be beneficial, but not always

▪ reliability diversity plays a role in setting design guidelines

many extensions possible

▪ use the model to analyze the slicing for all thee services

▪ multiple URLLC devices

▪ multiple mMTC channels and hopping

▪ mMTC repetitions


additional references

▪ P. Popovski, J. J. Nielsen, C. Stefanovic, E. de Carvalho, E. Strom, K. F. Trillingsgaard, A.-S. Bana, D. M. Kim, R. Kotaba, J. Park, R. B. Sørensen, "Ultra-Reliable Low-Latency Communication (URLLC): Principles and Building Blocks", IEEE Network Magazine, Special issue on 5G for Ultra-Reliable Low Latency Communications, in revision, 2017.

▪ K. F. Trillingsgaard, and P. Popovski, “Generalized HARQ Protocols with Delayed Channel State Information and Average Latency Constraints”, accepted for publication in IEEE Transactions on Information Theory, 2017.

▪ A. Kalør, R. Guillaume, J. Nielsen, A. Mueller and P. Popovski, “Network Slicing in Industry 4.0 Applications: Abstraction Methods and End-to-End Analysis”, IEEE Transactions on Industrial Informatics (SS on From Industrial Wireless Sensor Networks to Industrial Internet-of-Things), 2017.

▪ G. Durisi, T. Koch and P. Popovski, "Toward Massive, Ultrareliable, and Low-Latency Wireless Communication With Short Packets," Proceedings of the IEEE, vol. 104, no. 9, pp. 1711-1726, Sept. 2016.

▪ P. Popovski, ”Ultra-Reliable Communication in 5G Wireless Systems”, 1st International Conference on 5G for Ubiquitous Connectivity, Levi, Finland, November 2014.

▪ P. Popovski, K. F. Trillingsgaard, O. Simeone, and G. Durisi, ”5G Wireless Network Slicing for eMBB, URLLC, and mMTC: A Communication-Theoretic View”, available on Arxiv, 2018.

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principles of ultra-reliable low latency communications (URLLC) · 2018-06-11 · principles of ultra-reliable low latency communications (URLLC) Petar Popovski Aalborg University