optimal numerology for 5g heterogeneous services · i mixed numerology speciﬁed by 3gpp i...

Optimal Numerology for 5G Heterogeneous Services

CD-Lab Open day (Module 1 - Nokia)

Ljiljana MarijanovicNovember 15, 2018

Dependable Wireless Connectivity for the Society in Motion

Content

Mixed numerology for 5G

Optimal numerology in single-user case

Optimal numerology in multi-user case

Summary and Future work

Content

Introduction1

I Mixed numerology specified by 3GPPI Numerology assumes the parametrization of the multicarrier modulation

Numerology in 3GPP

Subcarrier

spacing

Symbol

duration

Cyclic pre!x

duration

duration/size

Subrame

duration/size

Supported transmission numerology

n ∆f Symbol and CP duration Symbols per subframe0 15 kHz 66.67µs / 4.69µs 141 30 kHz 33.33µs / 2.38µs 282 60 kHz 16.67µs / 1.19µs 563 120 kHz 8.33µs / 0.60µs 112

13rd Generation Partnership Project (3GPP),“Technical Specification Group Radio Access Network; NR; Physical channels and modulation“,

December, 2017

Introduction1

Numerology in 3GPP

Subcarrier

spacing

Symbol

duration

Cyclic pre!x

duration

duration/size

Subrame

duration/size

December, 2017

Introduction1

Numerology in 3GPP

Subcarrier

spacing

Symbol

duration

Cyclic pre!x

duration

duration/size

Subrame

duration/size

December, 2017

Introduction1

Numerology in 3GPP

Subcarrier

spacing

Symbol

duration

Cyclic pre!x

duration

duration/size

Subrame

duration/size

December, 2017

Why mixed numerology?

I Flexible way to support diverse user requirements

I Service requirementsI URLLCI eMBBI mMTC

I Channel conditionsI Large subcarrier spacings at high velocityI Small subcarrier spacing with large channel delay spread

I Currently we are focused on the Channel conditions.

UE5 UE4

UE1Δf1 UE2 UE3Δf3

UE5 UE4

UE1Δf1 UE2 UE3Δf3

UE5 UE4

UE1Δf1 UE2 UE3Δf3

UE5 UE4

UE1Δf1 UE2 UE3Δf3

UE5 UE4

UE1Δf1 UE2 UE3Δf3

UE5 UE4

UE1Δf1 UE2 UE3Δf3

UE5 UE4

UE1Δf1 UE2 UE3Δf3

System modelI OFDM transmission of a single user

yk,n = hk,nxk,n + ωk,n

I We perform Least Square (LS) estimation for the transmitted data symbol

hkp,np =ykp,np

xkp,np

hk,n =∑

kp,np∈Pw{kp,np}

k,n hkp,np ,

yk,n - received OFDM symbol at freq-time data positionxk,n - transmitted OFDM symbol at freq-time data positionhk,n - frequency response at freq-time data positionωk,n - AWGN, ICI, ISI, IBI, channel estimation error

hkp,np - estimated channel at pilot position

w{kp,np}k,n - inter/extrapolation weights

System modelI OFDM transmission of a single user

yk,n = hk,nxk,n + ωk,n

I We perform Least Square (LS) estimation for the transmitted data symbol

hkp,np =ykp,np

xkp,np

hk,n =∑

kp,np∈Pw{kp,np}

k,n hkp,np ,

yk,n - received OFDM symbol at freq-time data positionxk,n - transmitted OFDM symbol at freq-time data positionhk,n - frequency response at freq-time data positionωk,n - AWGN, ICI, ISI, IBI, channel estimation error

hkp,np - estimated channel at pilot position

w{kp,np}k,n - inter/extrapolation weights

Content

Optimization formulation2

High delay spread &

high Doppler shift

Low delay spread &

low Doppler shift

Pilot resource

maximizeDf ,Dt ,∆f

B(Df ,Dt ) log2(1 + γ(∆f ))

subject to ∆f ∈ 2n15kHzn ∈ {−1,0,1,2,3}

γ =σ2

σ2n + (σ2

ICI(∆f ) + σ2e(∆f ))σ2

2Lj.Marijanovic, S.Schwarz, M.Rupp “Optimal Numerology in OFDM Systems Based on Imperfect Channel Knowledge”, VTCSpring 2018

High delay spread &

high Doppler shift

Low delay spread &

low Doppler shift

Pilot resourcemaximize

Df ,Dt ,∆fB(Df ,Dt ) log2(1 + γ(∆f ))

γ =σ2

σ2n + (σ2

ICI(∆f ) + σ2e(∆f ))σ2

High delay spread &

high Doppler shift

Low delay spread &

low Doppler shift

Pilot resourcemaximize

Df ,Dt ,∆fB(Df ,Dt ) log2(1 + γ(∆f ))

γ =σ2

σ2n + (σ2

ICI(∆f ) + σ2e(∆f ))σ2

ICI power for different numerology

0 36 72 118 154 180 216 252User velocity [km/h]

7.5kHz15kHz30kHz60kHz120kHz

Parameters used for simulations

Parameters Values

Bandwidth 1.44MHzCarrier frequency 2.5GHz

SNR 30dBModulation coding scheme Adaptive

Channel Model TDL-ADelay spread (Trms) 45ns, 370ns

Throughput performances

0 36 72 118 154 190 216

User velocity [km/h]

TDL-45ns

7.5kHz

120kHz

0 36 72 118 154 190 216

TDL-45ns

7.5kHz15kHz30kHz60kHz120kHzLTE

0 36 72 118 154 190 216

TDL-45ns

7.5kHz15kHz30kHz60kHz120kHzLTE

0 36 72 118 154 190 216

TDL-370ns

7.5kHz15kHz30kHz60kHz120kHz

Content

Interband interference 3

0 10 20 30 40 50 60 70 80Subcarrier index (k)

2 IBI (

30 kHz60 kHz120 kHz

σ2IBI(k) =

[N−1∑k ′=0

∣∣∣∣sinc(

(k ′ + 1)π

k2∆f

)∣∣∣∣2]

k, k′ - subcarrier indicesN - total number of subcarriers within certainsubbandq ≥ 1 - ratio between two subcarrier spacings

3Ljiljana Marijanovic, Stefan Schwarz, and Markus Rupp, “Intercarrier Interference of Multiple Access UFMC with Flexible Subcarrier Spacings.“,

Proceedings of the 25th European Signal Processing Conference (EUSIPCO), August, 2017.

2 IBI (

30 kHz60 kHz120 kHz

σ2IBI(k) =

[N−1∑k ′=0

∣∣∣∣sinc(

(k ′ + 1)π

k2∆f

)∣∣∣∣2]

2 IBI (

30 kHz60 kHz120 kHz

σ2IBI(k) =

[N−1∑k ′=0

∣∣∣∣sinc(

(k ′ + 1)π

k2∆f

)∣∣∣∣2]

Integer linear problem formulation - IP method 4

γ =σ2

σ2n + (σ2

ICI + σ2ISI + σ2

e)σ2d + σ2

IBImax

maximize z

subject to∑∆f

log2(1 + γ∆f ,u)∆N∆f ,u ≥ z, ∆f ∈ S, u ∈ U, z ∈ R

N l∆f ,u ≤ Nh

∆f ,u , ∀u ∈ U, {N l∆f ,u ,Nh

∆f ,u} ∈ N0∑∆f

a∆f ,u = 1,

a∆f ,u ≤ ∆N∆f ,u ≤ Ntotal a∆f ,u , a∆f ,u ∈ {0, 1}

N l∆f ′,u′ − Nh

∆f ,u ≥ G(∆f ,∆f ′)a∆f ,u , ∆f ′ > ∆f , u′ 6= u

N l∆f ,u+1 − Nh

∆f ,u = 0,

∆N∆f ,u = 2(s−1)cs, s ∈ {1, 2, 3, 4}, cs ∈ N0,

4Ljiljana Marijanovic, Stefan Schwarz, and Markus Rupp, “A Novel Optimization Method for Resource Allocation based on Mixed Numerology.“,

International Conference on Communications (ICC) 2019 (submitted)

Integer linear problem formulation - IP method 4

γ =σ2

σ2n + (σ2

ICI + σ2ISI + σ2

e)σ2d + σ2

IBImax

G(15 kHz, 30 kHz) G(30 kHz, 60 kHz) G(60 kHz, 120 kHz)

s = 1 s = 2 s =3 s =4

NlΔf,2 Nh

maximize z

subject to∑∆f

log2(1 + γ∆f ,u)∆N∆f ,u ≥ z, ∆f ∈ S, u ∈ U, z ∈ R

N l∆f ,u ≤ Nh

∆f ,u , ∀u ∈ U, {N l∆f ,u ,Nh

∆f ,u} ∈ N0∑∆f

a∆f ,u = 1,

a∆f ,u ≤ ∆N∆f ,u ≤ Ntotal a∆f ,u , a∆f ,u ∈ {0, 1}

N l∆f ′,u′ − Nh

∆f ,u ≥ G(∆f ,∆f ′)a∆f ,u , ∆f ′ > ∆f , u′ 6= u

N l∆f ,u+1 − Nh

∆f ,u = 0,

∆N∆f ,u = 2(s−1)cs, s ∈ {1, 2, 3, 4}, cs ∈ N0,

4Ljiljana Marijanovic, Stefan Schwarz, and Markus Rupp, “A Novel Optimization Method for Resource Allocation based on Mixed Numerology.“,

International Conference on Communications (ICC) 2019 (submitted)

The other problem formulation approaches

I Linear programming solution - LP method

I Low computational complexity even with large bandwidth and high number of usersI Suboptimal solution

I Heuristic approaches

∆f ≈

I Optimal heuristic

I Optimally divide the bandwidth based on IP method.

I Pure heuristic

I Divides the total bandwidth onto the allocated subbands according to the number of users thatare assigned to the subbands.

∆f ≈

I Optimal heuristic

I Pure heuristic

∆f ≈

I Optimal heuristic

I Pure heuristic

∆f ≈

I Optimal heuristic

I Pure heuristic

∆f ≈

I Optimal heuristic

I Pure heuristic

∆f ≈

I Optimal heuristic

I Pure heuristic

∆f ≈

I Optimal heuristic

I Pure heuristic

∆f ≈

I Optimal heuristic

I Pure heuristic

Parameters used for numerical results

parameter valuesubcarrier spacing 15 kHz 30 kHz 60 kHz 120 kHznumber of symbols per subframe 14 28 56 128CP duration 4.76µs 2.38µs 1.18µs 0.59µsbandwidth 5 MHzcarrier frequency 5.9 GHzchannel model TDL-Apilot pattern diamondnumber of user 7

Numerical results

v = 100 km/h

IPLPoptimal heuristicpure heuristicLTE

D1 - {100,200}nsD2 - {30,50,100,200}nsD3 - {30,50,100,200,300,400,500}ns

V1 - {100,200}km/hV2 - {5,50,100,200}km/hV3 - {5,50,100,200,300,400}km/h

Numerical results

v = 100 km/h

D1 - {100,200}nsD2 - {30,50,100,200}nsD3 - {30,50,100,200,300,400,500}ns

V1 - {100,200}km/hV2 - {5,50,100,200}km/hV3 - {5,50,100,200,300,400}km/h

Numerical results

v = 100 km/h

D1 - {100,200}nsD2 - {30,50,100,200}nsD3 - {30,50,100,200,300,400,500}ns

= 200 ns

v [km/h]

V1 - {100,200}km/hV2 - {5,50,100,200}km/hV3 - {5,50,100,200,300,400}km/h

Numerical results

v = 100 km/h

D1 - {100,200}nsD2 - {30,50,100,200}nsD3 - {30,50,100,200,300,400,500}ns

= 200 ns

v [km/h]

V1 - {100,200}km/hV2 - {5,50,100,200}km/hV3 - {5,50,100,200,300,400}km/h

Content

Summary

I Large subcarrier spacings are more robust to ICI, but suffer of ISI and large interpolation error with largerms delay spread channels.

I Interband interference occurs due to the different numerology in multi-user scenario.I The LP method provides a highly favorable tradeoff between computational complexity and performance.I We gain with the mixed numerology compared to an LTE.

Summary

Future work

I Optimal numerology based on QoS requirements - latency, reliability

I Employ the OFDM-based modulation schemes

-20 -10 0 10 20

Frequency

PSD[dB]

I PhD defense - first half of 2020

Future work

-20 -10 0 10 20

Frequency

PSD[dB]

Future work

-20 -10 0 10 20

Frequency

PSD[dB]

Future work

-20 -10 0 10 20

Frequency

PSD[dB]

Thank you for your attention!{[email protected]}

Optimal Numerology for 5G Heterogeneous Services

CD-Lab Open day (Module 1 - Nokia)

Ljiljana MarijanovicNovember 15, 2018

optimal numerology for 5g heterogeneous services · i mixed numerology speciﬁed by 3gpp i...

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