the challenges of future iot waveforms

The challenges of future IoT

waveforms

CMT 2019

Michel Terré

Conservatoire National des Arts et Métiers

Paris, France

CNAM/CEDRIC/Laetitia

5G markets

eMBB

(Enhanced Mobile BroadBand)

URLLC

(Ultra Reliable Low Latency

Communications)

mMTC

(massive Machine Type

Communications)

Throughput > 10 Gbits/s

Battery Life > 10 years Latency < 1 ms

3GPP

release 13 (2016)

release 14 (2017)

release 15 (2018)

release 16 (2019)

release 17 (2020)

So many objectives

• Very High Throughput

• High Reliability and Low Latency

• Low Power Consumption

• Opportunistic Transmissions

• Unsynchronized Transmissions

• Idle Mode and Fast Wake Up

• Millimeter Waves

• Reconfigurable Antennas

• Indoor Localization

• Massive MIMO

• New Coding Scheme for short packets

• Non Orthogonal Multiple Access (NOMA)

• Pilot Free Synchronization

• Blind Channel Estimation

• …

5G waveform

• So many proposals !– CP-OFDM

– SC-OFDM

– f-OFDM

– BF-OFDM

– FMT

– WOLA

– UFMC

– GFDM

– FBMC-OQAM

– FFT-FBMC

- NB-IoT

- LTE-M

- LoRa

- SigFox

Overview

• A short review of mobile radio waveforms

• Short focus on WOLA, FBMC-OQAM and LoRa

• Some power amplification challenges

• Blind estimation

2G waveform

• GMSK (CPFSK ½ )

☺

– Constant Envelope

– Low side lobes

– Low cost technology

�

– Low spectral efficiency

(1bit/s/Hz)

P. Chevalier, F. Pipon, "New insights into optimal widely linear array receivers for the demodulation

of BPSK, MSK and GMSK signals corrupted by non circular interferences - Application to SAIC", IEEE

Trans. Signal Processing, Vol 54, N°3, pp. 870-883, March 2006.

900 900.5 901 901.5 902-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

PS

D (

dB)

frequency (MHz)

3G waveform

• Filtered M-QAM (and CDMA)

☺

– Spectral efficiency (thanks to M-QAM)

– Good spectral location (thanks to roll-off)

�

– Interferences (CDMA)

– (Non constant Envelope, Down Link)

2 2.002 2.004 2.006 2.008 2.01 2.012 2.014 2.016 2.018-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

frequency (GHz)

PS

D (

dB)

2.4 2.402 2.404 2.406 2.408 2.41 2.412 2.414 2.416 2.418-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

frequency (GHz)

PS

D (

dB)

4G waveform

• CPOFDM, M-QAM

☺

– Spectral efficiency of M-QAM modulations

– Easy to implement (FFT and Cyclic Prefix)

�

– Side lobes, OOB emissions

– Non constant Envelope, PAPR

Side lobes

WOLA (Weighted OverLap and Add)

2.39 2.392 2.394 2.396 2.398 2.4 2.402 2.404 2.406 2.408 2.41

x 109

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

frequency (GHz)

PS

D (

dB)

WOLA


• WOLA OFDM, M-QAM

☺

– Reduced Side Lobes

– Spectral efficiency of

M-QAM modulations

– Easy to implement(FFT, Cyclic Prefix, Multiplication)

– Can be demodulated

by a CP-OFDM receiver

�

– Non constant Envelope,

PAPR

Reduced

Side lobes


Received with a CP-OFDM receiver

FBMC-OQAM (Filter Bank MultiCarrier)

Transmitter

M. Bellanger et al. "FBMC physical layer : a primer", http://www.ict-

phydyas.org/teamspace/internal-folder/FBMC-Primer_06-2010.pdf

FMBC - Polyphase Approach -

Transmitter

FBMC – Polyphase Approach -

Receiver

FBMC-OQAM, Phydyas Filter

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2-0.02

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

time

ampl

itude

Shape filter (Impulse response)

FBMC

OFDM

-4 -3 -2 -1 0 1 2 3 4

-60

-50

-40

-30

-20

-10

0

frequencypo

wer

(dB

)

Shape filter (Frequency response)

FBMC

OFDM

http://www.ict-phydyas.org/

�� = 0.971960� =

22

�� = 0,235147ℎ� = 1 − 2��

��2� + 2��

�� − 2��

3��2�

FBMC-OQAM (Filter Band MultiCarrier)

FBMC-OQAM (Receiver)

FBMC-OQAM

☺

– Reduced Side Lobes

– Spectral efficiency of M-QAM modulations

– No Cyclic Prefix

�

– Complexity

– Loss of complex orthogonality

– Not well suited for MIMO

– Non constant Envelope, PAPR 2.4 2.402 2.404 2.406 2.408 2.41 2.412 2.414 2.416 2.418-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

Frequency (GHz)

PS

D (

dB)

FBMC OQAM

FBMC–OQAM Interferences

s.c./t -T -T/2 0 T/2 T

k-1 Imaginary Real Imaginary Real Imaginary

k Real Imaginary Real Imaginary Real

k+1 Imaginary Real Imaginary Real Imaginary

Interference Table,limited to adjacent sub-carriers

OQAM transmission table (equivalent to 2 interleaved PAM)

Received 16-OQAM Constellation

-8 -6 -4 -2 0 2 4 6 8-8

-6

-4

-2

0

2

4

6

8

real

imag

inar

y

Received 16-OQAM Constellation(with channel and noise)

-1.5 -1 -0.5 0 0.5 1 1.5-1.5

-1

-0.5

0

0.5

1

1.5

real

imag

inar

y

rotation to process to alignreceived samples on thesquare grid

MIMO Problem

H1s1=1

Channel 1, H1=1 interferences

H2s2=j

Channel 2, H2=j interferences

Ultra simple case

1+ja j+b

1+j + b+ja Interferences (high level)

Input signal

23

High Power Amplifier (HPA) and PAPR(Peak to Average Power Ratio)

� � = � � �� !

Modified Rapp Model

" �(�) = %�(�)

1 + %�(�)&'(!

) �)

* � = " � � ��+ !HPA Output signal

0 0.2 0.4 0.6 0.8 10

1

2

3

4

5

6

7

8

rho(t)

F(r

ho(t

))

G=10, Asat=7, p=3

OutputSaturation

Out Of Band (OOB) Transmissions

f

20 MHz

7,54 MHz 7,54 MHz

0,7 MHz

2,1 MHz 2,1 MHz

H. Shaiek, R. Zayani, Y. Medjahdi, D. Roviras. "Analytical analysis of SER for beyond 5G post-OFDM

Waveforms in presence of High Power Amplifiers", IEEE Access, pp. 1-13, 2019,

(doi:10.1109/ACCESS.2019.2900977)

OOB CP-OFDM and HPA

2.39 2.392 2.394 2.396 2.398 2.4 2.402 2.404 2.406 2.408 2.41

x 109

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

Frequency (Hz)

PS

D (

dB)

OFDM

Rapp Model

Ideal Linear HPA

OOB WOLA and HPA

2.39 2.392 2.394 2.396 2.398 2.4 2.402 2.404 2.406 2.408 2.41

x 109

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

Frequency (GHz)

PS

D (

dB)

WOLA

Rapp Model

Ideal Linear HPA

OOB FBMC-OQAM and HPA

2.39 2.392 2.394 2.396 2.398 2.4 2.402 2.404 2.406 2.408 2.41

x 109

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

Frequency (GHz)

PS

D (

dB)

FBMC OQAM

Rapp Model

Ideal Linear HPA

HPA with a dynamic saturation level ?

" �(�) = %�(�)

1 + %�(�)&(�)'(!

) �)

&'(! � = ,( � � − - ,… , � � , … , �(� + -) )

OOB FBMC-OQAM and dynamic

saturation level

2.39 2.392 2.394 2.396 2.398 2.4 2.402 2.404 2.406 2.408 2.41

x 109

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

Frequency (GHz)

PS

D (

dB)

Dynamic Asat

Rapp Model

Ideal Linear HPA

Dynamic saturation level evolution

2600 2800 3000 3200 3400 3600 3800 4000

0.135

0.14

0.145

0.15

0.155

0.16

0.165

time (microsec)

Dynamic AsatMean Dynamic AsatStatic Asat

0 0.5 1 1.5 2 2.5 3

x 104

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

time (microsec)

Dynamic AsatMean Dynamic AsatStatic Asat

Lora Chirp Spread Spectrum

0 0.005 0.01 0.015 0.029.7

9.75

9.8

9.85

9.9

9.95

10x 10

6

freq

uenc

y (H

z)

time (s)


2.39 2.392 2.394 2.396 2.398 2.4 2.402 2.404 2.406 2.408 2.41

x 109

-70

-60

-50

-40

-30

-20

-10

0LoRa

frequency (Hz)

PS

D (

dB)


2.39 2.392 2.394 2.396 2.398 2.4 2.402 2.404 2.406 2.408 2.41

x 109

-70

-60

-50

-40

-30

-20

-10

0LoRa

frequency (Hz)

PS

D (

dB)

2.39 2.392 2.394 2.396 2.398 2.4 2.402 2.404 2.406 2.408 2.41

x 109

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

Frequency (GHz)

PS

D (

dB)

Dynamic Asat

Rapp Model

Ideal Linear HPA

Blind Interferences cancellation

User 1

User 2

Receiver

H

G

1/01(234)5 → �5 + %5

7

1(234)

1/01(234)8 → �8 + 70�5%5 + %8

7

9 = �5, : = %5 ; 9 + : = <9 + 709: + : = =

Stanley Smith et al., "A moment-based estimation strategy for underdetermined single-

sensor blind source separation," IEEE Signal Processing Letters, pp 1-5, April 2019.

Conclusion

• Universal waveform for all 5G services ?

• Interference Mitigation for Massive IoT

Deployments

https://www.hindawi.com/journals/wcmc/si/375608/cfp/

Dead Line : December 1st

Thank you for your attention

[Source: ITU-R M.2083-0 IMT Vision]

the challenges of future iot waveforms

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