5G Applications trends and technology needs
Sven MattissonEricsson Research, Lund
5G Applications trends and technology needs | NORCAS 2017 | Page 2
Envisioned 5G plans
Source: Ericsson Mobility Report
5G Applications trends and technology needs | NORCAS 2017 | Page 3
Estimated 5G traffic
Source: Ericsson Mobility Report
5G Applications trends and technology needs | NORCAS 2017 | Page 4
5G when?
Source: Ericsson Mobility Report
5G Applications trends and technology needs | NORCAS 2017 | Page 5
5G research challenges
A set of integrated radio-access technologies jointly enabling the long-term networked society
Ultra-reliable communication
Inter-vehicular / vehicular-to-roadcommunication
Massive machine-typecommunication
Ultra-dense deploymentsDevice-to-device
communication and cooperative devices
Multi-hopcommunication
5G Applications trends and technology needs | NORCAS 2017 | Page 6
What is MTC?
Three different 3GPP machine-type communication initiatives:› EC-GSM-IoT (Extended Coverage - GSM - Internet of Things)› LTE-M (LTE M2M)› NB-IoT (Narrow Band Internet of Things, LTE add-on)
5G Applications trends and technology needs | NORCAS 2017 | Page 7
5G IoT traffic
Massive IoT traffic scenario
A dense urban environment with 10,000 households per km2 – similar to the central area of London, Beijing or New York – was used as the base for a massive IoT services scenario. A selection of connected device types were assumed to be deployed in the area, including water, gas and electricity meters, vending machines, rental bike position monitors and accelerometers in cars1 monitoring driver behavior. Traffic characteristics for each device are summarized in the diagram above.2 The number of connected devices used in this scenario represents a mature, large scale massive IoT scenario. During an initial rollout phase device densities will be lower and the corresponding traffic load will not be as high.
The services represent a realistic range of massive IoT use cases that are expected to be deployed in an urban environment.3
Deployment environment and traffic models differ for these services: a remote-controlled meter may face an indoor coverage challenge, while a device mounted on a bike is usually found outside. The traffic intensity from meters may be once per day, whereas other devices may need to transmit every 10 minutes.
The data traffic for massive IoT devices is small; the typical data packet for a service is about 100-150 bytes, accounting for a payload of the device ID, time stamp and report data values.
Additionally, each packet has IP overhead and higher layer headers of around 65 bytes; the Media Access Control (MAC) layer overhead is 15 bytes, and standard control signaling within the mobile network is 59 bytes per event for uplink. In total, each event generates around 250-300 bytes to be transmitted by the IoT device.
The figure on the following page shows the resulting traffic demand. It clearly demonstrates that, despite the very high device density, the small traffic per device limits the traffic per area unit to a few kilobits per second (kbps) per km2. As a comparison, mobile broadband traffic is approaching gigabit per second (Gbps) per km2 in dense urban areas.
1 Calculation based on an average of one car per household and every fourth in traffic 2 In this scenario, the traffic is uplink dominated, as downlink traffic for application acknowledgement (ACK)
and control plane signaling (RRC) between the device and the radio access network is comparably small 3 Orange, Ericsson, “Traffic Model for legacy GPRS MTC” (February 15-19, 2016), document GP 160060, 3GPP GERAN meeting #69
Traffic characteristics of deployed massive IoT connected devices in a city scenario
WATER METERS
100 bytes
12 hours
10,000/km2
Typical message size
Message interval
Device density
ELECTRICITY METERS
100 bytes
24 hours
10,000/km2
GAS METERS
100 bytes
30 minutes
10,000/km2
VENDING MACHINES
150 bytes
24 hours
150/km2
BIKE FLEET MANAGEMENT
150 bytes
30 minutes
200/km2
PAY-AS- YOU-DRIVE
150 bytes
10 minutes
2,250/km2
NOVEMBER 2016 ERICSSON MOBILITY REPORT IoT IN FOCUS 31
Estimated traffic from massive IoT devices in a city scenario with 10,000 households per km2.
Per device type:> 100–150 B/msg> 1–150 msgs/day> 0.05–1 #/household
Source: Ericsson Mobility Report – November 2016
5G Applications trends and technology needs | NORCAS 2017 | Page 8
NB-IoT Deployment scenarios1. Stand-alone
NB-Io
T
GSM
NB-Io
T
NB-Io
T
GSM
GSM
NB-Io
Tf
[MHz]
GSMisreplacedbyaNB-IoTcarrier.
Future:SeveralNB-IoTresourceblocksaregroupedtogether.
› Two GSM carriers can be replaced by one NB-IoT carrier.
› The NB-IoT system can use more than 1 resource block.
– In the stand-alone case, they are grouped together.
f[MHz]
1PRB=180kHz
5G Applications trends and technology needs | NORCAS 2017 | Page 9
…NB-IoT Deployment scenarios
LTE
NB-Io
TLTE
NB-Io
T
f[MHz]
LTEcarrierbandwidth
f[MHz]
LTEcarrierbandwidth
OneormoreNB-IoTcarriers(dependingonLTEbandwidth)canbedeployedintheguardbandoftheLTEcarrier.
OneormoreNB-IoTcarriersisreplacingresourceblocksintheLTEcarrier.
Guardband
2. LTE guard band
3. In-band LTE
NB-Io
T
NB-Io
T
f[MHz]
LTEcarrierbandwidthLTE
Power
boost
5G Applications trends and technology needs | NORCAS 2017 | Page 10
5G mm-wave signal properties
› CP-OFDM with windowing/filtering› PAPR on the order of 10dB
CP-OFDM
BWsig: > 0.9 BWch
guard band 10% →1%BWch: 50 – 200 (400) MHz
sub-carrier spacing{60, 120, (240) } kHz
• • •• • •
5G Applications trends and technology needs | NORCAS 2017 | Page 11
AAS — array/advance/adaptive antenna systems/steering
beam generationLet one single data stream (i.e. beam) connect to M antenna elements, then we can bombineeither in the analog or digital domain (both RX and TX). Similarly we can tap of several copiesof the antenna signal to N di↵erent cominers to get multiple beams.
w1
wM
w1
wM
w1,1
wM,1
w1,N
wM,Nanalog BF digital BF
M antennas, one beam M antennas, N beams
Valid both for RX and TX.c�Ericsson AB 2015 Ericsson Confidential 12𝑃"# = 𝑃%#𝐺%#𝐺"#
𝜆4𝜋𝑑
+
Friis’ transmission equation→ use many antennas at mm-wave
10x10 cm, 15GHz
5G Applications trends and technology needs | NORCAS 2017 | Page 12
Above 6 GHz emissionmask
-13 dBm/MHz
-5 dBm/MHz
BW
BW10
12 ·NRB · fSCS
c�Ericsson AB 2015 Ericsson Confidential 5
Regulatory requirements
› 4G has 90/10% carrier/guard allocation› 5G will use a variable allocation
– up to 98.3/1.7% below 6GHz – up to 95/5% above 6GHz– filter complexity and power consumption– group delay incurred latency– interference in mixed NR and LTE cells
Spectrum confinement
95%
5%
90%
10%
Above 6GHz TX mask
5G Applications trends and technology needs | NORCAS 2017 | Page 13
1.96e+09 1.98e+09 2e+09 2.02e+09 2.04e+09
-100
-50
0
Frequency (Hz)
Spec
tral d
ensi
ty (d
Bm/M
Hz)
IP3 30dBmgain+NF 40dB
20MHz AWGN signal with IM3 (in-band IM3 dotted)
P=20 dBmUE E-UTRA mask
kTB
…regulatory requirements
Sample 20MHz PA spectrum, with noise and IM3, @ 2GHz
kTB
Duplex distanceRX band
› Emission in own FDD RX band has to be below the RX noise floor› TDD isolates TX from RX in time, e.g. for NB-IoT and 5G mm-wave bands
5G Applications trends and technology needs | NORCAS 2017 | Page 14
Selectivity testingAdjacent channel selectivityConducted
Selectivity test
+ RX demodPsig BER/FER
Psig = Pref sens + 6dBPint
c�Ericsson AB 2015 Ericsson Confidential 2
OTA Selectivity test
RXPRX
PnoisePint
c�Ericsson AB 2015 Ericsson Confidential 3
Current 3GPP approach
Selectivity = 𝑃,-. − 𝑃0,1
At ref. sens BER/FER
Time consuming when BER/FER threshold is low as well as when there are many RX paths (AAS)
Tentative approach for array antenna systems (AAS)
Simpler, no need for conducted sensitivity, accurate and agnostic but need to be completed with limited over-the-air tests based on minimum radiated sensitivity with a WANTED signal.
Selectivity ~𝑃"# − 𝑃-9,0:
with 𝑃"#, 𝑃-9,0: antenna referred
5G Applications trends and technology needs | NORCAS 2017 | Page 15
Of particular interest in 3GPP for mm-wave applications
› Receiver noise figure– Insertion losses in RF filter, switches and substrate– Low-noise amplifier (LNA) input-referred noise– Dynamic range
› Adjacent-channel selectivity (ACS)› Blocking
› Power amplifiers– Linearity
› Error-vector magnitude (EVM)› Adjacent-channel leakage ratio (ACLR)
– Efficiency at back-off› Peak-to-average power ratio (PAPR)
5G Applications trends and technology needs | NORCAS 2017 | Page 16
Cut-off frequency and scalingPA technology comparisonCut-off frequency and scalingFundamental trade-off
between voltage and frequency
scaling
Scaling sets speed and integration potential
> Si is superior for integration (so far)
> GI (fT ) = 1, GP(fmax) = 1
gd
s
rg
cgs
cgd
gm
go
fT =gm
2⇡(cgs + cgd), fmax =
fTp4 rg (2⇡fT cgd + go)
c�Ericsson AB 2016 36 (48)Source: del Alamo
5G Applications trends and technology needs | NORCAS 2017 | Page 17
Receiver noise figureA simplified receiver model can be derived by lumping the front-end (FE), analog/RF receiver (RX) and ADC into three cascaded blocks.
Receiver noise figureA simplified receiver model can be derived by lumping the front-end (FE),analog/RF receiver (RX) and ADC into three cascaded blocks.
| {z }IL
filter, SW, routing
| {z }DR,CPVFS
| {z }F ,BW ,G
LNA, mixer, analog base band
ADCRXFE
Psig ,N0 SNR
F =Nout
Nin ·G=
Nout · SinNin · Sout
=SNRin
SNRout
NF = 10 · log10(F )
c�Ericsson AB 2016 2 (25)
Receiver noise figureA simplified receiver model can be derived by lumping the front-end (FE),analog/RF receiver (RX) and ADC into three cascaded blocks.
| {z }IL
filter, SW, routing
| {z }DR,CPVFS
| {z }F ,BW ,G
LNA, mixer, analog base band
ADCRXFE
Psig ,N0 SNR
F =Nout
Nin ·G=
Nout · SinNin · Sout
=SNRin
SNRout
NF = 10 · log10(F )
c�Ericsson AB 2016 2 (25)
5G Applications trends and technology needs | NORCAS 2017 | Page 18
Cascade noise factorFriis' formula can be used to find the noise factor at the antenna connector as (linear units unless noted)
Cascade noise factorFriis’ formula [21] can be used to find the noise factor at the antennaconnector as (linear units unless noted)
F = IL ·✓FLNA +
FADC � 1
G
◆.
For example, assuming
NF = 5dB
IL = 0.7 dB
FLNA = 0.8 dB
9>=
>;) FADC � 1
G= 1.5 (1.76 dB)
This factor 1.5 can be used to represent the net allowable SNRdegradation due to the ADC noise floor, base-band processing losses,variability margins etc.
c�Ericsson AB 2016 3 (25)
Cascade noise factorFriis’ formula [21] can be used to find the noise factor at the antennaconnector as (linear units unless noted)
F = IL ·✓FLNA +
FADC � 1
G
◆.
For example, assuming
NF = 5dB
IL = 0.7 dB
FLNA = 0.8 dB
9>=
>;) FADC � 1
G= 1.5 (1.76 dB)
This factor 1.5 can be used to represent the net allowable SNRdegradation due to the ADC noise floor, base-band processing losses,variability margins etc.
c�Ericsson AB 2016 3 (25)
For example, assuming
This factor 1.5 can be used to represent the net allowable SNR degradation due to the ADC noise floor, base-band processing losses, variability margins etc.
5G Applications trends and technology needs | NORCAS 2017 | Page 19
Wideband LNA noise-figure trends
LNA Noise figuretrends
0 20 40 60 80 1000
1
2
3
4
5
6
7
Carrier frequency (GHz)
NF (d
B)
28nm45nm SOI65nm90nm130nm SOI130nm SiGe250nm GaN150nm GaNtrend
LNA noise figure vs. frequency
By inserting(F0 = 1.12 (0.5 dB)
ft = 168 (GHz)
into the Fmin(fc) equation weget the depicted trend curvethat matches the bestreported noise figures.
c�Ericsson AB 2016 6 (25)
By inserting
into the Fmin(fc) equation we get the depicted trend curve that matches the best reported noise figures.
LNA Noise figuretrends
0 20 40 60 80 1000
1
2
3
4
5
6
7
Carrier frequency (GHz)
NF
(dB)
28nm45nm SOI65nm90nm130nm SOI130nm SiGe250nm GaN150nm GaNtrend
LNA noise figure vs. frequency
By inserting(F0 = 1.12 (0.5 dB)
ft = 168 (GHz)
into the Fmin(fc) equation weget the depicted trend curvethat matches the bestreported noise figures.
c�Ericsson AB 2016 6 (25)
[Tuned LNAs can do better at the cost of bandwidth]
5G Applications trends and technology needs | NORCAS 2017 | Page 20
Total noise figure
› The receiver noise figure increases with the carrier frequency› Total noise figures of 10, 12, and 14dB assumed for 30, 45, and
70GHz, respectively (5dB at 2GHz)
Receiver noise figureA simplified receiver model can be derived by lumping the front-end (FE),analog/RF receiver (RX) and ADC into three cascaded blocks.
| {z }IL
filter, SW, routing
| {z }DR,CPVFS
| {z }F ,BW ,G
LNA, mixer, analog base band
ADCRXFE
Psig ,N0 SNR
F =Nout
Nin ·G=
Nout · SinNin · Sout
=SNRin
SNRout
NF = 10 · log10(F )
c�Ericsson AB 2016 2 (25)
1.3dB 0.9dB 1.7dB 2.7dB 0.3dB 30HGz
add 3dB variability and implementation margin
5G Applications trends and technology needs | NORCAS 2017 | Page 21
PA material propertiesSi GaAs SiC InP GaN Diamon
dμn 1400 10000 800 5400 2000 1900 cm2/Vs
Eg 1.1 1.4 3.26 1.34 3.4 5.45 eV
Ebr 0.3 0.4 3.5 0.5 3.3 5.6 MV/cm
vsat 1.0 1.5 2.0 0.67 2.5 2.7 107 cm/s
JFOM 0.48 0.95 11 0.53 13 24 1012 V/s
Rel. JFOM
1.0 2.0 23 1.1 28 50
Johnson’s figure of merit (JFOM) is defined as <=>?@AB+C
[data1 from Mishra and Rais-Zadeh]
Silicon technology has by far the best integration, cost and scaling properties but suffers from low break-down voltage (Ebr ). If it can be done in (CMOS) Si it will. . . 1 Data is somewhat contradictory
5G Applications trends and technology needs | NORCAS 2017 | Page 22
PA capabilities - Psat
P sat
[dBm
]
0
5
10
15
20
25
30
35
40
45
10 100
CMOSBulk
CMOSSOI
GaNHEMT
Frequency [GHz]
-20dB/dec
Source: Johnson, 3GPP R4-1610279
5G Applications trends and technology needs | NORCAS 2017 | Page 23
ACLR
For AWGN-like amplitude-modulated signals (like LTE) we have
𝐴𝐶𝐿𝑅 = HAIJKLMANO
= 3 KHMHAIJ
+,
assuming a cubic nonlinearity 𝑓 𝑥 = 𝑎T𝑥 +𝑎V𝑥V, with 𝐼𝑃V =XVYZYM
� .Source: Pedro
1.98e+09 2e+09 2.02e+09 2.04e+09-200
-180
-160
-140
-120
-100
-80
-60
Frequency (Hz)S
pect
ral d
ensi
ty (d
Bm
/Hz)
AWGN signal with IM3 due to cubic nonlinearity (in-band IM3 dash-dotted)
IP3 30dBm
P=20 dBm
10 dBm
0 dBm
𝑃Y?1
𝐼𝑀VY]^
5G Applications trends and technology needs | NORCAS 2017 | Page 24
Throughput loss vs ACIR
› Adjacent channel interference ratio
𝐴𝐶𝐼𝑅 =1
1𝐴𝐶𝐿𝑅 +
1𝐴𝐶𝑆
› Adjacent services outside own band may aggravate ACLR, though
ACIR [dB]
Thro
ughp
ut lo
ss [%
]
Source: 3GPP R4-1610477
𝐴𝐶𝑆𝐴𝐶𝐿𝑅
𝑓a 𝑓Y]^
5G Applications trends and technology needs | NORCAS 2017 | Page 25
ACLR vs output power
Source: 3GPP R4-168391, R4-1610279
ACLR 30 dB 40 dB
CMOS 16dBm 9dBm
GaN 28dBm 22dBm
5G Applications trends and technology needs | NORCAS 2017 | Page 26
𝑃𝐴𝐸 =𝑃9c. − 𝑃,-
𝑃de
Typical bias point(before DPD)
PAE vs ACLR
ACLR: 30 dB 40 dBCMOS 8% 2%GaN 11% 4%
Source: 3GPP R4-168391, R4-1610279
5G Applications trends and technology needs | NORCAS 2017 | Page 27
Field tests of 5G technology
› Green flag waves on 5G in Indianapolis, May 2017.– https://www.youtube.com/watch?v=Dw2GT95Vyxc&index=1&list=PLsn61Zheh8ije3EjK_NcyGUAF2PJe34_a
› New world record speed with 5G, February 2017.– https://www.youtube.com/watch?v=UOCM_91n90U&index=2&list=PLsn61Zheh8ije3EjK_NcyGUAF2PJe34_a
5G Applications trends and technology needs | NORCAS 2017 | Page 28
Discussion› 5G will augment existing wireless systems with a range of new applications, including, e.g., AAS
for high capacity mm-wave cells and low-power MTC.› Standardization is ongoing but legacy requirements will probably be extended up to 6GHz. Band
allocation above 6GHz will be addressed by WRC-19.› AAS will require OTA testing and new methods will need to be developed to account for spatial
filtering of the transmitted signals as well as received signals.› The need for high integrated mm-wave systems with many transceivers and antennas will require
careful and often complex consideration regarding the power efficiency and heat dissipation in small area/volume affecting the achievable performance as well as over-the-air testing.
› Transceivers for mm-wave frequencies will have increased power consumption due to higher BW, and, considering the thermal challenges given the significantly reduced area/volume for mm-wave products,
– the complex interrelation between receiver linearity, NF, bandwidth and dynamic range in the light of power dissipation should be considered,
– as well as transmitter achievable power versus efficiency as well as linearity.
5G Applications trends and technology needs | NORCAS 2017 | Page 29
Acknowledgement
Numerous colleagues have contributed to the activities reported here. In particular I would like to thank:
› Farshid Ghasemzadeh,› Stefan Parkvall, › Kenneth Sandberg, and,› Lars Sundström
for letting me use their material.
5G Applications trends and technology needs | NORCAS 2017 | Page 30
References
1. Ericsson Mobility Report. URL: http://www.ericsson.com/mobility-report/.
2. E. Johnson, "Physical limitations on frequency and power parameters of transistors," 1958 IRE International Convention Record, New York, NY, USA, 1965, pp. 27-34.
3. 3GPP R4-164226, On mm-wave technologies for NR.4. 3GPP R4-166526, Discussion on BS and UE noise figure for mm-waves.5. 3GPP R4-168391, On mm-wave ACLR.6. 3GPP R4-1610279, On mm-wave ACLR for 45 and 70 GHz.7. 3GPP R4-1610477, Simulations results for coexistence studies in 30GHz.8. U. K. Mishra et al.“GaN-Based RF Power Devices and Amplifiers 04414367.pdf”. In: 96.2 (2008), pp. 287–305. ISSN: 0018-
9219. DOI: 10.1109/JPROC.2007.911060. 9. M. Rais-Zadeh et al. “Gallium nitride as an electromechanical material”. In: Journal of Microelectromechanical Systems 23.6
(2014), pp. 1252–1271. ISSN: 10577157. DOI: 10.1109/JMEMS.2014.2352617. 10. J. A. del Alamo. Si CMOS for RF Power Applications. Last visited 2016-03-17. 2005.
URL: http://www-mtl.mit.edu/~alamo/pdf/2005/RC-108.pdf. 11. J. C. Pedro and N. Borges de Carvalho. “On the Use of Multitone techniques for Assessing RF Components’ Intermodulation
Distortion”, IEEE Transactions on Microwave Theory and Techniques (Dec. 1999), pp. 2393–2402.
5G Applications trends and technology needs | NORCAS 2017 | Page 31