real-time emulation methodologies for centralized radio ... · conclusions references real-time...

IntroductionObjectives

Centralized Radio Access NetworkReal-time emulationsPerformance Results

ConclusionsReferences

Real-time Emulation Methodologies forCentralized Radio Access Networks

USE OF OPENAIRINTERFACE IN RESEARCH ANDPROTOTYPING

Luis Felipe Ariza VesgaUniversidad Nacional de Colombia

Raymond KnoppEURECOM

Nokia Bell Labs, Murray Hill, New Jersey - June 26, 20191 / 21




Agenda1 Introduction2 Objectives3 Centralized Radio Access Network

Architecture4 Real-time emulations

Frequency domain extension5 Performance Results

Performance MetricsA proof-of-conceptVideo Demo

6 Conclusions7 References

2 / 21




Introduction

There is a trade-off between network simulations, networkemulators and real test-beds :

1 A network simulator has good scalability and reproducibi-lity.

2 A network emulator has good applicability and captures3GPP standard-compliant environments.

3 A test-bed has good applicability but reproducibility issuesin multi-vendor scenarios.

Optimizing software functions and simulating the multipathchannel in terms of a frequency domain representation, wedecrease the signal processing complexity in a software-only environment.

3 / 21




Objectives

Increase the scalability of real-time synthetic networks (Mul-tiple Remote Radio Units and User Ends) in a software-onlyenvironment.Prototype 4G and 5G rapid proof-of-concept designs beforelaunching to the market.Hybridize real-time synthetic network components, and Ra-dio Frequency (RF) hardware for complex scenarios.

4 / 21




Architecture

Architecture

We extracted Primary and Secondary SynchronizationSignals (PSS and SSS) information from the eNB andassigned to the UE (frame_type, cell_id).PBCH is decoded from the rxdataF at the UE(initial_synch_freq() function).

SyntheticNetwork

RealNetworkSynchronization

RRUs/DUs RRU/DU

RAU/DU

UE UE…

UE UE…

EPC/NGCBack-haul

Mid-haul

Front-haul

Testing DevicesRCC/CU

IF4p5

SyntheticNetworks

SynchronizationRRU/DU RRU/DU

RAU/DU

UE UE…UE UE…

EPC/NGCBack-haul

Mid-haul

Front-haul

Testing DevicesRCC/CU

IF4p5

Network scalability Application testabilityNetwork scalability

FIGURE – Architecture. 5 / 21




Architecture

Functional split IF4p5

We created new methodologies for C-RANs, where I/Q signalsare exchanged in the frequency domain (Split 7.1).

FIGURE – IF4p5 functional split at the transmitter [1]

6 / 21




Frequency domain extension

Single Instruction Multiple Data

We implemented new SSE and AVX2 optimized functions of themultipath channel to improve the emulation speed.

SIMD

Instruction

s

Data

Results

AVX2

AVX512

SSEAVX

FIGURE – SingleInstructions Multiple Data.

File Functioninit_freq_channel_AVX_float

freq_channel_AVX_floatinit_freq_channel_prach_AVX_float

abstraction.c freq_channel_prach_AVX_floatsincos256_ps

log256_psexp256_ps

multipath_channel.c multipath_channel_freq_AVX_floatmultipath_channel_prach_freq_AVX_float

rangen_double.c nfix_AVX, boxmuller_AVX_floatSHR3_AVX, UNI_AVX, NOR_AVX

do_DL_sig_freqchannel_sim.c do_UL_sig_freq

do_UL_sig_prach_freqdac.c dac_fixed_gain_AVX_float

dac_fixed_gain_prach_AVX_floatrf.c rf_rx_simple_freq_AVX_float

adc.c adc_AVX_floatadc_prach_AVX_float

TABLE – New AVX2optimized functions of themultipath channel.

Function Time Domain (µs) Frequency Domain(µs) GainDownlink multipath channel 45.58 9.774 4.66Uplink multipath channel 46.048 11.356 4.06

Downlink DAC 19.303 13.815 1.4Uplink DAC 19.487 13.99 1.39

Downlink receiver rf 500.288 37.062 13.49Uplink receiver rf 494.876 36.867 13.42Downlink ADC 18.52 2.304 8.04Uplink ADC 18.489 2.122 8.71

TABLE – Averagecomputation times in timeand frequency domains.C-RAN architecture, 5MHz of bandwidth, 10000frames, AWGN channelmodel, and 5 MB of iperftraffic.

7 / 21





Gaussian random number generators

Gaussian random number generators (rf_rx_simple_freq) areemployed to simulate the noise at the receiver.

-5 -4 -3 -2 -1 0 1 2 3 4 5

Fre

qu

en

cy o

f o

cu

rre

nce

Standard deviation

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

Fre

qu

en

cy o

f o

cu

rre

nce

Standard deviation

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

Fre

qu

en

cy o

f o

cu

rre

nce

Standard deviation

FIGURE – Zigguratmethod to generateGaussian randomnumbers.

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

-5-4-3-2-1 0 1 2 3 4 5

Fre

qu

en

cy o

f o

cu

rre

nce

Gaussian pseudo-random number

0

50000

100000

150000

200000

250000

300000

350000

-6 -4 -2 0 2 4 6

Fre

qu

en

cy o

f o

cu

rre

nce


0

100000

200000

300000

400000

500000

600000

700000

-6 -4 -2 0 2 4 6

Fre

qu

en

cy o

f o

cu

rre

nce


FIGURE – Box-Mullermethod to generateGaussian randomnumbers.

Generator Samples Chi-Square Computation time (ns/samples)Box-Muller 9.99e+05 290

SSE Box-Muller 1e+06 9.99e+05 74.5AVX2 Box-Muller 9.75e+05 37.4

Ziggurat 1e+06 220SSE Ziggurat 1e+06 1e+06 78AVX2 Ziggurat 1e+06 39

TABLE – Chi-Square andaverage computation timemetrics for Box-Muller andZiggurat methods.

8 / 21





Physical slot structure

In the frequency domain analysis the Cyclic Prefix is not imple-mented. Inter-symbol interference is not avoided. We change thetime_stamp in eNB_trx_read and UE_trx_read functions.

FIGURE – LTE resource blocksallocation (25 PRBs / 300 subcarrierindices / 512 FFT size) [2].

S 0 S 1 S 2 S 3 S 4 S 5 S 6

301

subc

arrie

rs +-

DC

S 0 S 1 S 2 S 3 S 4 S 5 S 6

40Ts 36Ts 36Ts

512Ts 512Ts

150 subcarrier indices 150 subcarrier indices

212 zero-padded indices

……

…… ……

36Ts

512Ts

Time Units (Ts)

Subcarrier indices

Slot in the frequency domain

Slot in the time domain

FIGURE –Physical slot structure. Ts = 1

512∗15000 = 130.21nsTime_stamp(time)=samples_per_tti=(40+512+6*36+6*512)*2 = 7680

Time_stamp(frequency)=symbols_per_tti (14) * ofdm_symbol_size (512)=7168.9 / 21





Channel Frequency Response

We create slot_fep_freq and lte_dl_channel_estimation_freq func-tions to exclude dfts and to add an offset to the rxdataF vector.

RemoveCyclicPrefix

Mod Mapp IFFTAdd

CyclicPrefix

DAC RF

Demod Demapp FFT ADC RF

CIR / CFR

Transmitter

Receiver

FIGURE – Orthogonal FrequencyDivision Multiplexing (OFDM) chain.

r(m)=s(m)*h(m)+n(m) (1)

R(k)=S(k).H(k)+N(k) (2)

Tapped Delay Line (TDL) model [3] :h(m)=

∑Np−1l=0 a[l]sinc(m − Fs(l + β)∆τd − 0.5Fsτmax )

H[k]=∑Np−1

i=0 a[l](j sin(2π kN ml)− cos(2π k

N ml))

ml = Fs(l + β)∆λd + 0.5Fsτmax ,∆τd = τmaxNp

N = sampling rate,Np = channel path number, Fs =

sampling frequency, β = real number to ensure h(m)

envelope continuity, τmax = maximum allowable delay

in the channel, a is the channel state vector,

m = samples in the time domain, k = samples in the frequency domain.

10 / 21





Synthetic Network Scalability

Scalability is enabled changing the scheduler behaviourper component carrier (CC).Each IF4p5 link has a physical Ethernet connection.

GTP-C GTP-U

RRC PDCP

RLC

MAC

HIGH-PHY

1 L1

, 1 L

2 in

stan

ces

-1 C

C

LOW-PHY

RFDEVICE

RFDEVICE

IFDEVICE

IFDEVICE

1 L1

inst

ance

GTP-C GTP-U

MME S-PGw

=

EPC

RCC

RR

UR

RH

IF4p

5 sp

lit

FIGURE – SimpleSynthetic Network.

GTP-C GTP-U

RRC PDCP

RLCMAC

HIGH-PHY

1 L1

, 1

L2 in

stan

ces

-2

CC

s

LOW-PHYLOW-PHY

RFDEVICERFDEVICE

RFDEVICERFDEVICE

IFDEVICEIFDEVICE

IFDEVICEIFDEVICE

2 L1

inst

ance

s

GTP-C GTP-U

MME S-PGw

=

EPC/NGC

RCC/CU

RR

U/D

U1

RR

U/D

U2

RR

H1

RR

H2

IF4p

5 sp

lits

FIGURE – SyntheticNetwork Scalability.

phy_procedures_eNB_TX :if (eNB->CC_id == 0)

→ eNB_dlsch_ulsch_scheduler(Mod_id , ...,CC_id)

→→ schedule_ue_spec(module_idP, ...,CC_id)

→→→ dlsch_scheduler_pre_processor(module_idP, ...,CC_id)

→→→→ store_dlsch_buffer(module_idP, ...,CC_id)

→→→→ assign_rbs_required(module_idP, ...,CC_id)

→→→→ sort_UEs(module_idP, ...,CC_id)

→→→→ store_dlsch_buffer(module_idP, ...,CC_id)

11 / 21





Hardware and Emulation Parameters

Parameter Single-UE Value / USRP B200mini-iBand 7

Transmitter gain 90 dBReceiver gain 120 dB

Transmitter power 15 dBmWorking Mode FDDCyclic Prefix Normal

Interface compression A-lawSystem Bandwidth 5 MHzTransmission Mode 1 SISO

Multipath Channel Model AWGN / Rayleigh 1

TABLE – Networkemulation parameters forthe C-RAN.

FIGURE – The C-RAN iscomposed of 3 PCs for theEPC, the RCC, and RRUs.The USRP, antennas andthe COTS UE areemployed for validation.

RCCEPC192.168.12.171

192.168.12.170

192.168.13.11192.168.13.10

172.16.0.2172.16.0.4172.16.0.6 UEs

192.168.14.171192.168.16.171

192.168.14.170192.168.16.170

RRUs

Backhaul IF4P5 fronthaul

FIGURE – Fronthaul andbackhaul networksegments for 3RRUs and 3UEs.

12 / 21





Maximum User Throughput

Downlink and uplink maximum user throughputs have errors of4.5% and 8.4% compared with specifications respectively.

MCS Time Frequency USRP B200mini-i TS 36.213 [4]Downlink 28 17.5 Mb/s 17.5 Mb/s 17.5 Mb/s 18.336 Mb/sUplink 18 8.43 Mb/s 8.43 Mb/s 8.43 Mb/s 9.144 Mb/s

TABLE – Maximum user throughput (5 MHz of Bandwidth, AWGN channel model).

13 / 21





Downlink Block Error Rate

BLER for both domains are pretty similar, however there is stillissues compared with reference [5].

10-3

10-2

10-1

100

0 5 10 15 20 25 30 35

BLE

R (T

ime

Dom

ain)

SNR (dB)

MCS0MCS3MCS6MCS9

MCS12MCS15

10-3

10-2

10-1

100

0 5 10 15 20 25 30 35

BLE

R (F

requ

ency

Dom

ain)

SNR (dB)

MCS0MCS3MCS6MCS9

MCS12MCS15

FIGURE – Downlink Block Error Rate for different MCSs (5 MHz of Bandwidth, 5000subframes, transmission mode 1, and Rayleigh channel model (1 tap)).

14 / 21





Average computation time

We accomplished a gain of almost one order of magnitude forboth, uplink and downlink multipath channels.

FIGURE – Average computation time(Time domain).

FIGURE – Average computation time(Frequency domain).

Channel function Time Domain (µs) Frequency Domain(µs) GainUplink Channel 596.232 72.758 8.19

Downlink Channel 596.833 78.811 7.57Uplink PRACH Channel n/a 219.202 n/a

TABLE – Average computation times intime and frequency domains. C-RANarchitecture, 5 MHz of bandwidth, 10000frames, AWGN channel model, and 5 MBof iperf downlink traffic.

15 / 21





Average computation time

101

102

103

104

105

1 2 3

Tim

e pe

r sub

fram

e (u

s)

UEs

Time DomainFrequency Domain

FIGURE – Average computation time benchmark.

16 / 21





Synthetic network scalability

RCCs CCs/RRUs UEs Time Domain µs Frequency Domain µs B200mini-i µs

1 11 1193.065 151.66 0.06512 2262.5 330.972 N/A3 3614.066 523.208 N/A

1 21 1280.8 162.25 N/A2 2215.87 358.2 N/A3 N/A 622.164 N/A

1 31 N/A 148.072 N/A2 N/A 397.556 N/A3 N/A 546.334 N/A

. . . Non-Real-time zone . .

TABLE – Average computation times of the multipath channel.

Real-time emulations can be improved for complex scenariosusing AVX512 instructions and more threads.

17 / 21





Real-time Coordinated Scheduling

We implemented the static coordinated scheduling. The RCCworks as the coordinator using 1 scheduler and multiple CCs.

242322212019181716151413121110

9876543210

RR

U1

0 1 2 3 4 5 6 7 8 9

UE1

1 RCC / 2 RRUs / 2CCs

Subframes

242322212019181716151413121110

9876543210

RR

U2

0 1 2 3 4 5 6 7 8 9

UE2

Subframes

Res

ourc

e Bl

ocks

FIGURE – StaticCoordinated Scheduling.Subframes 0 and 5 areused for commonchannels.

RCCs CCs/RRUs UEs Time Domain µs Frequency Domain µs

1 2 2 N/A 335.2

1 3 3 N/A 455.23

. . . Non-Real-time zone .

TABLE – Averagecomputation times of themultipath channel. TimeDomain does achievesynchronization.

FIGURE – Xforms(eNB->UE). Evensubframes ofUE->...thread[1].rxdataFand uplink traffic.

18 / 21





Video Demo

FIGURE – Real-time emulation methodologies for Centralized Radio AccessNetworks.

19 / 21

https://www.youtube.com/watch?v=ZX8qLqK4kb4

https://www.youtube.com/watch?v=ZX8qLqK4kb4




Conclusions

We successfully implemented affordable real-time emula-tion methodologies in the frequency domain for C-RANs asa prototyping framework to rapid proof-of-concept and time-to-market designs in a software-only environment.We reduced near 10-fold the average computation time ofthe multipath channel in the frequency domain compared tothe time domain. The cost in time we need to pay is relatedto the additional uplink PRACH channel.We improved the applicability and the scalability fro CRANson top of OpenAirInterface.Our proposal allows real-time 3GPP standard-compliant C-RANs emulations for downlink and uplink transmissions.

20 / 21




References

Gitlab branches : large_scale_simulations for RRUs + UEs,and master_large_scale_emulations for the RCC andmultiple CCs.Several videos related to the extensions in the frequencydomain.

21 / 21

https://gitlab.eurecom.fr/oai/openairinterface5g/tree/large_scale_simulations

https://gitlab.eurecom.fr/oai/openairinterface5g/tree/master_large_scale_emulations

https://www.youtube.com/channel/UCz_8dQJotLFiNyOOkW92ahg




L. M. P. Larsen, A. Checko, and H. L. Christiansen, “Asurvey of the functional splits proposed for 5g mobilecrosshaul networks,” IEEE Communications SurveysTutorials, vol. 21, no. 1, pp. 146–172, Firstquarter 2019.

LG. (2019) Lte resource grid. [Online]. Available :http://niviuk.free.fr/lte_resource_grid.html

F. Kaltenberger, “Low-complexity real-time signalprocessing for wireless communications,” Ph.D.dissertation, Vienna University of Technology, Vienna,Austria, May 2007.

3GPP, “Evolved universal terrestrial radio access(e-utra) :physical layer procedures,” 3rd GenerationPartnertship Project (3GPP), Technical Specificacion (TS)

21 / 21

http://niviuk.free.fr/lte_resource_grid.html




36.213, 10 2018, version 15.3.0. [Online]. Available :https://goo.gl/C8ePeU

EURECOM. (2011) Openairinterface dl simulation results.[Online]. Available : https://cordis.europa.eu/docs/projects/cnect/8/248268/080/deliverables/001-D33AppendixOpenAirInterfacelinklevelsimulationresults.pdf

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https://goo.gl/C8ePeU

https://cordis.europa.eu/docs/projects/cnect/8/248268/080/deliverables/001-D33AppendixOpenAirInterfacelinklevelsimulationresults.pdf




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