External Use

TM

End-to-End LTE System Characterization

of the Uplink Adaptation, Including Signal to

Noise Ratio (SINR) Analysis for Small Cell

Field Deployments

FTF-SDS-F0230

A P R . 2 0 1 4

Gopikrishna Charipadi | Wireless System Architect

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External Use 1

• Ankush Jain, L1 Software lead

• Loksiva Paruchuri, System Integration and Test

• Nirali Patel, Program Manager

• Saurabh Shandilya, Algorithms

• Saikat Senapati, L1 Software

Presenter Details

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External Use 2

Session Introduction

• Wireless OEMs and infrastructure vendors today are looking for:

− Commoditized small cells end-to-end solutions

− Turnkey solutions tested with industry commercial network elements

− SoC + L1 commercial software fully tested for qualification and mobility

− System characterization of small cell SoC + L1 SW offering for network

readiness with minimum integration effort for inter-operability testing

(IOT)

− Solutions that maximize spectral efficiency (maximum bits per Hz), multi-

user optimum scheduling, interference management and capacity

optimization (throughput and maximum # of users)

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Session Objectives

• After completing the session you will be able to understand:

− Challenges in end-to-end characterization of LTE small cell SoC and L1

software with LTE network elements including Radio hardware for Uplink

(UL)

− Interworking of system components, RF chipset in UL link adaptation

− Important 3GPP system parameters to maximize UL system

performance

− Systematic method of system optimization of LTE UL Link adaptation

− Configurability aspects of industry offering of LTE radio chipset

hardware, L1/L2 software

− Competitive/differentiating benefits of QorIQ Qonverge BSC913x small

cells system characterization that enables shorter time-to-market for

OEMs and network infrastructure vendors

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External Use 4

Agenda

• LTE network deployment overview and

heterogeneous networks

• Freescale small cell (BSC913x) uplink link

adaptation characterization

• Link adaptation logical topology

• Link adaptation:

− Step 1: RF characterization

− Step 2: Signal to Interference and Noise (SINR)

characterization

− Step 3: Power control characterization with end-to-end

system results

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External Use 5

LTE Network Deployment Overview

Freescale small cell solutions’ target market is femto/enterprise/pico

outdoor/metrocells

Macro Macro

Wifi

Hotspots

Small Cells

Metro

Wifi

RRU RRU

Metro

Metro Macro

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Technology Solution – Heterogeneous Networks

Access Network Edge

DSLAM/MSAN BRAS

RNC/EPC/

AGW

Micro/Pico

BTS

Macro

BTS

Freescale Base Station

Sub-segment

Home/SMB Femto 8 -16 users

Metro Microcell up to 200 users

Macro Hundreds of users

Enterprise

Pico/Femto Hot spots, campuses,

high-rise buildings

32 to 64 users

Enterprise Pico/Femto

Femto BTS Standalone or

integrated into

RGW, STB …

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Freescale System Characterization End-to-end Setup

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External Use 8

Freescale Small Cell Solution:

QorIQ Qonverge BSC913x Series

BSC913x Form Factor Reference Design Board

Features:

• Complete communications platform enabling LTE,

WCDMA/HSPA+

• Dual-band system covering up to 2.7 GHz

• Development and debugging tools available from

Freescale and our partners

Benefits:

• Form factor design helps speed customers time to market

• Turn-key hardware design

• Integrated with ADI RF solutions

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External Use 9

QorIQ Qonverge BSC913x Reference Design and

Link Adaptation Characterization

Freescale: Physical layer, board support package and network interface components

(in light-blue).

Note: Many LTE UL/DL processing and signal processing blocks are implemented in

MAPLE accelerators that is part of 913x SoC HW.

L2/L3 partner: Most of the L2/L3 Layer

Third-party hardware: All hardware and reference design board

Physical Layer

- Sensitivity (SMU based) -Data/Control power diff -Open-loop SINR tests

L2 Layer

Link Adaptation: -Closed-loop SINR test

- MCS selection

Network Interface

RF Tx/Rx with AGC

RF

PAs

RLC

MAC

Frequency Processing

User

Processing

IP

Security,

ASF,

IP

Scheduler (RRM)

SmartDSP OS Linux OS Linux OS

PDCP

(Encypt)

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External Use 10

SINR Definition

• SINR is Signal Power to Interference plus Noise Power Ratio; SINR is commonly used to measure the quality of wireless links

• A wireless communication system is usually affected by environmental parameters, thermal noise and interference from other wireless equipments

• To measure the quality of wireless link, SINR estimation is an integral part of any wireless receiver system design

• In LTE, link adaptation is done based on SINR measured in 9131 FSL Physical layer on:

− PUSCH (UL data channel)

− PUCCH (UL control channel)

− SRS (UL sounding reference signal)

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Link Adaptation Logical Topology

UE Tx power = min (Pmax, P0 + αPL + 10logM + f(Δi))

UE

eNB L1 SW

eNB L2 SW

Power

Control

AMC RRM

(scheduler)

Reference

signals

Tx

(Pmax, PL)

UL grant (Resource

blocks (M) , MCS)

UL Data

(N + 4)

f (Δi) = TPC

commands

SINRtarget

SINRmeas

SINR meas

L2 filtering

eNodeB

(de)modulator/

(De)coder

DM-RS /

SRS

Po, α

• Link Adaptation enables the eNodeB to adapt the UE’s Tx power and throughput based on the radio link quality from UE to eNB

• UL Link Adaptation is applied independently on:

− PUSCH (UL data channel)

− PUCCH (UL control channel)

− SRS (UL sounding reference signal)

• By measuring respective SINR on DM-RS

(PUSCH/PUCCH) and SRS signals

• And issuing Transmit Power Control (TPC) commands via f(Δi) to maintain a target SINR required to support a selected MCS by RRM in the presence of fast fading and interference

• To maintain this specific SINRtarget over a long range, Path-loss/shadowing compensation is performed via (Po, α) broadcast at cell-level by eNB

SINRmeas

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Link Adaptation:

Step 1: RF Characterization

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STEP 1: RF Chip UL Characterization

• ADI RF chip on BSC913x RDB is software programmable for eg:

− Digital channel filtering for UL adjacent channel Interference rejection

− AGC setpoint and gain table for wide I/L dynamic range of operation

− AGC gain mode: Hybrid vs fast-attack mode

• Eg: Hybrid mode provided better BLER for full traffic and burst traffic (silent –to-traffic subframes ie., 2 RBs to 48 RBs). This mode required FSL SoC to provide periodic strobes to ADI so AGC gain updates are synchronized to TTI subframe boundaries

Source: Analog Devices website

• Rx front end chain contains:

− LNA

− Mixer

− Amplifiers

− Low Pass Filter (AAF)

− ADC

− Channel filtering

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Link Adaptation:

Step 2: SINR Measurement

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Challenges in Designing PUSCH SINR Estimation

Symbol

0

Symbol

1

Symbol

2 DMRS

Symbol

4

Symbol

5

Symbol

6

Frequency

domain cross

correlation

Filtering to

minimise

noise

User power

estimate

Filter gain

compensation

Noise signal

estimate

Noise power

estimate

SINR estimation

and FAPI index

generation

Ref ZC signal

Slot =>

PUSCH RBs

Slot 0 Slot 1 LTE system

Bandwidth

PUSCH SINR estimation block diagram

Requirements

• SINR is estimated across entire user allocation (max up to system BW)

• Compared with narrow BW channels like PUCCH and less frequent channels like SRS, PUSCH is wideband and occurs in every TTI and hence requires efficient and low complexity implementation

• Average SINR across allocation is reported in FAPI indication messages

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Challenges in Designing PUCCH SINR Algorithm

Pucch RB

Pucch RB

Slot 0 Slot 1 LTE system

Bandwidth

Symbol

0 DM-RS

Symbol

2

Symbol

3

Symbol

4 DM-RS

Symbol

5

Frequency

domain cross

correlation

Filtering to

separate

users

User power

estimate

Estimate of

transmitted

reference signal

Noise signal

estimate

Noise power

estimate

SINR estimation

and FAPI index

generation

Ref ZC signal

Slot =>

PUCCH SINR estimation block diagram

Requirements

• PUCCH data always span across 1 RB and is used for UL control information

• Accurate SINR estimation is challenging considering multiple CDM based users within just 12 sub-carriers (1RB)

• PUCCH is very sensitive to timing offset

• It’s also sensitive to fading due to inherent frequency diversity used across slots

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External Use 17

Challenges in Designing SRS SINR Estimation

Requirements

• SRS is mainly used for frequency selective scheduling of the users

• Multiple CDM based users are span across SRS bandwidth and SINR is computed for each user on per RB basis

• Computed SINR also considers the impact of fading (frequency selective) in each RB of a given SRS allocation bandwidth

PUSCH RBs

Slot 0 Slot 1 LTE system

Bandwidth

S

R

S

Frequency-

domain cross

correlation

Frequency to

time-domain

mapping

Filtering to

separate

users

Estimate of

transmitted

reference signal

Noise signal

estimate

Noise power

estimate

SINR estimation

per RB and FAPI

index generation

Ref ZC signal

Noise

reduction

on module

Time to

Frequency

domain mapping

User power

estimate per

RB

SRS SINR estimation block diagram

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External Use 18

Observations:

1. Estimated SINR is frequency selective and estimation is pretty close to the reference channel

Challenges in Designing SRS SINR Estimation

20 MHz: Performance of SRS across

resource blocks in EVA5 channel across

different SINR values

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External Use 19

FAPI SINR Reporting

• Fixed point processors are not efficient while computing SINR in

logarithmic domain

− FSL L1 algorithms are highly optimized to compute dB values of SINR

− Typical scenario of SRS where SINR is reported per RB basis, these

algorithms are highly squeezed in terms of cycle consumed

− 30% cycles gain for 1 UE, 41% cycles gain for 2UEs

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Link Adaptation:

Step 3: Power Control

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External Use 21

Open Loop and Closed Loop PUSCH Power Control in OTA

25

15

12.5

10.5

8.5 7

5.5

3 1.5

-1 -2.5

-4

-2

0

2

4

6

8

10

12

14

16

18

20

22

24

26

23 22 20 16 13 11 10 9 5 2 0

SIN

R

MCS

MCS Vs SINR_Required @5% BLER

SINR_Required

Over-The-Air Power Control setup

1. Variable attenuator with alpha = 0 to simulate UE moving from cell center to cell edge

2. In Open Loop, required SINRtarget for each MCS characterized via HARQ BLER statistics

3. Then, Closed Loop Power control enabled to verify RRM MCS changes wrt SINR

4. Finally, over-the-air testing verified for OLPC path-loss compensation and CLPC

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External Use 22

PUSCH and PUCCH Relative Power Characterization

• In MUE scenario, it’s important to characterize system performance when

there is relative power difference between PUCCH and PUSCH signals

received at the eNodeB (eg., MCS 23 in previous slide)

− For an efficient implementation, fixed-point FFT is performed on composite signal

received at eNodeB instead of floating-point FFT

− Relative power difference between PUSCH and PUCCH can impact decoding

performance, CRC failures and SINR degradation

− SMU based characterization is performed to simulate and verify different scenarios

with relative PUCCH and PUSCH power difference and its impact on CRC, CQI

decoding, SINR estimation, HARQ decoding

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External Use 23

PUSCH Closed Loop Power Control on OTA

• Initially, eNodeB sends Transmit Power Control (TPC) commands to increase the UE Tx

power until the eNB received SINR on PUSCH reaches SINRtarget ~7 dB

• When attenuator is switched in middle of test, eNodeB sends TPC commands until UE Tx

power increases further and received SINR recovers back to SINRtarget ~ 7 dB

• This verifies the end to end working on power control part of link adaptation

0

0.5

1

1.5

2

2.5

1.5

4.5

7.5

10.5

13.5

16.5

19.5

22.5

25.5

28.5

31.5

34.5

37.5

40.5

43.5 Meas_SINR (dB) Vs TPC CMDs

Meas_SINR TPC_CMDS

SINR (dB) TPC cmd value

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External Use 24

PUCCH Closed Loop Power Control on OTA

• Closed loop control has been verified

for single UE with a walkabout test

• PUCCH transmit power should be

read as (-ve) of what is plotted

• It is seen that UE PUCCH Tx power is

holding well when path loss is

constant and responding to transmit

power control commands (g(i)) from

eNB

• Note: At eNodeB, PUCCH is allocated

only for 1 RB resulting in limited

accuracy of SINR estimated and

hence this requires L2 filtering to get

a smoother SINRmeasured.

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External Use 25

Summary

• Introduction to LTE Link adaptation system

• System level challenges in characterizing UL Link adaptation

solution in LTE small cell system

• Freescale’s QorIQ Qonverge BSC913x SoC small cell link

adaptation solution including:

− RF characterization

− Specific SINR measurement methods for different UL LTE channels

− Open-loop power control characterization

− Closed-loop power control characterization

• Competitive/differentiating benefits of QorIQ Qonverge BSC913x small

cells system characterization that enables shorter time-to-market for

OEMs and network infrastructure vendors

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Q&A

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External Use 27

Introducing The

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Extending the industry’s broadest portfolio of 64-bit multicore SoCs Built on the ARM® Cortex®-A57 architecture with integrated L2 switch enabling

interconnect and peripherals to provide a complete system-on-chip solution

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External Use 28

QorIQ LS2 Family Key Features

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ease of use for smarter, more

capable networks

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interconnect and memory bandwidth

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External Use 29

See the LS2 Family First in the Tech Lab!

4 new demos built on QorIQ LS2 processors:

Performance Analysis Made Easy

Leave the Packet Processing To Us

Combining Ease of Use with Performance

Tools for Every Step of Your Design

TM

© 2014 Freescale Semiconductor, Inc. | External Use

www.Freescale.com