5G K-SimSys to SimNet Interworking...

mm-dd-yyyy Doc. No. Page

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Project Title: Research and Development of Open

5G Reference Model

5G K-SimSys to SimNet

Interworking Method

SLS-NS Interworking Method for TCP-MAC/PHY Cross-Layering


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Document Information

Affiliation Name Date Signature

Author

Hankyong National University

Dongjin Han Dec. 28, 2018


Wonseok Lee Jul. 18, 2018


Hayoung Seong Dec. 28, 2018


Hyun-Ho Choi Dec. 28, 2018


Howon Lee Dec. 28, 2018


In-Ho Lee Dec. 28, 2018

Reviewer


Hyun-Ho Choi Dec. 31, 2018


Howon Lee Dec. 31, 2018



Team Leader Hankyong National University


Version V0.1

Publication

Date Jan. 02, 2019


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Version Information

Version V0.1

Author Dongjin Han, Wonseok Lee, Hayoung Seong, Hyun-Ho Choi, Howon Lee,

In-Ho Lee

Reviewer Hyun-Ho Choi, Howon Lee, In-Ho Lee

Publication Date Jan. 02, 2019

Revision History

Revision Date Version Revision Description Author

July 20, 2018 V0.0 Draft (Korean) Dongjin Han, Wonseok Lee, Hayoung Seong,

Hyun-Ho Choi, Howon Lee, In-Ho Lee

Nov. 30, 2018 V0.1 Draft revision (Korean)Dongjin Han, Hayoung Seong,


Jan. 02, 2019 V0.1 Final revision (English)Dongjin Han, Hayoung Seong,



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Table of Contents

Abbreviations and Acronyms

References

1. Introduction ..................................................................................................... 9

2. Previous Study ................................................................................................ 11

2.1. Wireless TCP …..……................................................................................... 11

2.2. Multipath TCP ............................................................................................ 12

2.3. Cross-Layering between TCP and MAC/PHY ….................................................... 13

2.4. 4G-5G Interworking .................................................................................... 15

3. Simulation Guideline for TCP-MAC/PHY Cross-Layering …………...………….......... 22

3.1. Structure for TCP-MAC/PHY Cross-Layering ….................................................... 22

3.2. Guideline for TCP-MAC/PHY Cross-Layering …..……………….…............................. 25

4. SLS-NS Interworking Method ….………………………………………….........……............ 29

4.1. SLS-NS Interworking Scenario and Method …….….............................................. 29

4.2. Performance Evaluation Using OPNET ……………………….................................... 40

5. Conclusions …….………….……........................................................................... 51


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Abbreviations

ACK

BS

CC

CDF

CWND

DL

eMBB

EESM

ID

LOS

MAC

NLOS

mmWave

MSS

NS

PHY

QoS

RTT

Acknowledge

Base station

Congestion control

Cumulative distribution function

Congestion window size

Downlink

enhanced Mobile Broadband

Exponential effective SNR mapping

Identification

Line-of-sight

Medium access control

Non line-of-sight

Millimeter-waveband (30 to 300GHz) will be used for 6 to 100GHz

Maximum segment size

Network simulation

Physical

Quality-of-service

Round trip time


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SINR

SLS

SNR

ssthresh

TCP

Tx

UL

Signal-to-interference-plus-noise ratio

System-level simulation

Signal-to-noise ratio

Slow start threshold

Transmission Control Protocol

Transmit

Uplink


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References

[1] Menglei Zhang, et al. “Transport Layer Performance in 5G mmWave Cellular,” Millimeter-wave Networking

Workshop, 2016.

[2] K.-C. Leung and Victor OK Li. "Transmission control protocol (TCP) in wireless networks: issues, approaches,

and challenges." IEEE Communications Surveys & Tutorials, 2006.

[3] Bakre, Ajay, and B. R. Badrinath. "I-TCP: Indirect TCP for mobile hosts." Distributed Computing Systems,

1995., Proceedings of the 15th International Conference on. IEEE, 1995.

[4] Brown, Kevin, and Suresh Singh. "M-TCP: TCP for mobile cellular networks." ACM SIGCOMM Computer

Communication Review 27.5 (1997): 19-43.

[5] Haas, Zygmunt J. "Mobile-TCP: An asymmetric transport protocol design for mobile systems." Mobile

Multimedia Communications. Springer, Boston, MA, 1997.

[6] Song, Young-Joo, and Young-Joo Suh. "Rate-control snoop: a reliable transport protocol for heterogeneous

networks with wired and wireless links." Wireless Communications and Networking, 2003. WCNC 2003.

2003 IEEE. Vol. 2. IEEE, 2003.

[7] Ayanoglu, Ender, et al. "AIRMAIL: A link-layer protocol for wireless networks." Wireless Networks 1.1 (1995):

47-60.

[8] Buchholcz, Gergo, Thomas Ziegler, and Tien Van Do. "TCP-ELN: on the protocol aspects and performance of

explicit loss notification for TCP over wireless networks." null. IEEE, 2005.

[9] Mathis, Matt, et al. TCP selective acknowledgment options. No. RFC 2018. 1996.

[10] Stevens, W. Richard. "TCP slow start, congestion avoidance, fast retransmit, and fast recovery algorithms."

(1997).

[11] Wu, EH-K., and Mei-Zhen Chen. "JTCP: Jitter-based TCP for heterogeneous wireless networks." IEEE Journal

on Selected Areas in Communications 22.4 (2004): 757-766.

[12] Fu, Cheng Peng, and Soung C. Liew. "TCP Veno: TCP enhancement for transmission over wireless access

networks." IEEE Journal on selected areas in communications 21.2 (2003): 216-228.

[13] Mascolo, Saverio, et al. "TCP westwood: Bandwidth estimation for enhanced transport over wireless links."

Proceedings of the 7th annual international conference on Mobile computing and networking. ACM, 2001.

[14] Biaz, Saad, and Nitin H. Vaidya. "" De-randomizing" congestion losses to improve TCP performance over

wired-wireless networks." IEEE/ACM Transactions on networking 13.3 (2005): 596-608.

[15] Xu, Kai, Ye Tian, and Nirwan Ansari. "TCP-Jersey for wireless IP communications." IEEE Journal on selected


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areas in communications 22.4 (2004): 747-756.

[16] Akyildiz, Ian F., Giacomo Morabito, and Sergio Palazzo. "TCP-Peach: a new congestion control scheme for

satellite IP networks." IEEE/ACM Transactions on Networking (ToN) 9.3 (2001): 307-321.

[17] Tsaoussidis, Vassilios, and Hussein Badr. "TCP-probing: towards an error control schema with energy and

throughput performance gains." Network Protocols, 2000. Proceedings. 2000 International Conference on.

IEEE, 2000.

[18] Goff, Tom, et al. "Freeze-TCP: A true end-to-end TCP enhancement mechanism for mobile environments."

INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies.

Proceedings. IEEE. Vol. 3. IEEE, 2000.

[19] Chinta, Madhav, Abdelsalam Helal, and Choonhwa Lee. "ILC-TCP: An interlayer collaboration protocol for tcp

performance improvement in mobile and wireless environments." Wireless Communications and

Networking, 2003. WCNC 2003. 2003 IEEE. Vol. 2. IEEE, 2003.

[20] Singh, Ajay Kumar, and Kishore Kankipati. "TCP-ADA: TCP with adaptive delayed acknowledgement for

mobile ad hoc networks." Wireless Communications and Networking Conference, 2004. WCNC. 2004 IEEE.

Vol. 3. IEEE, 2004.

[21] Bhandarkar, Sumitha, et al. "TCP-DCR: A novel protocol for tolerating wireless channel errors." IEEE

Transactions on Mobile Computing 4.5 (2005): 517-529.

[22] M. Polese, R. Jana, and M. Zorzi. "TCP in 5G mmWave Networks: Link Level Retransmissions and MP-TCP."

IEEE Infocom 2017.

[23] Azzino, Tommy, et al. "X-TCP: A Cross Layer Approach for TCP Uplink Flows in mmWave Networks."

MEDHOCNET 2017.

[24] "4G-5G Interworking, RAN-level and CN-level Interworking," Samsung, June 2017.


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1. Introduction

TCP issue in 5G mmWave link

Due to the nature of the high frequency band, the mmWave link causes blockage, link

disruption, and large fluctuation of bandwidth depending on the change of LOS and NLOS.

This change in the link layer generates various problems that were not considered in the

conventional TCP operation. In the mmWave channel environment, the operation of the

conventional TCP takes a very long time to reach the maximum transmission rate after the

occurrence of the outage, and induces a very high round trip time (RTT) and buffer block

problem in the NLOS condition. This TCP problem reduces the overall network performance

with wasted radio resources and makes it difficult to guarantee the required end-to-end

quality-of-service (QoS) of users [1].

Figure 1-1: Channel dynamics and TCP performances in mmWave link


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Background of SLS-NS interworking research

Wireless channel variation becomes considerably larger in mmWave frequency bands,

which can induce severe TCP performance degradation. Thus, an advanced congestion

control algorithm of TCP considering such large wireless channel variation can be needed to

prevent the TCP performance degradation. In our study, we focus on a SLS-NS interworking

method based on cross-layering between TCP in NS and MAC/PHY in SLS so as to develop

an advanced congestion control algorithm considering serious wireless channel variation, as

shown in Figure 1-2. In particular, in the research of SLS-NS interworking, we use 5G K-

SimSys as SLS to investigate wireless channel characteristics, and then using 5G K-SimNet as

NS, we propose a congestion control algorithm utilizing the wireless channel characteristics

in order to enhance TCP performance

Figure 1-2: Network structure in terms of NS and SLS


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2. Previous Study

2.1. Wireless TCP

Objective of wireless TCP: To prevent inefficient operation of conventional TCP due to

packet loss in wireless link by distinguishing the congestion in wired line and the bit

error in wireless link [2]

Split connection approach: separate TCP connection into FH(Fixed Host)-BS connection

and MH(Mobile Host)-BS connection and handle two TCP connections independently

- Indirect TCP (I-TCP) [3]

- M-TCP : TCP for mobile cellular networks [4]

- Mobile-TCP [5], etc.

Link layer technique: a method to retransmit the erroneous packets at the link layer of

BS before detecting the packet loss at the sender Throughput increases but delay

increases accordingly.

- Snoop [6]

- AIRMAIL [7], etc.

End-to-end technique: a method to call a fast retransmit procedure before timeout by

sending a specific signal to a corresponding TCP layer when reconnecting a wireless link

- TCP-ELN (Explicit Loss Notification) [8]

- TCP Selective Acknowledgments (SACK) [9]

- Fast Retransmission [10], etc.

Congestion detection technique: a method to find where the packet loss has occurred

and perform an appropriate traffic control


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- Jitter TCP (JTCP) [11]

- TCP Veno [12]

- TCP Westwood [13]

- TCP-Casablanca [14]

- TCP-Jersey [15]

- TCP-Peach [16]

- TCP-Probing [17], etc.

State suspension technique: a method to pause TCP connection when wireless error

occurs

- Freeze-TCP [18]

- ILC-TCP (Interlayer Collaboration Protocol for TCP) [19], etc.

Response postponement technique: a method that TCP clients slow down the triggering

of traffic control responses

- TCP-ADA (TCP with adaptive delayed acknowledgement) [20]

- TCP-DCR (TCP Delayed Congestion Response) [21], etc.

2.2. Multipath TCP

An approach to obtain the path diversity by using two paths of LTE and mmWave [22]

- Uncoupled approach: Each flow is independent each other (i.e., two single-path TCPs

operated).

Coupled approach: Congestion of one flow affects the behavior of the other flow If

one flow is congested, it sends traffic to the other flow.


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Figure 2.2-1: Overview of multipath-TCP

In multipath TPC, the TCP performance is improved by the use of LTE link, as shown in

Figure 2.2-2.

Disadvantages: Current congestion control algorithm is not suitable for mmWave link.

Figure 2.2-2: Performance evaluation of multipath-TCP

2.3. Cross-Layering between TCP and MAC/PHY

Concept of cross-Layering


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vs

Figure 2.3-1: Comparison of typical TCP and cross-layering TCP

Optimize TCP cwnd size and procedure by providing lower layer information (SINR,

buffer status, rate, etc.) to upper TCP layer

X-TCP [23]: Adjusts the TCP cwnd at the mobile terminal based on the estimated value

of the RTT obtained from the ACK reception, the SINR value measured at the mmWave

physical layer, and the estimated value of the available transmission rate (uplink TCP only)

- Simply, cwnd edatarate * rttmin if SINR > 0

- Otherwise, cwnd λ * edatarate * rttmin (λ is an empirical value)

TCP performance in NLOS

Figure 2.3-2: TCP performance with and without cross-layering

Issue: X-TCP does not consider the operation of downlink TCP TCP split approach can

be applied.


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2.4. 4G-5G Interworking

Interworking Architecture [24]

Figure 2.4-1: Interworking Architecture

RAN-level Interworking

- Using a direct interface between LTE eNB and 5G NB

- NSA (Non-Standalone Architecture)

- Control

• RRC message is transmitted over the LTE radio interface

• Connection and the mobility of UE are controlled by LTE eNB

- User traffic

• PDCP aggregation: simultaneously transmitted through LTE eNB and 5G NB

• CN-split Bearer: by using 5G NB only


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Figure 2.4-2: RAN-level interworking architecture

CN-level Interworking

- EPC entity is connected to the 5GC entity

- SA (Standalone Architecture)

- Single registration

• UE registers to either one of the LTE or 5G networks

• UE context is delivered when the connected network is changed

- Dual registration

• UE to register individually with EPC and 5GC

• No interface between MME and AMF


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Figure 2.4-3: CN-level interworking architecture


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Performance Analysis

- Peak Data Rate

• BW below 6 GHz: 80 MHz, peak spectral efficiency: 15 bit/s/Hz peak data rate: 1.2

Gbps.

• BW above 6 GHz: 667 MHz, peak spectral efficiency: 30 bit/s/Hz peak data rate: 20

Gbps

Figure 2.4-4: Throughput Comparison

- Control Plane Latency

• Defined as “the time to move from a battery efficient state (e.g. IDLE) to the start of

continuous data transfer (e.g. ACTIVE).”

Figure 2.4-5: Control Plane Latency Comparison

- User Plane Latency

• Defined as “the time to successfully deliver an application layer packet/message from

the radio protocol layer 2/3 SDU ingress point to the radio protocol layer 2/3 SDU

egress point via the radio interface in both uplink and downlink directions (i.e., the

latency between 5G NB MAC and UE MAC)”


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Figure 2.4-6: User Plane Latency Comparison

Mobility

Figure 2.4-7: NR-NR Handover/Switching in RAN-level Interworking

Figure 2.4-8: NR-NR Handover in CN-level Interworking


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Figure 2.4-9: NR-to-LTE Fallback in RAN-level Interworking

Figure 2.4-10: NR-to-LTE Fallback in CN-level Interworking


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Migration to a True 5G Network

Figure 2.4-11: Migration structure to 5G network

Issues for end-to-end performance

- Selection of 4G-5G interworking architecture

• RAN-level interworking

• CN-level interworking

- The location to place TCPC agent when using split TCP

- Link selection algorithms: 4G only, 4G+5G, or 5G only

- Packet distribution method considering 4G and 5G link state when using dual link

• Consider the highly dynamic link rate difference between 5G's NLOS and LOS

• Minimize packet error, packet drop, and packet reordering to prevent TCP timeout


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3. Simulation Guideline for TCP-MAC/PHY Cross-Layering

3.1. Structure for TCP-MAC/PHY Cross-Layering

Single TCP

- The most basic method, Use only one TCP connection: 5G or 4G

- Cross layering in UE: Uplink congestion control by reporting the uplink state information

to TCP layer

- Ref: Azzino, Tommy, et al. "X-TCP: A Cross Layer Approach for TCP Uplink Flows in

mmWave Networks." MEDHOCNET 2017

Figure 3.1-1: Structure of single TCP

Splitted TCP

- Cross layering in UE

- Apply the split connection technique by separating TCP into wireless section and wired

section

- Cross layering in BSs: Downlink congestion control by reporting the downlink state

information to the cloud server


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- Ref: Yun Chao Hu, Milan Patel, Dario Sabella, Nurit Sprecher and Valerie Young, ”Mobile

Edge Computing A key technology towards 5G First edition”, Sep. 2015

Figure 3.1-2: Structure of splitted TCP

MP-TCP

- Cross layering in UE

- Use two TCP connections simultaneously

- Ref: M. Polese, R. Jana, and M. Zorzi. "TCP in 5G mmWave Networks: Link Level

Retransmissions and MP-TCP." IEEE Infocom 2017


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Figure 3.1-3: Structure of MP-TCP

Decoupled MP-TCP

- Split Connection, Cross layering in UE and BSs, MP-TCP

- Decoupling: Operate TCP connections independently (i.e., independent congestion control)

Figure 3.1-4: Structure of decoupled MP-TCP

Coupled MP-TCP

- Split Connection, Cross layering in UE and BSs, MP-TCP


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- Coupling: one network manages TCP connection with a cloud server (i.e., coupled

congestion control)

- Issue: where to do the coupling: 4G, 5G, MME, or Server

Figure 3.1-5: Structure of coupled MP-TCP

3.2. Guideline for TCP-MAC/PHY Cross-Layering

Comparisons of TCP-MAC/PHY cross-layering structures

Single TCP Splitted

TCP

MP-TCP Decoupled

MP-TCP

Coupled

MP-TCP

Perf

orm

ance

- UL-CC: O

- DL-CC: X

- Cross-layering in

UE: O

- Cross-layering in

BS: X

- UL-CC: O

- DL-CC: O

- Cross-layering in

UE: O

- Cross-layering in

two BSs: O

- UL-CC: O

- DL-CC: X

- Cross-layering in

UE: O

- Cross-layering in

BS: X

- UL-CC: O

- DL-CC: O

- Cross-layering in

UE: O

- Cross-layering in

two BSs: O

- UL-CC: O

- DL-CC: O

- Cross-layering in

UE: O

- Cross-layering in

one BS: O

Requ

irem

ents

- UL state info.

feedback to TCP

- Selection

algorithm for

- UL state info.

Feedback to TCP

- DL state info.

feedback to

- UL state info.

Feedback to TCP

- 2 TCP layers in

UE and server

- UL state info.

Feedback to TCP

- DL state info.

feedback to

- UL state info.

Feedback to TCP

- DL state info.

feedback to


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TCP connection

between 4G and

5G in UE

server

- 2 TCP layers in

4G and 5G BSs

- 4G/5G selection

algorithm in UE

server

- 2 TCP layers in

UE, BS, and

server

- Employ 4 TCP

connections

server

- 2 TCP layers in

UE & 3 TCP

layers in one BS

- Employ 3 TCP

connections

- Packet

forwarding

between BSs

- Decision who will

do coupling

Pros - Simple & low

implementation

cost

- Better

performance

than SP-TCP

- Improved

performance

- Improved

performance in

terms of speed

and reliability

- Improved

performance in

terms of speed

and reliability

- Overhead is

reduced

compared to

decoupled MP-

TCP

Cons - Low performance - Overhead in BS

with 2 TCP layers

- Overhead in UE

with 2 TCP layers

- Overhead in UE,

BS & server that

use 2 TCP layers

- Delay variance

due to packet

forwarding

between BSs

Guideline for TCP-MAC/PHY cross-layering

- Apply hybrid approach: Cross-Layering + Splitted TCP + Multipath-TCP + Coupling

between 4G and 5G networks

Recommend the structure of Coupled MP-TCP for TCP-MAC/PHY cross-layering in

4G-5G interworking architecture


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Basic operation procedure of coupled MP-TCP

Figure 3.2-1: Basic operation procedure of coupled MP-TCP

- Step 1: Three TCP connections are established between UE and 4G BS (i.e., TCP 1),

between 4G BS and server (i.e., TCP 2), and between UE and 5G BS (i.e., TCP 3).

- Step 2: Tunneling between 4G BS and 5G BS is created.

- Step 3: UE receives UL state information (i.e., RSSI, SINR, etc.) from two BSs.


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- Step 4: UE reports UL state information to its TCP layer.

- Step 5: UE’s TCP layer does a congestion control for UL data session.

- Step 6: Uplink data is delivered to server via both 4G and 5G networks.

- Step 7: UE feeds back DL state information to 4G BS.

- Step 8: 4G BS’s TCP does a congestion control based on the feedback of DL state info.

- Step 9: 4G BS forwards the DL state information to the server and the server’s TCP does

a congestion control.

- Step 10: Server transmits downlink data to 4G BS and this data is delivered to UE via

both 4G and 5G networks.


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4. SLS-NS Interworking Method

4.1. SLS-NS Interworking Scenario and Method

SLS-NS interworking scenario

Figure 4.1-1 shows the interworking scenario between MAC/PHY-layer of SLS and TCP-

layer of NS to realize the SLS-NS interworking. As seen in Figure 4.1-1, for the SLS-NS

interworking the statistical results of effective SINR or user throughput are used to

determine parameter values of congestion control algorithm, which can improve TCP

performance in NS.

Figure 4.1-1: 5G K-SimSys to K-SimNet interworking scenario

Analysis of 5G K-SimSys simulation results

Table 4.1-1 shows 5G K-SimSys simulation scenario and parameter values.

Table 4.1-1: 5G K-SimSys simulation scenario

Parameter value


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System & channel model Downlink urban macro cell

Carrier frequency 2GHz, 6GHz, 28GHz

Bandwidth 10MHz

BS Tx power 44 dBm

Noise figure 5dB

Number of BS vertical antennas 2

Number of BS horizontal antennas 2

Number of BS vertical panels 1

Number of BS horizontal panels 1

Number of BS Tx antenna ports 2

BS vertical antenna distance 0.5λ BS horizontal antenna distance 0.5λ Number of MS vertical antennas 1

Number of MS horizontal antennas 2

Number of MS vertical panels 1

Number of MS horizontal panels 1

MS horizontal antenna distance 0.5λ Number of cells 19

Number of sectors per cell 3

Number of MSs per sector 1

Inter site distance 500m

Minimum distance between BS and MS 10m


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Figures 4.1-2 ~ 15 show the 5G K-SimSys simulation results (i.e., statistical results of

effective SINR) for the simulation scenario in Table 4.1-1. From the simulation results, it is

observed that the instantaneous effective SINRs can increase or decrease by more than 20dB

due to the considerable wireless channel variations. As such large channel variations can

cause severe TCP performance degradation, we clearly recognize that an advanced

congestion control algorithm of TCP considering effective SINR variations is required to

prevent the serious TCP performance degradation.

Figure 4.1-2: Mean and standard deviation of effective SINR at 2GHz carrier frequency


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Figure 4.1-3: CDF of effective SINR at 2GHz carrier frequency

Figure 4.1-4: CDF of effective SINR variations at 2GHz carrier frequency


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Figure 4.1-9: CDF of effective SINR variations at 6GHz carrier freque

(Results of Figure 4.1-8 in the range of -50dB to -20dB)



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(Results of Figure 4.1-13 in the range of -50dB to -20dB)


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Advanced congestion control algorithm of TCP

Figure 4.1-16 shows the 5G K-SimSys to K-SimNet interworking method for TCP

performance enhancement. As in Figure 4.1-16, first instantaneous effective SINRs for each

of users for a given simulation scenario are collected using 5G K-SimSys, and then the

statistical results of them are obtained for each user, where the statistical results of effective

SINRs include mean, variance, and CDF of effective SINRs, and CDF of effective SINR

variations. Then, using such statistical results of effective SINRs, an advanced congestion

control algorithm is proposed to improve TCP performance in 5G K-SimNet.


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Figure 4.1-16: 5G K-SimSys to K-SimNet interworking method

In our research, the congestion control algorithm based on 5G K-SimSys to K-SimNet

interworking is developed to enhance the end-to-end throughput performance of TCP

NewReno. The detailed interworking procedure is as follows:

- Step 1: Set the simulation scenario and parameters in 5G K-SimSys.

- Step 2: Collect effective SINR values from the variable “MS[msID]->scheduling->

downlinkESINRdB” in the main function of 5G K-SimSys during a given simulation

time, where msID denotes the user ID.

- Step 3: Calculate the statistics of the collected effective SINR values such as mean,

variance, and CDF, as shown in Figures 4.1-2 ~ 4.1-15.

- Step 4: Find certain percentiles of effective SINR using the CDF corresponding to

given mean and variance of effective SINR.

- Step 5: Calculate the user-specific congestion window sizes using the following scaled

Shannon capacity based on the certain percentile of effective SINR.

𝑆𝑝 = 𝑊 × log 1 + 10 / × 𝐹/8 ,

where 𝑆𝑝 denotes the packet size in bytes in TCP layer, 𝑊 is the system bandwidth,


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𝑆𝐼𝑁𝑅𝑒𝑓𝑓 represents the certain percentile of effective SINR, and 𝐹 is the scaling

factor to map Shannon capacity to TCP packet size.

- Step 6: Set the simulation scenario and parameters in 5G K-SimNet that are the same

as in 5G K-SimSys.

- Step 7: Apply the user-specific congestion window sizes to the congestion control

algorithm (i.e., slow start algorithm and congestion avoidance algorithm) of TCP

NewReno in 5G K-SimNet.

4.2. Performance Evaluation Using OPNET

Figure 4.2-1 shows the overview of OPNET modeler 17.5.A used for performance

evaluation in our research. Also, Table 4.2-1 shows OPNET specifications.

Figure 4.2-1: OPNET Modeler Overview


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Table 4.2-1: OPNET Modeler Specifications

Figure 4.2-2: Network simulation Interworking methodology based on 5G K-SimSys and OPNET

If channel capacity calculated by the effective SINR values obtained from 5G K-SimSys is

less than the congestion window (CWND) size, the source (or server) does not transmit

packets to the destination (or client). Otherwise, the source transmits its packets to the

• Total simulation time: 15s• # of users: 57

Step 2. Load the effective SINR values of 57 users by 5G K-SimSys in OPNET

Step 3. Find the time intervals that packet errors occur for each user based on SINR threshold and save the information for these intervals to new array.

Step 4. Randomly choose a representative user and AP drops downlink segments in accordance with the information of packet errors occurrence of the chosen user.

Step 5. Obtain the results of TCP congestion window size and TCP throughput when packet error doesnot occur and when packet errors occur according to the information of packet errors occurrence.

• TCP NewReno• Performance metric: effective SINR

Step 6. Analyze the end-to-end performance results considering the patterns of packet errors occurrence against the variation in congestion window size of TCP NewReno

Step 1. Find effective SINR values from “MS[msID]->scheduling->downlinkESINRdB” in main function of 5G K-SimSys and output the results to a file.

Find the main factors (maximum SINR

attenuation size, SINR attenuation frequency, …) via the statistical analysis of effective

SINR results and usethese factors to determine the

congestion window size

Specification

Company OPNET Technologies (Copyright © 2013)

*In October 2012, OPNET became part of Riverbed.

Product OPNET Modeler

*recently referred to as Riverbed Modeler

Version 17.5.A PL6 (Build 12988 64-bit)

Operating System Windows

Programming language C language

File size 5.47 GB


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destination. It reflects the impact of packet errors in a wireless network environment. Table

4.2-2 shows OPNET simulation parameters. Herein, the server transmits the packets every

5ms to the client. The size of each packet is 1500 bytes and the total number of packets is

3000. Also, Figure 4.2-3 shows the node deployment in our OPNET simulation scenario.

Table 4.2-2: OPNET Simulation Parameters

Attribute Value

Initialization time (sec) 1

Request Count 3000

Inter-request Time (sec) 0.005

Request Packet Size (bytes) 1500

Figure 4.2-3: Node Deployment in OPNET Simulation Scenario

Table 4.2-3 shows the pseudo code of TCP NewReno in OPNET. The performance results


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for TCP NewReno with respect to TCP throughput and congestion window size can be

obtained by using the below pseudo code of TCP NewReno.

Table 4.2-3: Pseudo Code of TCP NewReno

Slow start Algorithm:

Initial : CWND = 1;

For (each packet ACKed)

CWND += MSS;

Until (congestion event or CWND>ssthresh)

Congestion avoidance Algorithm:

/* slow start is over and CWND>ssthesh */

Every ACK:

CWND += MSS * (MSS/CWND) ;

Until (Timeout or 3 duplicate ACKs)

Fast Retransmit Algorithm:

/* After receiving 3 duplicate ACKs */

ssthersh = max (FlightSize / 2 ,2 * MSS);

Record the highest sequence number transmitted in variable “recover”

Retransmit lost packet;

CWND = ssthresh + 3*MSS

Invoke Fast Recovery algorithm

Fast Recovery Algorithm:

/* After fast retransmit ; do not enter slow start */

After receiving an ACK

/* recover > ACK number */

If partial ACK;

Stay fast recovery;

Retransmit next lost packet; (one packet per RTT)

CWND +=MSS

/* recover ≤ ACK number */


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If full ACK

CWND = min(ssthresh, max(FlightSize, MSS) +MSS) or ssthresh

Exit fast recovery;

Invoke congestion avoidance Algorithm;

When Timeout occurs

ssthresh = CWND / 2;

CWND = 1;

Invoke slow start algorithm

Slow start threshold (ssthresh) decision

ssthresh is the maximum congestion window size (CWND) for the slow start algorithm in

TCP NewReno. Here, the CWND size exponentially increases until to reach this ssthresh

value. Also, the CWND size linearly increases over ssthresh according to the congestion

avoidance algorithm. Herein, ssthresh can be calculated by 3.3th, 10th, and 20th percentile

effective SINRs obtained from 5G K-SimSys. In addition, we compare the performance results

with respect to the congestion window size and the TCP throughput to conventional TCP

NewReno when the drop rate in server is 10%.

Effective SINR values of user 4 and 9 are utilized for performance analysis among total 57

users in 5G K-SimSys. As mentioned before, 3.3th, 10th, and 20th percentile effective SINR

values of users 4 and 9 are used to calculated ssthresh. The 3.3th, 10th, and 20th percentile

effective SINRs of users 4 and 9 are as follows.

- User 4: 1dB (3.3th percentile of effective SINR), 2.75dB (10th percentile of effective SINR),

5.5dB (20th percentile of effective SINR)

- User 9: 1dB (1.75th percentile of effective SINR), 4.5dB (10th percentile of effective SINR),


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8.75dB (20th percentile of effective SINR)

A dB scale slow start threshold can be calculated by

SlowStartThreshold = 𝑊 × log 1 + 10 / × 𝐹/8

where bandwidth W is 10MHz and scale factor F is 0.0012. In accordance with each

ssthresh value, we compare the performance results with respect to the congestion

window size and the average TCP throughput of the proposed algorithm to conventional

TCP NewReno.

User 4

Figure 4.2-4 shows the congestion window size according to ssthresh calculated by 3.3th,

10th, and 20th percentile effective SINR values of user 4.

Figure 4.2-4: Congestion window size of user 4


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Figure 4.2-5 is an enlarged view of the 3~5.5s and 4.3~4.8s intervals of Figure 4.2-4. As

shown in Figures 4.2-4 and 4.2-5, we can see that the congestion window size exponentially

increases until to reach ssthresh. That is, as ssthresh increases, the congestion window

grows faster. On the other hand, the higher ssthresh, the higher packet drops. Therefore,

this means there is a trade-off between congestion window size growth and packet drop

rate. In our research, we set the target drop rate as 10% considering the trade-off between

congestion window size growth and packet drop rate.

Figure 4.2-5: Enlarged view of congestion window size for user 4

Figure 4.2-6 shows point-to-point throughput results of user 4. This figure shows that the

higher ssthresh, the higher the point-to-point throughput.


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Figure 4.2-6: Point-to-point throughput of user 4

Table 4.2-4 shows the simulation results for packet drop rate (the number of packet drops

/ the number of total packets) and average throughput of user 4 according to the variation

in the effective SINR values. As shown in Table 4.2-4, the average throughput of our

interworking method is 6.1% higher than that of TCP NewReno when the target drop rate is

set to 10%.

Table 4.2-4: Packet drop rate and average throughput against effective SINR of user 4

Effective SINR (Nth percentile SINR

of user 4)

Packet drop rate (# of packet drops/ # of

total packets)

Average throughput (bits/sec)

Original data 3.27% (98/3000) 2,697,147

1dB (3.3%) 5.67% (170/3000) 2,760,292

2.75dB (10%) 9.53% (286/3000) 2,862,025

5.5dB (20%) 14.87% (446/3000) 3,002,347


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User 9

Figure 4.2-7 shows the congestion window size according to ssthresh calculated by 3.3th,

10th, and 20th percentile effective SINR values of user 9.

Figure 4.2-7: Congestion window size of user 9

Figure 4.2-8 is an enlarged view of the 3~6s and 3.8~4.8s intervals of Figure 4.2-7. As

shown in Figures 4.2-7 and 4.2-8, we can see that the congestion window size exponentially

increases until to reach ssthresh. That is, as ssthresh increases, the congestion window size

also rapidly increases. Otherwise, the higher ssthresh, the higher packet drops. Therefore,

this means there is a trade-off between congestion window size growth and packet drop

rate. In our research, we set the target drop rate as 10% considering the trade-off between


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congestion window size growth and packet drop rate.

Figure 4.2-8: Enlarged view of congestion window size of user 9

Figure 4.2-9 shows point-to-point throughput results of user 9. This figure shows that the

higher ssthresh, the higher the point-to-point throughput.

Figure 4.2-9: Point-to-point throughput of user 9


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Table 4.2-5 shows the simulation results for packet drop rate (the number of packet drops

/ the number of total packets) and average throughput of user 9 according to the variation

in the effective SINR values. As shown in Table 4.2-5, the average throughput of our

interworking method is 5.6% higher than that of TCP NewReno when the target drop rate is

set to 10%.

Table 4.2-5: Packet drop rate and average throughput against effective SINR of user 9

Effective SINR (Nth percentile SINR of

user 9)

Packet drop Rate

(# of packet drops/ # of total

packets)

Average

throughput

(bits/sec)

Original data 2.73% (82/3000) 2,683,115

1.75dB (3.3%) 4.93% (148/3000) 2,740,998

4.5dB (10%) 8.47% (254/3000) 2,833,961

8.75dB (20%) 15% (450/3000) 3,005,855


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5. Conclusions

In this research, we considered TCP issue in 5G mmWave link that inherently has an

attribute of high frequency band and causes frequent link disruptions and a large fluctuation

of bandwidth due to the change of LOS and NLOS. We first examined the previous wireless

TCP techniques to solve such TCP problems in the 5G mmWave environment, such as split

connection, link layer, end-to-end, congestion detection, state suspension, and response

postponement techniques. Moreover, the recent researches on multipath TCP, cross-layering

between TCP and MAC/PHY, and 4G-5G Interworking approaches were investigated. On the

basis on these TCP techniques, we presented a guideline for TCP-MAC/PHY cross-layering in

4G-5G interworking architecture. We proposed five network structures for TCP-MAC/PHY

cross-layering, such as single TCP, splitted TCP, multipath TCP, decoupled MP-TCP, and

coupled MP-TCP. By comparing these cross-layering structures, we provided a hybrid

approach for TCP-MAC/PHY cross-layering, which suitably applies cross-layering, splitted TCP,

multipath-TCP, and coupling techniques to the 4G-5G interworking architecture. In addition,

the basic operation procedure of this coupled MP-TCP structure was presented. These

structure and procedure can be effectively applied to solve the TCP problems in the 5G

mmWave environment.

In addition, we presented the interworking scenario between MAC/PHY-layer of SLS and

TCP-layer of NS to realize the SLS-NS interworking for TCP performance enhancement, and

proposed the interworking method using 5G K-SimSys and K-SimNet. The interworking

method was based on the statistical results of the instantaneous effective SINRs for each of

users obtained from 5G K-SimSys, where the statistical results of effective SINRs can include


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mean, variance, and CDF of effective SINRs. In this research, the interworking method was

applied to the slow start threshold decision to improve the end-to-end throughput of TCP

NewReno in 5G K-SimNet, where the slow start threshold denotes the maximum congestion

window size for the slow start algorithm in TCP NewReno. For certain users, the slow start

threshold was calculated by 3.3th, 10th, and 20th percentile effective SINRs obtained from

5G K-SimSys. Then, through OPNET simulation, we compared the congestion window sizes

and the end-to-end TCP throughputs for the certain percentile effective SINRs, and also

compared them with the conventional TCP NewReno when the drop rate in server was 10%.

From the performance comparison, we showed the average throughput of our interworking

method can increase by 5~6% compared to the conventional TCP NewReno when the target

drop rate was set to 10%. The interworking method can be also applied to the other

congestion control algorithms (e.g., congestion avoidance, fast retransmit, and fast recovery)

for further performance enhancement.

5G K-SimSys to SimNet Interworking...

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