저작권법에따른이용자의권리는위의내용에의하여영향을받지않습니다.

(1)

저작자표시-비영리-변경금지 2.0 대한민국 이용자는 아래의 조건을 따르는 경우에 한하여 자유롭게 l 이 저작물을 복제, 배포, 전송, 전시, 공연 및 방송할 수 있습니다. 다음과 같은 조건을 따라야 합니다: l 귀하는, 이 저작물의 재이용이나 배포의 경우, 이 저작물에 적용된 이용허락조건 을 명확하게 나타내어야 합니다. l 저작권자로부터 별도의 허가를 받으면 이러한 조건들은 적용되지 않습니다. 저작권법에 따른 이용자의 권리는 위의 내용에 의하여 영향을 받지 않습니다. 이것은 이용허락규약(Legal Code)을 이해하기 쉽게 요약한 것입니다. Disclaimer 저작자표시. 귀하는 원저작자를 표시하여야 합니다. 비영리. 귀하는 이 저작물을 영리 목적으로 이용할 수 없습니다. 변경금지. 귀하는 이 저작물을 개작, 변형 또는 가공할 수 없습니다.

(2)

공

학

박

사

학위

논

문

PHY/MAC Layer Strategies for

High-Efficiency Dense WLANs

밀

집환

경 고

효

율

무선랜

을 위

한

물리

/

매

체

제

어

계

층

기

술

연

구

2020

년

8월

서

울

대

학

교

대

학

원

전

기

· 컴

퓨

터

공

학

부

손

영 욱

(3)

공

학

박

사

학위

논

문

PHY/MAC Layer Strategies for

High-Efficiency Dense WLANs

밀

집환

경 고

효

율

무선랜

을 위

한

물리

/

매

체

제

어

계

층

기

술

연

구

2020

년

8월

서

울

대

학

교

대

학

원

전

기

· 컴

퓨

터

공

학

부

손

영 욱

(4)

PHY/MAC Layer Strategies for

High-Efficiency Dense WLANs

지도

교

수

박

세

웅

이

논

문

을

공

학

박사

학위

논

문

으

로

제

출

함

2020년

8 월

서

울대학

교

대학원

전

기

· 컴

퓨

터

공

학

부

손

영 욱

손

영욱의

공

학

박사

학위

논

문

을 인

준

함

2019

년

12월

위

원

장

:

심

병

효

(

인

)

부

위

원

장

:

박

세

웅

(

인

)

위

원:

권

태

경

(

인

)

위

원:

주

창

희

(

인

)

위

원:

최

성

현

(

인

)

(5)

Abstract

Among lots of performance issues on IEEE 802.11 wireless local area networks (WLANs), also referred to as Wi-Fi, the top priority concern in recent years has been to achieve better user experience and higher efficiency in densely deployed, user-populated areas. In this context, IEEE 802.11ax standard has newly adopted ground-breaking PHY/MAC protocols as core features, including uplink multi-user transmis-sion (UL MU) and spatial reuse (SR) operation. These new technologies enable mul-tiple stations within a common cell or across neighboring cells to transmit simulta-neously at a time, for elevating the spectral efficiency and overall network capacity. However, since the reworld performance is highly dependent on specific built-in al-gorithms and implementation which stipulate actual device behaviors, the upcoming standard still holds plenty of practical issues regarding its real deployment.

In this dissertation, we consider the following three challenges to be addressed for desired operation of IEEE 802.11 WLANs: (i) Symbol timing synchronization for UL MU, (ii) understanding and exploitation of a CS anomaly named preamble-passing for promoting valid transmissions in high-density WLANs, and (iii) enabling viable simultaneous transmissions via SR protocol with intelligent operating strategies.

First, we spotlight the symbol timing synchronization problem for UL MU in IEEE 802.11ax WLANs specifically. While UL MU enables multiple stations to transmit si-multaneously to a common access point (AP), tight timing synchronization is required among transmitted signals for the receiver AP to correctly decode them, which is not fully addressed in the standard specification. Based on the observations and analysis, we present a novel receiver-side symbol timing synchronization mechanism with en-hanced PHY functionality to capture a desirable symbol timing, which accommodates asynchronously arriving signals and mitigates ISI and ICI.

(6)

behaviors, which makes neighboring devices blind to each other and transmit simulta-neously. Through experimental study, we reveal both sides of preamble-passing, which heavily affects the overall network performance. Based on the observations, we de-signREFRAIN, a standard-compliant PHY/MAC framework, to cope with and further exploit the anomaly for better spatial reuse. Our prototype using NI USRP and com-mercial devices shows the effectiveness of our approach, while extensive simulation results demonstrate thatREFRAINachieves up to 1.57×higher average throughput by promoting valid transmissions, without modifying 802.11 CS specification at all.

Finally, we investigate detailed operation of the SR protocol in IEEE 802.11ax, with relation to preamble-passing anomaly. Identifying both detrimental effects and potential for spatial reuse, we developAdOPT, a standard-compliant operating frame-work for the SR protocol. AdOPT enables only viable simultaneous transmissions opportunistically, by adjusting data rate at each transmission attempt. Our extensive simulation results verify that AdOPT brings significant performance gain over base-line 802.11 and other comparison schemes, up to 1.82×especially for the worst-case stations suffering from starvation and poor link conditions.

In summary, we propose a symbol timing synchronization algorithm for UL MU, and two frameworks for better spatial reuse, REFRAIN and AdOPT, each working with conventional CS mechanism and 802.11ax SR protocol. Through this research, we present practical operating strategies to achieve desirable real-world performance in high-density WLANs. The feasibility and performance of our approaches are vali-dated via various methodologies including system-level and link-level simulation, and prototype using commercial Wi-Fi devices and NI USRP software-defined radio.

keywords: Wi-Fi, 802.11, high-efficiency WLAN, high-density, multi-user transmission, symbol timing synchronization, carrier sensing, spatial reuse. student number: 2013-23121

(7)

4 AdOPT: Augmenting Valid Transmissions for Better Spatial Reuse in IEEE 802.11ax WLANs 88 4.1 Introduction . . . 88 4.2 Preliminaries . . . 91 4.2.1 OBSS PD SR Protocol . . . 91 4.2.2 Preamble-Passing . . . 91 4.3 Performance Diagnosis . . . 93 4.3.1 Methodology . . . 93 4.3.2 Results . . . 93 4.4 Proposed Scheme . . . 98 4.4.1 Design Philosophy . . . 98

4.4.2 Adjustive Use of OBSS PD-based Transmission (AdOPT) . . 99

4.4.3 Trial-and-Error Rate-Selective Transmission (TEST) . . . 100

4.5 Performance Evaluation . . . 102

(10)

5 Concluding Remarks 107 5.1 Research Contributions . . . 107 5.2 Future Work . . . 108

(11)

List of Tables

(12)

List of Figures

2.1 Innovative change of IEEE 802.11ax realizes multiple transmitters at a time. . . 9 2.2 Possible cases of receiver’s DFT window position over an OFDM

sym-bol: (a) Perfect synchronization, (b) ISI-free region, (c) involving ISI from the previous symbol, (d) involving ISI from the next symbol. . . 13 2.3 Effective SINR versus STOs (δ) under various ideal SNR levels,

es-timated by EVM [1] in a general SISO/MIMO-OFDM system with

NDFT= 64andNCP= 16. . . 16

2.4 IEEE 802.11 legacy PLCP preamble structure. . . 17 2.5 Description of the entire UL MU procedure and HE trigger-based (TB)

PPDU structure for OFDMA / MU-MIMO . . . 21 2.6 Effects of asynchronous arrival timings among UL MU frames: 1)

Global ISI-free region for DFT window, and 2) difficulty in processing legacy preamble fields. . . 24

(13)

2.7 Comparison of the conventional correlation metrics between SU and 9-user UL MU: Auto-correlation in (2.13 LaTeX Error: Can be used only in preambleSee the LaTeX manual or LaTeX Companion for explana-tion.Your command was ignored.Type I ¡command¿ ¡return¿ to replace it with another command,or ¡return¿ to continue without it.2.13) with

Ka = 16 &d = 16 for L-STF, and cross-correlation in (2.14

La-TeX Error: Can be used only in preambleSee the LaLa-TeX manual or LaTeX Companion for explanation.Your command was ignored.Type I ¡command¿ ¡return¿ to replace it with another command,or ¡return¿ to continue without it.2.14) withKc= 64for L-LTF (time samples in

20 MHz sampling rate). . . 26 2.8 Two exemplary UL MU scenarios within 20 MHz: OFDMA alone with

9 participants assigned (upper) and OFDMA+MU-MIMO with 8 par-ticipants assigned (lower). . . 31 2.9 UL MU data delivery ratio versusδ∗for different MCSs and maximum

deviation of arrival timings,θmax. . . 32

2.10 Combined UL MU signal in the worst scenario ofθmax= 1.3µs, and

corresponding values ofa(n)in (2.13 LaTeX Error: Can be used only in preambleSee the LaTeX manual or LaTeX Companion for explana-tion.Your command was ignored.Type I ¡command¿ ¡return¿ to replace it with another command,or ¡return¿ to continue without it.2.13) with

Ka = 64&d= 64. 3.2µs-repetition remains over the intersection of

L-LTFs, and accordingly the auto-correlation can roughly detect the L-LTF/L-SIG boundary of the earliest UL MU frame. . . 34

(14)

2.11 Performance of the state-of-the-art synchronization algorithms in lit-erature when applied to 9-user UL MU in 20 MHz, where each UL MU frame has an independent random arrival timing following uni-form distribution withθmax= 16 (0.8µs)and26 (1.3µs), assuming

TGn “D” NLOS channel (L = 9) and that frequency and power

pre-correction are ideally performed at participating STAs. . . 39

2.12 Performance of the proposed time-domain synchronization in time do-main applied to 9-user UL MU, where frame arrival timings are ran-domly distributed with θmax = 16 (left), and θmax = 26 (right), assuming TGn “D” NLOS channel (L = 9) and that frequency and power pre-correction are ideally performed at participating STAs. . . 40

2.13 Global ISI-free ratio versusθmaxfor three different CP lengths. Time-domain synchronization used alone (TS) and in combination with fine calibration (TS+FC) for two different UL MU scenarios are compared with Wang’s method proposed in [2]. . . 41

2.14 Mean of|δ∗|for two different CP sizes when there cannot be global ISI-free region forL∗−1> NCP. . . 43

2.15 Average MUDR versusθmax, with SNR set to fixed levels where per-fectly synchronous UL MU achieves ∼90% MUDR. Time-domain synchronization used alone (TS) and in combination with fine calibra-tion (TS+FC) are compared with Wang’s method [2], for each case of using two short CPs, 0.8µs CP (16 samples in 20 MHz) and 1.6µs CP (32 samples in 20 MHz). . . 44

3.1 Preliminary measurement (using a constant data rate of 65 Mb/s, with RTS/CTS turned off). . . 48

3.2 Wi-Fi physical carrier sensing mechanisms. . . 49

3.3 Preamble-passing—an anomaly of Wi-Fi CS. . . 50

(15)

3.5 Representative scenarios for preamble-passing in dense Wi-Fi networks. 53 3.6 Experimental study on the link performance of STA→AP, depending

on CS interaction between STA and neighbor. . . 58

3.7 Measurements in a two-BSS scenario. . . 60

3.8 Measurements in a three-BSS scenario, revealing the impact of preamble-passing upon RTS/CTS. . . 62

3.9 Preamble-passing upon RTS/CTS. (HN1 and HN2 can sense each other.) 63 3.10 Revised RX performance model to reflect the actual impact of cor-rupted CSI, leading to high A-MPDU FER under preamble-passing. . 66

3.11 Simulation results forIndoor Small BSSs, according to the deployment size, user population, and traffic condition. . . 68

3.12 With different CS configurations (RTS/CTS off). . . 70

3.13 REFRAIN PHY: PPI detection. . . 72

3.14 REFRAIN MAC: Null frame handshake. . . 73

3.15 Overall operation flow ofREFRAINsystem design. . . 75

3.16 Operational structure ofREFRAIN. . . 78

3.17 Evaluation of PPI detection performance, using the programmable SDR platform. . . 79

3.18 False detection on heterogeneous traffic. . . 81

3.19 PoC evaluation results in two-BSS scenario. . . 82

3.20 PoC evaluation results in three-BSS scenario. . . 83

3.21 Simulation-based evaluation forIndoor Small BSSsscenario with 19-BSS deployment in Figure 3.11 LaTeX Error: Can be used only in preambleSee the LaTeX manual or LaTeX Companion for explana-tion.Your command was ignored.Type I ¡command¿ ¡return¿ to replace it with another command,or ¡return¿ to continue without it.3.11(a). . . 86

4.1 Conventional exposed node problem in WLANs. . . 89

(16)

4.3 Simple Two-BSS topology . . . 93

4.4 Performance diagnosis ofBaseline OBSS PDcompared with baseline 802.11. . . 94

4.5 Preamble-passing induced by OBSS PD-enabled SR TX. . . 95

4.6 Performance ofREFRAINin combination withBaseline OBSS PD. . 97

4.7 Operation ofAdOPTfor OBSS transmission duration. . . 99

4.8 Operation ofTESTapplied for PPTXs. . . 101

4.9 Performance ofAdOPTin the two-BSS topology. . . 103

4.10 Hexagonal layout of 19-BSS topology. . . 104

(17)

Chapter 1 Introduction

1.1 Motivation

In recent years, with the explosive growth of mobile traffic volume, IEEE 802.11 wire-less local area network (WLAN), also referred to as Wi-Fi, has become indispensable in our daily lives. Such proliferation of Wi-Fi also has led to dense deployment of public hotspots. According to a research from industry, it is expected that there will be globally 549 million public Wi-Fi hotspots by 2022, a four-fold increase from 124 million in 2017, and they will carry 51% of total IP traffic, amounting to nearly 200 exabytes per month [3]. To keep pace with this increasing demand for mobile traffic and wireless connectivity, IEEE 802.11 standard is now preparing for another new deal as it has always been in its history.

IEEE 802.11n/ac, as representative amendments in the last decade, have achieved data rates up to 600 Mb/s and 6.9 Gb/s, respectively, by exploiting many state-of-the-art technologies in their physical layer (PHY) such as high-order modulation and cod-ing scheme (MCS), channel bondcod-ing, and multiple input multiple output (MIMO) [4, 5]. After the completion of IEEE 802.11ac, consideration for user experience and high efficiency in dense deployment scenarios has boosted the need for another evolutionary advance. Accordingly, a new task group was launched to develop the next amendment

(18)

named IEEE 802.11ax, claiming for high efficiency (HE) WLAN.

The goal of IEEE 802.11ax is to elevate the overall efficiency of conventional WLAN system, thereby bringing better performance in terms of user experience. To this end, the new standard specifically intends to resolve the sufferings under dense environments, all of which fundamentally stem from the intrinsic nature of 802.11 system design, that is, its PHY based on orthogonal frequency-division multiplexing (OFDM), and medium access control layer (MAC) based on carrier-sensing multi-ple access with collision avoidance (CSMA/CA). First, the OFDM-based PHY allows only a single wireless station to access the channel at a time, which leads to highly inefficient resource sharing among users, especially in user-populated areas. Second, under the PHY constraint, IEEE 802.11 relies on the CSMA/CA-based MAC coor-dination. That is, a station obtains the channel access opportunity only if there is no detected signal at the transmitter’s perspective, instead of the receiver that could be an actual victim of possible interference signal. Eventually, with this decentralized and distributed operating mechanism, 802.11 stations often suffer from starvation, con-tention collision, hidden and exposed node problem, etc., under dense environments. In this regard, the emerging IEEE 802.11ax presents two fundamental breakthrough to address these inherent limitations of WLANs—uplink multi-user transmission (UL MU), and spatial reuse (SR) protocol.

With newly defined PHY specification, i.e., orthogonal frequency-division multi-ple access (OFDMA) and spatial-division multimulti-plexing (SDM), UL MU allows more than one station to access the channel at a time. In other words, multiple stations can transmit their own traffic simultaneously to a common target access point (AP) within BSS. In the meantime, SR protocol refines the conventional carrier-sensing (CS) mech-anism so that its receive sensitivity, also called CS threshold, can be conditionally adjusted for some external signals from overlapping BSS (OBSS). Accordingly, the neighboring stations under exposed node problem, who do not interfere with each other but are prohibited to access the channel at a time, are allowed to transmit

(19)

simul-taneously within their own respective BSSs. In summary, the both core technologies in 802.11ax WLANs enable intra-BSS and inter-BSS simultaneous transmissions, re-spectively, to elevate the channel utilization and spectral efficiency.

We note that, even though the upcoming IEEE 802.11ax standard specifies those new ground-breaking features, their real-world performance will be highly dependent on specific algorithms and chipset implementation, which still remain as challenging problems for academia and device vendors. Concretely, UL MU requires tight syn-chronization of timing, frequency and power among the participating stations, which cannot be easily achieved considering the distributed nature of WLANs. In this situa-tion, the individual link performance of UL MU could benefit from better implemen-tation of the receiver-side synchronization modules, i.e., by refining the conventional algorithms to be more resilient to UL MU, leading to better traffic delivery under the same asynchronous user characteristics. Likewise, SR protocol needs detailed oper-ating strategies regarding how to control the receive sensitivity for achieving better spatial reuse performance. Stations should make a careful decision on whether it can spatially reuse the wireless medium under the ongoing interference from OBSS, since the abuse of the protocol could simply result in severe hidden node interference and starvation. Understandably, to tackle this trade-off problem, it is pre-required to have a full understanding of the conventional 802.11 CS mechanisms, from the perspective of actual Wi-Fi device behaviors and their interactive dynamics in high-density networks.

1.2 Main Contributions

1.2.1 Symbol Timing Synchronization for Uplink Multi-User

Transmission in IEEE 802.11ax WLANs

We spotlight two aspects of symbol timing synchronization problem for UL MU in IEEE 802.11ax WLAN specifically: 1) The impact of symbol timing errors on data decoding performance for UL MU with OFDMA and MU-MIMO and 2) malfunction

(20)

of conventional 802.11 synchronization methods, which fail to find proper symbol tim-ing when receivtim-ing asynchronously superposed preambles. Based on the observations and analysis from these two aspects, we present a new receiver-side symbol timing synchronization mechanism with enhanced PHY functionality to capture a desirable symbol timing, which accommodates asynchronously arriving signals and mitigates inter-symbol interference (ISI) and inter-carrier interference (ICI).

Our key contributions are summarized as follows.

• We extend the previous analysis about the symbol timing misalignment in general OFDM systems to 802.11-specific UL MU scenarios considering OFDMA/MU-MIMO transmissions.

• Understanding the entire preamble processing flow in the conventional 802.11 re-ceiver implementation, we formulate the challenges of finding a proper symbol timing for asynchronous UL MU.

• We present a novel two-step synchronization method, which can find the best tol-erable symbol timing within possible sample ranges, by utilizing both time and frequency domain information.

• Extensive simulation-based evaluation shows that our proposed method achieves near-optimal performance under given CP sizes and signal arrival timings.

To the best of our knowledge, this is the first work that identifies and tackles the symbol timing synchronization problem for standard-compliant UL MU in IEEE 802.11ax WLANs.

1.2.2 REFRAIN: Promoting Valid Transmissions in High-Density

Modern Wi-Fi Networks

In this chapter, we shed light on a kind of anomaly in 802.11 carrier sensing (CS), named preamble passing, which makes neighboring Wi-Fi devices behave as if they

(21)

are hidden nodes.We look into the causes and effects of preamble-passing, including its incidence and importance in high-density WLANs. To this end, we conduct not only extensive measurements in real testbed, but also rigorous simulation-based analysis, incorporating a realistic PHY model firstly developed in this research to reflect the impact of corrupted preamble reception. Based on empirical verification and analysis of the problem, we designREFRAIN, a standard-compliant PHY/MAC framework, to cope with and further exploit the anomaly for better spatial reuse. Finally, we verify the feasibility and effectiveness of our approach through proof-of-concept (PoC) experi-ments using NI USRP platform and commercial Wi-Fi devices, followed by extensive simulation-based evaluation for large-scale deployments.

To the best of our knowledge, this is the first work that spotlights the CS anomaly in high-density Wi-Fi networks, and tackles the spatial reuse issue with the awareness of such anomaly. Most remarkably, REFRAIN elevates the overall network capacity via better spatial reuse, even without modifying conventional 802.11 CS.

1.2.3 AdOPT: Augmenting Valid Transmissions for Better

Spatial Reuse in IEEE 802.11ax WLANs

In this chapter, we firstly investigate possible problem situations caused by 802.11ax overlapping BSS (OBSS) preamble detection (PD) spatial reuse (SR) protocol, which enables each 802.11 station to control its receive sensitivity, i.e., to use adaptive CS threshold for attempting transmissions more aggressively. With the understanding of preamble-passing anomaly, we dissect the performance of OBSS PD SR protocol, and identify both its detrimental effects and potential for spatial reuse under certain topological circumstances. Based on the observation, we developAdOPT, a standard-compliant OBSS PD operating framework, which aims to achieve better spatial reuse and fairness by capturing only viable transmission opportunities at user station side. Through extensive simulation-based evaluation, we show thatAdOPT brings signifi-cant performance gain over baseline 802.11 and other comparison schemes, especially,

(22)

for worst-case stations suffering from starvation and poor link conditions. Our key contributions are summarized as follows.

• We extend the previous analysis about preamble-passing to 802.11ax WLANs, where individual stations adjust their receive sensitivity by applying OBSS PD SR protocol.

• Revealing merits and demerits of the SR protocol, we developAdOPT, a standard-compliant OBSS PD operating framework, to achieve spatial reuse and better fair-ness.

• Extensive simulation-based evaluation demonstrates thatAdOPT achieves signif-icant performance gain and better fairness, by capturing only viable spatial reuse opportunities along with the proper data rate selection for each simultaneous trans-mission.

To the best of our knowledge, this is the first work that identifies the relation be-tween preamble-passing and the use of OBSS PD, also diagnosing their combined effects. Most notably,AdOPTprovides a practical way of employing OBSS PD proto-col, with an emphasis on the importance of proper data rate selection in elevating the network efficiency.

1.3 Organization of the Dissertation

The rest of the dissertation is organized as follows.

Chapter 2 presents a new symbol timing synchronization mechanism with en-hanced functionality for capturing a desirable symbol timing in UL MU. Preliminary knowledge about symbol timing synchronization is introduced in terms of general MIMO-OFDM systems and IEEE 802.11 WLAN. UL MU specification and newly arising challenges for symbol timing synchronization are elaborated. Our new

(23)

synchro-nization mechanism for UL MU is presented with extensive performance evaluation results.

In Chapter 3, we presentREFRAIN, standard-compliant PHY/MAC framework, to cope with and further exploit the CS anomaly for better spatial reuse. We first dis-sect the cause and effect of preamble-passing, including its incidence and importance in high-density networks. Our proposed framework,REFRAIN, is presented with the empirical verification and analysis of the problem We verify the feasibility and effec-tiveness of our approach through proof-of-concept (PoC) experiments and extensive simulation-based evaluation.

Chapter4presentsAdOPT, a standard-compliant OBSS PD operating framework, to achieve better spatial reuse and fairness with the understanding of preamble-passing phenomenon. We first discuss the performance of baseline OBSS PD, and both its detrimental effects and potential for better spatial reuse under certain circumstances. Then our OBSS PD operating strategies are presented, which involves intelligent judge-ment on the application of OBSS PD, proper data rate selection for each transmission attempt, SR prohibition for better fairness, etc., all functionalities of which are in-tended for achieving better spatial reuse at user station side. We comparatively evaluate the performance ofAdOPTvia extensive ns-3 simulation.

Finally, Chapter5 concludes the dissertation with the summary of contributions and discussion on the future work.

(24)

Chapter 2 Symbol Timing Synchronization for Uplink Multi-User

Transmission in IEEE 802.11ax WLANs

2.1 Introduction

Most highlighted as a key driver in upcoming IEEE 802.11ax is the adoption of uplink multi-user transmission (UL MU), which allows multiple stations (STAs) to concur-rently transmit to a common receiver, i.e., access point (AP). As illustrated in Fig. 2.1, it is absolutely a new paradigm contrary to single-user transmission (SU) in previous WLANs.

There are two enablers for UL MU: orthogonal frequency-division multiple access (OFDMA) and multi-user MIMO (MU-MIMO). Theoretically, both technologies al-low interference-free concurrent transmissions in a perfectly synchronous network via frequency-division and spatial-division channel sharing among STAs. However, this is not the case usually in practical WLANs owing to the intrinsically distributed nature of 802.11 in that STAs are not tightly synchronized and are not strictly controlled as in cellular systems. In reality, multiple PLCP protocol data units (PPDUs)1 transmit-ted in a UL MU can arrive at an AP with asynchronous timings. Although the timing

1

PHY Layer Convergence Protocol (PLCP) is the upper sublayer of 802.11 PHY, and PPDU is a transmission unit of 802.11 PHY.

(25)

STA1 STA2 STA3 AP TX DEFER DEFER

(a) SU in conventional WLANs.

STA1 STA2 STA3 AP TX TX TX Triggered Triggered Triggered (b) UL MU in 802.11ax WLAN.

Figure 2.1: Innovative change of IEEE 802.11ax realizes multiple transmitters at a time.

misalignment only reduces to hundreds of nanoseconds thanks to tight hardware re-quirement of IEEE 802.11ax specification, we note that even such small misalignment could be fatal to the entire performance. Especially, since the conventional 802.11 re-ceivers have not been originally designed for detecting asynchronous multiple signals, their synchronization modules are likely to be disrupted at the initial stage of frame reception in UL MU scenarios. Then the resulting timing errors cause inter-symbol interference (ISI) and inter-carrier interference (ICI), leading to severe aggravation of data decoding performance.

There have been several studies addressing the problem of symbol timing syn-chronization and possible deleterious interference in asynchronous multi-user sys-tems. [6–8] established the system model and timing requirements of asynchronous uplink OFDMA. They also provided comprehensive analysis and verification results for the interferences induced from synchronization errors among users, even though they focus only on OFDMA system with single spatial stream enabled. Meanwhile, it is identified in [9] that sufficiently long guard interval between adjacent symbols, namely cyclic prefix (CP) in OFDM, can be a buffer to accommodate the synchroniza-tion errors. Exploiting longer CP durasynchroniza-tion, however, sacrifices transmission efficiency leading to low network throughput. Other researches in [10, 11] present user-side ap-proaches to resolve the asynchronous timings, that is, open-loop or closed-loop timing

(26)

advance, which are not applicable at all to WLANs. Recent work in [12] illuminates UL MU-MIMO in asynchronous WLANs. It presents a new PHY design, as a sub-stitute for the conventional minimum mean square error (MMSE) / zero-forcing (ZF) receivers, to decode the multiple misaligned streams. However, the extremely asyn-chronous scenarios assumed in this work are where STAs are not compliant with the timing requirement in 802.11ax standard specification. Thus it focuses on separating the concurrent streams using spatial filters, showing its feasibility for only up to four-stream MU-MIMO transmissions.

In this chapter, we spotlight the two aspects of symbol timing synchronization problem for UL MU in IEEE 802.11ax WLAN specifically: 1) The impact of symbol timing errors on data decoding performance of OFDMA/MU-MIMO with the exis-tence of asynchronous STAs and 2) malfunction of conventional 802.11 synchroniza-tion methods which fail to find proper symbol timing when receiving asynchronously superposed preambles. Based on the observations and analysis from those two aspects, we present a new symbol timing synchronization mechanism with enhanced function-ality for capturing a desirable symbol timing, to accommodate asynchronously arriving PPDUs and mitigate ISI and ICI. To the best of our knowledge, this is the first work that identifies the symbol timing synchronization problem for standard-compliant UL MU in IEEE 802.11ax WLAN, and presents a solution to support the conventional MMSE/ZF receivers.

Note that all the analysis and evaluation throughout this chapter have been carried by utilizing our elaborate 11ax link-level simulator, where all the features of IEEE 802.11ax PHY and lower medium access control (MAC) protocols are embedded by using IT++ libraries [13], at baseband signal processing level. Those features include new OFDM numerology of 802.11ax represented by symbol duration of 12.8µs, new HE PPDU formats, and all sorts of transmission and reception (TX/RX) processing blocks for supporting OFDMA/MU-MIMO with MMSE receiver. For a UL MU im-plemented in our simulator, AP receives concurrent transmissions via OFDMA or

(27)

OFDMA combined with MU-MIMO from up to 9 STAs, multiplexed within 20 MHz baseband, which is the smallest unit of operating bandwidth.

The rest of this chapter is organized as follows. We introduce preliminary knowl-edge about symbol timing synchronization in terms of general MIMO-OFDM systems and IEEE 802.11 WLAN in Section 2.2. In Section 2.3, we elaborate UL MU specifi-cation and newly arising challenges for symbol timing synchronization. Our new syn-chronization mechanism for UL MU is presented in Section 2.4, and its performance is evaluated in Section 2.5. Finally, Section 2.6 concludes the chapter.

2.2 Preliminaries

2.2.1 Primer on OFDM Symbol Timing Synchronization

Case classification

We consider aN×NMIMO-OFDM system designed with discrete Fourier transform (DFT) size ofNDFTand cyclic prefix (CP) ofNCPsamples prepended to every

sym-bol. Let Xm(i)(k) represent the modulated constellation on thek-th subcarrier of the

m-th symbol for thei-th spatial stream. Then the complex baseband samples of the symbol are constructed as

x(_mi)(n) = √ 1 NDFT NDFT−1 X k=0 X_m(i)(k)ej2πkn/NDFT_, for −NCP≤n≤NDFT−1, (2.1)

and the consequenti-th TX stream is written as

x(i)(n) =X

m

x(_mi) n−m(NDFT+NCP)

(28)

The received baseband signal for thej-th RX chain can be written by y(j)(n) =X i hji(n)∗x(i)(n) +z(j)(n) =X i ( X m L−1 X l=0 hji(l)·x(mi) n−l−m(NDFT+NCP) ) +z(j)(n), (2.3)

where hji(n) is channel impulse response (CIR) between thei-th TX chain and the

j-th RX chain, and z(j)(n) represents additive white Gaussian noise (AWGN). The total number of delay taps comprising the CIR,L, is supposed to be smaller thanNCP

in a well designed OFDM system.

Four different cases of the receiver’s DFT window over an OFDM symbol are illustrated in Fig. 2.2. We refer to the number of misaligned samples relative to the ideal symbol start as symbol timing offset (STO),δ, with the following relation:

δ,nˆDFT−nsym, (2.4)

wherensymdenotes the sample index at which the transmitted OFDM symbol actually

starts, and ˆnDFT is its estimate at the receiver where the DFT window starts to be

applied.

In Fig. 2.2, case (a) describes the perfect symbol timing synchronization, where receiver’s DFT window is positioned at the exact range of the symbol so thatδequals zero. Assuming no frequency offset, the DFT output on thek-th subcarrier is repre-sented as

Y_m(j)(k) =X

i

Hji(k)Xm(i)(k) +Zm(j)(k), (2.5)

whereHji(k) denotes the channel gain of subcarrierkcorresponding to the DFT of

hji. We consider employing an MMSE receiver with the coefficient matrixW(k) ∈

CN×N given by

W(k) =HH(k)H(k) +N0I −1

(29)

(m–1)-th

symbol CP m-th data symbol

(m+1)-th symbol

(a) ࢾ=૙(DFT window at exact position)

symbol ܰେ୔ ܰୈ୊୘ ܮ െ1 Multi-path components from (m-1)-th symbol (m–1)-th

(m+1)-th symbol symbol

(b)െࡺ_۱۾+ ࡸ െ ૚ ൑ ࢾ<૙(ISI-free region)

(m–1)-th

(c) ࢾ<െࡺ_࡯ࡼ+ ࡸ െ ૚ (Involving ISI from previous symbol)

(m–1)-th

(d)૙<ࢾ(Involving ISI from next symbol)

Figure 2.2: Possible cases of receiver’s DFT window position over an OFDM symbol: (a) Perfect synchronization, (b) ISI-free region, (c) involving ISI from the previous symbol, (d) involving ISI from the next symbol.

(30)

whereH(k)∈CN×Nis the channel coefficient matrix ideally assumed withH(k) _ji=

Hji(k), and the superscriptHof a matrix denotes Hermitian transpose of the matrix.

Then, the recovered symbol for thei-th stream can be achieved by

˜ X_m(i)(k) =X j Wij(k)Ym(j)(k) =    X j Wij(k)Hji(k)    X_m(i)(k) +X s6=i I_MMSE(s) _,_i(k)X_m(s)(k) +X j Wij(k)Zm(j)(k), (2.7) whereWij(k) = W(k) _ij andI_MMSE(s) _,_i(k) =X j Wij(k)Hjs(k).

For case (b), DFT window starts somewhere within a specific range calledISI-free region. ISI-free region is the range which is not reached by delayed components of the previous symbol and is defined as

−NCP+ (L−1)≤δ <0. (2.8)

In terms of the DFT output, cyclic shift property of the CP samples results in linear phase offsets across the subcarriers:

Y_m(j)(k) =ej2πkδ/NDFTX

i

Hji(k)Xm(i)(k) +Zm(j)(k). (2.9)

As these phase offsets are not distinguished from the channel gains, the coefficient matrixW(k)naturally compensates them making no difference from (2.7).

Finally, cases (c) and (d) are the worst cases where DFT window starts outside the ISI-free region, that is,δ <−NCP+ (L−1)or0< δ. In this case, the DFT input does

not cover the desiredm-th symbol entirely and rather contains irrelevant samples from an adjacent symbol. Then the consequent DFT output is corrupted by ISI in addition to symbol distortion from the collapsed orthogonality. Referring to [14], the resulting

(31)

Ym(j)(k)is given by

Y_m(j)(k) =α(δ)ej2πkδ/NDFTX

i

Hji(k)Xm(i)(k)

+I_m(j)(k, δ) +Z_m(j)(k), (2.10)

whereα(δ)represents the attenuation factor due to the less number of useful samples andIm(j)(k, δ)is an additive interference term accounting for ISI and ICI, modeled as

a zero-mean random variable with varianceσ_I2(k, δ). With the same MMSE receiver using ideal coefficient matrixW(k), the recovered symbol for thei-th stream can be obtained by ˜ X_m(i)(k) =X j Wij(k)Ym(j)(k) =α(δ)ej2πkδ/NDFT    X j Wij(k)Hji(k)    X_m(i)(k) +α(δ)ej2πkδ/NDFTX s6=i I_MMSE(s) _,_i(k)X_m(s)(k) +X j Wij(k) I_m(j)(k, δ) +Z_m(j)(k) . (2.11) SINR degradation

As a consequence of the analysis above, average signal-to-interference-plus-noise-ratio (SINR) for thei-th spatial stream on subcarrierkis given depending onδas2

SINR(_ki)(δ) = α2(δ) P jWij(k)Hji(k) 2 P_T(i) α2₍_δ₎P s6=i I (s) MMSE,i(k) 2 P_T(s)+σ2_I(k, δ) +N0 Pj W_ij(k) 2, (2.12)

whereP_T(i)is the average power of thei-th TX stream, on which additive interference power, σ_I2(k, δ), also depends. For −NCP+ (L−1) ≤ δ ≤ 0, power attenuation

2

Note that (2.12) indicates the upper limit of average SINR degraded under the impact of STO, since it has been derived assuming the ideal channel coefficients. In practice, STOs and thermal noises could further induce channel imperfection at the receiver, thus spoiling the decoding process.

(32)

−20 −15 −10 −5 0 5 10 15 20 0 10 20 30 δ_{(in samples)} SINR (dB) SNR (ideal) 35 dB SNR (ideal) 25 dB SNR (ideal) 15 dB SNR (ideal) 5 dB

(a) AWGN (no delay spread), SISO.

(b) IEEE TGn “D” NLOS (L= 9), SISO.

(c) IEEE TGn “D” NLOS (L= 9), 2×2 MIMO.

Figure 2.3: Effective SINR versus STOs (δ) under various ideal SNR levels, estimated by EVM [1] in a general SISO/MIMO-OFDM system withNDFT = 64andNCP =

16.

α2(δ)and additive interferenceσ_I2(k, δ)attributed to the symbol timing offset reduce to unity and zero, respectively.

To quantitatively figure out the impact ofδ on SINR performance, we calculate error vector magnitude (EVM) in the I-Q plane between the ideal TX symbol and the recovered symbol at the MMSE receiver, for differentδvalues. Referring that the effective SINR can be approximated as the reciprocal of the squared EVM [1], Fig. 2.3 plots the effective SINR versusδ under some ideal SNR levels (P_T(i)/N0), i.e., SNR

(33)

L-STF L-LTF L-SIG (V)HT-SIG (V)HT -STF (V)HT -LTFs VHT-SIG-B Data S1 S2 S3 S4 S5 S6 S7 S8 S9S10 CP L1 L2 CP SIGNAL CP ... 10 × 0.8ȝs 1.6ȝs + 2 × 3.2ȝs

Figure 2.4: IEEE 802.11 legacy PLCP preamble structure.

we have applied random CIR instances from AWGN (L = 1) and IEEE TGn “D” NLOS channel [15], which models typical indoor office environment (L= 9).

The result verifies the case classification of symbol timing offset illustrated in Fig. 2.2 and the existence of the ISI-free region by observing that SINR is maintained almost the same for−NCP+ (L−1)≤δ ≤0and rapidly decreases outside the

re-gion. Since the additive interference power,σ2

I(k, δ), becomes dominant at fartherδ’s

from the ISI-free region, SINR curves converge regardless of the ideal SNR level. For fading channels with L > 1, meanwhile, small negative STOs outside the ISI-free region but within CP, i.e.,−NCP ≤ δ < −NCP+ (L−1)yield less drastic SINR

degradation compared toδ >0. This difference between positive and negative values ofδ is attributed to the diminishing power delay profile (PDP) of CIR, which makes ISI from the previous symbol less influential than that from the next symbol.

2.2.2 Symbol Timing Synchronization for IEEE 802.11 WLAN

In IEEE 802.11 WLANs, legacy PLCP preamble is always at the head of every PPDU and utilized by receiver to acquire the symbol timing for aligning its DFT window with the following OFDM data symbols. In this section, we first provide a brief description for the preamble structure of IEEE 802.11 PPDU, and then introduce various 802.11-specific symbol timing synchronization techniques in literature.

PLCP preamble structure:Fig. 2.4 shows the legacy PLCP preamble that is prepended to all the practical IEEE 802.11 PPDU formats, namely, regardless of the standard

(34)

amendment version, e.g., 11a/b/g (Legacy) and 11n mixed-format (HT-MF) and 11ac (VHT). This uniformity helps maintain compatibility among heterogeneous standard-compliant WLAN devices. Specifically, the preamble is divided into two portions. The first is legacy short training field (L-STF), which consists of ten repetitions of a0.8µs

short training symbol. This field, by virtue of its repetitive nature and good correla-tion properties, is utilized for frame deteccorrela-tion, automatic gain control (AGC), symbol timing synchronization, and coarse frequency offset estimation. The other portion is legacy long training field (L-LTF), which contains two repetitions of a 3.2 µs long training symbol with a 1.6 µsCP. The main purposes of L-LTF are symbol timing synchronization, fine frequency offset estimation, and channel estimation.

Correlation metrics: Now we introduce two correlation metrics typically used by 802.11 receivers for processing the preamble fields:

wherer(n)is the received time-domain sample,s(n)is the known sequence stored at the receiver, andKaandKcdenote the window size parameters. Basically, these two

metrics are known to be first introduced by Schmidl and Cox in [16].

Eq. (2.13) represents the normalized auto-correlation calculated using the incom-ing signal and its one-symbol delayed version over the slidincom-ing window of lengthKa.

The metric is usually applied to L-STF with the delayd= 16(mapped to0.8µswith 20 MHz sampling rate). Its value exceeding a certain threshold indicates an incoming 802.11 PPDU detected, after which the receiver tries to search a sample index cor-responding to the start of L-LTF by observing when the auto-correlation reaches and stays at the peak level.

Meanwhile, (2.14) calculates the cross-correlation between the incoming signal and the known training sequence, andKcis determined depending on which training

(35)

sequence among L-STF and L-LTF is chosen ass(n). For example, when exploiting L-LTF samples,Kcis usually set to the number of samples in a long training symbol

(64 with 20 MHz sampling rate) and as a result of calculation two separated peaks appear at the end instants of long training symbols,L1andL2in Fig. 2.4.

Symbol timing synchronization techniques: Most symbol timing synchronization techniques for 802.11 system in literature utilize either of those two correlation met-rics or both in combination. As for the conventional SISO-OFDM systems before 802.11n, [17] proposed a cross-correlation based method applicable to L-LTF. Two separate peaks are obtained for long training symbols, and the method detects the first peak exceeding a certain threshold which indicates transition between L-STF and L-LTF. Fort’s method [18] is based on a modified auto-correlation function utilizing accumulators, which allows a clear peak instead of a plateau. [19] proposed a mech-anism which jointly utilizes auto-correlation and cross-correlation of L-STF for sym-bol boundary detection, unaffected by the arbitrary timing when PPDU detection and AGC settlement are completed. Another algorithm proposed in [20] adopted a two-step approach, where the auto-correlation using L-STF gives a coarse symbol tim-ing and then fine timtim-ing synchronization is accomplished by detecttim-ing the first cross-correlation peak of L-LTF. To deal with the plateau problem, i.e., the difficulty of auto-correlation based symbol timing synchronization methods due to the auto-auto-correlation plateau rather than a single peak, a differentiator is concatenated providing sharper peaks in the coarse step. Other than correlation based methods, there have been some maximum-likelihood (ML) based algorithms in literature [21]. They are considered impractical, however, due to excessive computational overhead as well as not provid-ing comparable accuracy to correlation based methods, as verified by [22].

With the advent of MIMO-OFDM WLANs since 802.11n, the use of cyclic shift diversity (CSD) which induces multiple cross-correlation peaks, i.e., pseudo multi-paths, has been the top priority concern for the symbol timing synchronization prob-lem. To address the pseudo multi-path problem, [2] proposed utilizing an SIR-based

(36)

metric for fine synchronization, which is calculated as the weighted sum of the cross-correlation of L-LTF. The method also resolves arbitrary AGC settlement timing and the plateau problem by adopting auto-correlation based coarse step with a sliding window differentiator, similar to that in [20]. On the other hand, [23] proposed an advanced version of Chang’s method [19], covering the pseudo multi-path problem by adopting SNR-varying threshold for the boundary detection. Finally, the proposed method in [24] introduces conjugate symmetric correlator using L-LTF for fine syn-chronization, instead of conventional cross-correlation based manner. While this al-gorithm guarantees moderate performance even with CSD-applied preambles, it has a drawback in the timeliness of channel estimation since the whole L-LTF samples are needed to calculate the conjugate symmetric correlation.

2.3 Symbol Timing Synchronization for 802.11ax

Uplink Multi-User Transmission

In the upcoming HE WLAN standard 802.11ax, most highlighted as a key driver is UL MU, which allows multiple STAs to transmit concurrently to a common AP via OFDMA, MU-MIMO, or a mixture of the both technologies. In this section, we present the specification of 802.11ax UL MU, and then elaborate on the emerging challenges regarding symbol timing synchronization for UL MU.

2.3.1 Standard Specification of UL MU

IEEE 802.11ax standard specifies that UL MU procedure is necessarily initiated by the AP announcing aTrigger frame, as shown in the upper part of Fig. 2.5. Participating STAs are then solicited for UL MU in HE trigger-based (TB) PPDU format, short inter-frame spacing (SIFS) after receiving the Trigger inter-frame. Basically, this trigger-driven procedure is for delivering the instruction about the following UL MU such as resource unit (RU) allocation, PPDU duration, MCS to be used, CP length, and so on, but also

(37)

H E -S T F H E -L T F s D a ta H E -S T F H E -L T F s D a ta C o m m o n fi e ld s H E -S T F H E -L T F s D a ta T ri g g e r F ra m e L-S T F L- _LTF L- _SIG RL- SIG HE -S IG -A HE -S T F HE -L T F s Data M u lt i-S T A B lo ck A CK S IF S S IF S C o m m o n f ie ld s : (l e g a c y f o rm a t) • O v e rl a p p in g i d e n ti c a l w a v e fo rm s • 6 4 / 1 2 8 / 2 5 6 D F T s ize f o r 2 0 / 4 0 / 8 0 M H z • 3 .2 ȝ s D F T p e ri o d w it h 0 .8 ȝ s C P U s e r-s p e c if ic f ie ld s : (1 1 a x n u m e ro lo g y ) • E a c h u s e r a ll o c a te d b y u n it s o f R U / s p a ti a l s tr e a m • 2 5 6 / 5 1 2 / 1 0 2 4 D F T s ize f o r 2 0 / 4 0 / 8 0 M H z • 1 2 .8 ȝ s D F T p e ri o d w it h 0 .8 / 1 .6 / 3 .2 ȝ s C P C o m m o n fi e ld s H E -S T F H E -L T F s D a t a A P S T A s C o m m o n fi e ld s H E -S T F H E -L T F s D a t a C o m m o n fi e ld s H E -S T F H E -L T F s D a t a C o m m o n fi e ld s H E -S T F H E -L T F s D a t a H E -S T F H E -L T F s D a t a H E -S T F H E -L T F s D a t a C o m m o n fi e ld s H E -S T F H E -L T F s D a t a C o m m o n fi e ld s H E -S T F H E -L T F s D a t a C o m m o n fi e ld s H E -S T F H E -L T F s D a t a + + F re q u e n c y -d iv is io n m u lt ip le x in g S p a ti a l-d iv is io n m u lt ip le x in g H E t ri g g e r-b a s e d (T B ) PPD U O F D M A M U -M IM O C F O e s ti m a te s P a th lo s s & T a rg e t R S S Æ P re -c o m p e n s a ti o n Æ T X p o w e r c o n tr o l D L U L D L Figure 2.5: Description of the entire UL MU procedure and HE trigger -based (TB) PPDU structure for OFDMA / MU-MIMO

(38)

aims at synchronizing the start instant of the transmissions from distributed STAs, by means of the reference signaling prior to UL MU. Unfortunately, this way of UL MU coordination via Trigger frame, however, does not ensure that all the transmitted signals arrive at the AP at the exactly same time, which could severely disrupt the receiving performance as will be detailed later.

HE TB PPDU, as a newly defined frame format for UL MU in 802.11ax, is largely divided into two distinct parts—Commonfields with legacy OFDM structure and user-specific fields with the new numerology of 802.11ax. Common fields consist of the legacy preamble fields described in Section 2.2.2 and several PHY header fields. They populate the whole bandwidth of the transmission channel like the legacy 802.11 frame formats, regardless of the allocated OFDMA RU. The only difference from the legacy 802.11 frames is that those PHY headers are generated with the information bits indi-cated by the Trigger frame, which are common for all the participants of UL MU. This means that the concurrent frames in a UL MU all have the identical waveforms for the common fields, so the preamble and PHY header fields are superposed at the AP after going through independent fading channels.

Subsequent user-specific fields are where OFDMA or MU-MIMO PHY is actually applied to support data delivery via UL MU. Unlike the legacy 802.11 frames, the user-specific fields only populate the OFDMA RU allocated for that UL MU within the whole bandwidth of the transmission channel, conveying user-specific preamble fields and data symbols. The HE preamble fields contain HE-LTFs to provide means for the receiver to retrain the channel gains, which are essential to decode the following data symbols. Note that for the remainder of this chapter we refer to those frames with the HE TB PPDU format, which are transmitted in response to Trigger frame, as “UL MU frames” or “concurrent frames” to avoid confusion.

(39)

2.3.2 Problem Description

The preceding Trigger frame coordinates UL MU such that participating STAs start their transmission simultaneously SIFS after receiving the Trigger frame. In terms of microscopic timing, however, it is not guaranteed that all those concurrent frames reach the AP at the exactly same time, since each STA has own round-trip delay (RTD) and local oscillator (LO) clock which makes its perceived SIFS interval. Concretely, the timing requirement in 802.11ax specifies that a STA who participates in UL MU shall ensure the arrival time of its transmitted frame at AP to be within ±0.4 µsof SIFS + RTD from the end of Trigger frame transmission. It also notes that STAs are not expected to measure or compensate for their RTDs [25]. Hence, for standard-compliant devices, concurrent UL MU frames can arrive at the AP with timing deviation of up to

0.8µs+ maximum RTD according to the environment.

Having distinct symbol start index nu_sym for the UL MU frame originated from

u-th STA, we defineθu as the deviation of arrival timing with respect to the earliest

arriving frame in UL MU:

θu ,nusym−min

v∈U

nv_sym , (2.15)

where U is a whole set of STAs who participate in the UL MU. Then the received baseband signal covering UL MU can be rewritten as

y(j)(n) =X u∈U hu_j(n)∗xu(n−θu) +z(j)(n) =X u∈U (_L u−1 X l=0 hu_j(l)·xu(n−θu−l) ) +z(j)(n) (2.16)

wherexu(n)andhu_j(n)denote the transmitted signal fromu-th STA and its CIR with

Lu taps to thej-th RX chain at the AP, respectively, andlis the tap index.

Fig. 2.6 illustrates the situation where concurrent UL MU frames reach the AP at slightly different timings from each other. Now we provide an investigation into the effect of asynchronous frame arrivals at AP’s UL MU receiver, which is twofold: on processing the legacy preamble fields and on decoding the following data symbols.

(40)

S1 S2S3 S4 S5 S6 S7 S8S9S10 CP L1 L2 CP SIGNAL S1 S2S3 S4 S5S6 S7S8 S9S10 CP L1 L2 CP SIGNAL L-STF L-LTF L-SIG RL-SIG HE-SIG-A User-specific Trigger Frame L-STF L-LTF L-SIG RL-SIG HE-SIG-A User-specific L-STF L-LTF L-SIG RL-SIG HE-SIG-A User-specific SIFS ±0.4ȝs₊RTD CP m-th symbol in the earliestHE TB PPDU

CP m-th symbol in the latestHE TB PPDU

Extended excess delay: ܮכ= max_௨א୙(ܮ_௨+ߠ_௨) Global ISI-free region of ࢾכ

Maximum deviation of arrival timings: ߠ_୫ୟ୶= max_௨א୙(ߠ_௨) Multiple cross-correlation peaks Delayed AGC settlement Plateau and gradual falling 1st Arrival (earliest) Last Arrival (latest)

Figure 2.6: Effects of asynchronous arrival timings among UL MU frames: 1) Global ISI-free region for DFT window, and 2) difficulty in processing legacy preamble fields.

Processing legacy preamble fields

Focusing on the legacy preamble fields, we can see that the incoming training symbols are superposed asynchronously according to their arrival timings, thus making it much harder to find a proper symbol timing. To be specific, as the detected signal strength fluctuates with each arriving frame, the AGC settlement gets delayed compared to when there is a single transmitter. This makes only a few intact L-STF samples avail-able for the synchronization purpose. In addition, the auto-correlation plateau tends to fall gradually around the boundary between L-STF and L-LTF, since the L-STF

(41)

from the late arriving frames maintains their repetitive pattern of0.8µsperiod even after the early arriving frames have moved on to L-LTF. As a result, accuracy of the auto-correlation based boundary detection methods is highly aggravated, even when combined with a differentiator as in [2, 20].

Meanwhile, the cross-correlation in (2.14) generates multiple peaks, every time its stored training sequence matches to an identical one from each UL MU frame, which is similar to the pseudo multi-path problem in MIMO transmissions. While the CSDs applied to the legacy preamble fields have pre-defined negative values up to−0.2µs, thus prone to STOs within the ISI-free region, the multiple peaks generated by asyn-chronously incoming training symbols tend to be put behind the earliest peak, obvi-ously outside of the ISI-free region. Fig. 2.7 illustrates an example of auto-correlation and cross-correlation applied to the asynchronously superposed preambles, distinct from SU case.

Above all, most challenging about processing the superposed preambles is the ran-domness in that those phenomena incurred in correlation metrics are wholly unpre-dictable, depending on the case-by-case distribution of arrival timings, θu’s and its

maximum deviation,θmax = maxu∈U(θu). Consequently, existing correlation-based

methods can be severely disrupted when employed for receiving UL MU at the AP, as will be verified in Section 2.5.

It is notable that, in practice, most commercial off-the-shelf (COTS) devices have the second capture capability [26] in receiving PLCP preamble, which is the capabil-ity to resynchronize to a newly incoming stronger signal than currently being received one. Hence, COTS devices are likely to synchronize to the strongest signal regardless of the arrival order. This “strongest first” behavior, however, is not desirable for receiv-ing concurrent frames in UL MU scenario, considerreceiv-ing practically imperfect power pre-correction and time-varying characteristics of the wireless channel. Moreover, dif-ferent from cellular communication systems that resolve the similar synchronization problem by supporting timing advance operation at the transmitter side, 802.11 WLAN

(42)

0 0.5 1 0 20 40 60 80 A u to -c o rr e la ti o n Sample index SU UL MU Plateau End of (earliest) L-STF

AGC settlement End of (earliest) L-LTF 0 0.5 1 0 10 20 30 40 50 C ro s s -c o rr e la ti o n Sample index SU UL MU

Figure 2.7: Comparison of the conventional correlation metrics between SU and 9-user UL MU: Auto-correlation in (2.13) with Ka = 16&d = 16for L-STF, and

cross-correlation in (2.14) with Kc = 64 for L-LTF (time samples in 20 MHz sampling

rate).

does not provide any functionality to pre-compensate the arrival timing deviation of concurrent transmissions.

Decoding data symbols

Looking into the data symbols, on the other hand, receiver’s DFT window should sat-isfy ISI-free for all the scattered UL MU frames to avoid mutual ISI and ICI among STAs. Accordingly, ISI-free region shrinks compared to the SU case in Section 2.2.1, thus making symbol timing synchronization for UL MU still more challenging. Now we should consider the global ISI-free region, that is, the intersection of all the ISI-free regions for concurrent UL MU frames. Equivalently, we can regard the received signal in (2.16) as SU that is being affected by a virtual CIR with an extended tap length of

(43)

L∗ = maxu∈U

Lu+θu , referring to [7]. With the maximum deviation in the worst

scenario,1.3µs, including0.5µsRTD difference and IEEE TGn ”D” NLOS channel, for instance, L∗ = 26 + 9 = 35, being larger than the medium CP length, i.e., 32 samples.

As illustrated in Fig. 2.6, the global ISI-free region, if it exists, then can be given as

−NCP+ (L∗−1)≤δ∗ ≤0, (2.17)

whereδ∗denotes STO with respect to the earliest UL MU frame, given by

δ∗ ,nˆDFT−min

u∈U

nu_sym . (2.18)

Note that forL∗−1> NCP, there exists no global ISI-free region that guarantees zero

mutual interference among STAs.

When satisfying the global ISI-free region, the DFT output on thek-th subcarrier is rewritten as Y_m(j)(k) = X u∈Uk ej2πkδu/NDFT_Hu j(k)Xmu(k) +Zm(j)(k), whereδu=δ∗−θu = ˆnDFT−nusym, (2.19)

whileUkrepresents a set of STAs, who are assigned the RU containing thek-th

sub-carrier, i.e.,Uk ,

uu ∈ UandX_mu(k) 6= 0for∀min user-specific fields . In this case, (2.19) just involves the linear phase offsets as in (2.9), yielding no SINR degra-dation.

On the other hand, if the AP’s DFT window starts somewhere outside the global ISI-free region or the global ISI-free region does not exist, the output suffers from self or mutual interference between STAs as well as signal distortion, according to

(44)

respectiveδu’s: Y_m(j)(k) = X u∈Uk α(δu)ej2πkδu/NDFTHju(k)Xmu(k) +X u∈U I_u,m(j) (k, δu) +Zm(j)(k), (2.20)

whereα(δu) andIu,m(j)(k, δu) reduce to unity and zero, respectively, forδu satisfying

each local ISI-free region,−NCP+Lu−1≤δu ≤0.

Similar to (2.12), average SINR for theu-th frame in UL MU is thus obtained by

SINRu_k(δv v∈U ) = α2(δu) P jWuj(k)Hju(k) 2 P_Tu σ2_MMSE+σ2_I,_tot+N0 P_j W_uj(k) 2, whereσ2_MMSE= X v∈Uk,v6=u    α2(δv) X j Wuj(k)Hjv(k) 2 P_Tv    , σ2_I,_tot=X v∈U σ_I2(k, δv), (2.21)

when AP adopts an MMSE receiver with the ideal coefficient matrix W(k) gener-ated from H(k) whose elements are H(k) _ju = H_ju(k). Although (2.16)–(2.21) above have been derived for single-stream transmission per STA in UL MU, straight-forwardly they can be extended to STAs each transmitting multiple streams, combined with OFDMA, MU-MIMO or a mixture of both.

2.4 Proposed Symbol Timing Synchronization

As described in the previous section, symbol timing synchronization for 802.11ax UL MU involves the distinct challenges from SU case, that is, conventional correlation metrics are disrupted by superposed preambles, and the ISI-free region for DFT win-dow position shrinks. In this section, we first examine how precise the symbol timings should be to ensure “good” performance in terms of data delivery via UL MU, and then propose a new symbol timing synchronization mechanism for AP’s UL MU re-ceiver. Our solution addresses asynchronous frame arrivals in order to accommodate

(45)

Table 2.1: Simulation settings.

Model & parameter Value

Bandwidth 20 MHz

Channel model TGn “D” NLOS

Number of STAs in UL MU 9 (OFDMA alone) / 8 (with MU-MIMO) Number of antennas Each STA: 1, AP: 1 (OFDMA alone)

Each STA: 1, AP: 4 (with MU-MIMO) Maximum arrival deviation (θmax) 16 (0.8µs) / 26 (1.3µs)

Frequency & power difference Ideal pre-correction assumed

SNR @∼90% MUDR withθu= 0for all STAs

and perfectly synchronized toδ∗_{= 0}

RU allocation 26-tone×9 (OFDMA alone)

106-tone×2 (with MU-MIMO) Number of spatial streams per RU 1 (OFDMA alone) / 4 (with MU-MIMO)

Cyclic prefix 1.6µs (medium size)

Modulation & coding scheme MCS3 (16-QAM, R=1/2) MCS7 (64-QAM, R=5/6)

MPDU size 1,500 bytes (no aggreagation)

CSD Following standard specification

Foward error correction (FEC) Binary convolutional code (BCC)

and soft-decision Viterbi decoder at receiver

UL MU into the backward-compatible 802.11 WLAN, by exploiting two key break-throughs: Remaining repetitive nature on superposed training symbols and per-STA channel estimates demultiplexed in frequency domain.

2.4.1 Performance Requirement

To investigate the desirable performance of new symbol timing synchronization for 802.11ax UL MU, we have tested on our 802.11ax link-level simulator how badly degraded the data delivery of UL MU is under differentδ∗’s and different values of an environmental parameter, namely, maximum deviation of arrival timings,θmax.

For each simulation run, UL MU frames arrive at the AP having independent ran-dom arrival timings following the uniform distribution withθmax = 16 (0.8µs)and

(46)

26 (1.3 µs). These two values are chosen representatively as they each correspond to the maximum tolerance without RTD difference specified in the standard and the maximum deviation in the worst scenario having RTD difference up to0.5µs. Using the channel traces from TGn “D” NLOS model withL= 9, the global ISI-free region for each value ofθmaxis given as−NCP+ 25≤δ∗ ≤0and−NCP+ 35≤δ∗ ≤0,

respectively, according to (2.17). Thus, with1.6µsCP (NCP= 32), for example, the

global ISI-free region for θmax = 16is −7 ≤ δ∗ ≤ 0, whereas no global ISI-free

region exists forθmax= 26. We assume the ideal frequency and power pre-correction

at STAs, so that there exists no frequency offset and no difference in the average signal strength among the received concurrent frames. Instead of the packet delivery ratio (PDR) commonly used in SU, we newly define MU data delivery ratio (MUDR) as the ratio of the number of successfully received MPDUs to the number of total MPDUs transmitted in a UL MU, in order to represent a metric to approximate “PDR per UL MU.” As in discussing PDR for conventional SU, we set MUDR around∼90% as the desirable performance of interest, which is considered an allowable reference level un-der given SNR in WLAN environments.3All the simulation settings are summarized in Table 2.1.

We set up two different UL MU scenarios for simulation, as illustrated in Fig. 2.8: 1) OFDMA alone where 9 concurrent frames are transmitted each populating one of the 9 26-tone RUs within 20 MHz for its user-specific fields, and 2) OFDMA combined with MU-MIMO where 8 concurrent frames are transmitted each populating one of the two 106-tone RUs within 20 MHz for its user-specific fields, forming four spatial streams per RU.

Fig. 2.9 shows average MUDR versusδ∗ for the two scenarios, with SNR set to some fixed levels at which perfectly synchronous UL MU (zeros for allθu’s andδu’s)

3

IEEE 802.11ax standard even specifies “Acceptable Receiver Interference Level” at triggering AP to be calculated using SNR margin of yielding 10% packet error rate for the ensuing uplink HE TB PPDUs, found in Clause 27.9.3.3 of [25].