應用於數位電視廣播系統之通道等化器設計

(1)

國立交通大學

電子工程學系電子研究所碩士班

碩士論文

應用於數位電視廣播系統之通道等化器設計

Channel equalizer for DVB-T/H System

學生：馬英豪

指導教授：李鎮宜教授

(2)

應用於數位電視廣播系統之通道等化器設計

Channel equalizer for DVB-T/H System

研究生：馬英豪 Student：Ying-Hao Ma

指導教授：李鎮宜 Advisor：Chen-Yi Lee

國立交通大學

電子工程學系電子研究所碩士班

碩士論文

A Thesis

Submitted to Institute of Electronics

College of Electrical Engineering and Computer Science National Chiao Tung University

in Partial Fulfillment of the Requirements for the Degree of

Master of Science in

Electronics Engineering July 2006

Hsinchu, Taiwan, Republic of China

(3)

應用於數位電視廣播系統之通道等化器設計

學生：馬英豪指導教授：李鎮宜教授

國立交通大學

電子工程學系電子研究所碩士班

摘要

數位電視的發展為未來一大趨勢，在本論文中，我門將會介紹通道估測演算法以及在2005 年 6 月，我們使用 0.18 微米製程實現了數位電視廣播系統基頻接收器的晶片設計。系統架構設計是根據歐規數位電視地面廣播系統的規格，以及考量通道非理想特性狀況。我們提出可適應性調整估測器的權重係數在時變通道中可達到降低雜訊干擾的效應。此外，通道響應使用散佈領航碼作二維通道響應的內插，我們分析多種多項式內插方法於不同通道下的效能。在硬體架構下，複數除法器佔了通道等化器大部分的硬體花費以及功率消耗，所以此處我們提出複數除法器的改善架構，在此架構可以有效率的降低硬體花費已及功率消耗。可節省原本 90.5%的硬體花費以及 59.9%的功率花費。

(4)

Channel equalizer for DVB-T/H System

Student：Ying-Hao Ma Advisor：Dr. Chen-Yi Lee

Institute of Electronics Engineering

National Chiao Tung University

ABSTRACT

In this thesis, we introduce the channel estimation algorithm for DVB-T/H system, and COFDM basedband receiver chip for DVB-T/H applications. This chip is implemented with 0.18μm cell library and tapped out in Jun. 2005. The architecture is established according to the standard and several channel impairments. We propose the adaptive channel estimator for pilot signal which can average out the noise effects under portable environments. Furthermore, the channel response is estimated by means of two-dimension interpolation of scattered pilots. We analyze several polynomial interpolation methods under channels specified by standards. In architecture part, we can find the complex division is dominant the equalizer in cost and power. So we proposed the improved architecture for simplified the division architecture which hardware can be saved by 90.5% and power saved by 59.9% in divider itself.

(5)

誌

謝

從大四推徵進實驗室以來，Si2 這個大家庭已經與我共度了兩年多的時光。在這裡不但學到了許多專業知識，為人處事方面更是受益良多。能完成這本論文，我最感謝的，是李鎮宜教授這兩年多以來不厭其煩的指導與研究方向的指引，讓我在研究遇到挫折或困難時，得以重新找到突破瓶頸的方法。此外，也要感謝李鎮宜教授爲實驗室提供完善的研究設備，使我的研究得以順利完成。在這裡，也要特別感謝DVB group 的黎峰學長、昱偉學長、陳元老兒大夥一起努力 tape out 的那段不眠不休的日子真的很有趣，快速的拉近了彼此的距離跟感情，感謝大家這兩年來的腦力激盪與相互討論，不但使我在相關的研究領域有所精進，更學習到團隊合作的可貴。尤其是昱偉不只在功課以及其他方面幾乎都給了我很多寶貴意見跟實際的支持，讓我感到相當窩心的感動及感謝。還有可靠的YY 以及三師兄，凶狠的 meeting 的砲火攻勢，讓我每次都很感挫折但卻覺得收穫良多。還要感謝與我同屆的家豪、侯康、阿龍，在這兩年內，我們一起經歷過許多風風雨雨，有歡笑沒有淚水，有你們的陪伴，使我這兩年的碩士生涯充滿了多彩多姿的回憶。最後，我要由衷的感謝我的父母及家人，感謝你們多年來的栽培及細心，讓我能順利完成碩士的學業。僅將此論文獻給你們，以表達我最深的感激。

(6)

List of Figures

FIG.1.1FUNCTIONAL BLOCK DIAGRAM OF DVB-T SYSTEM...3

FIG.1.2BLOCK DIAGRAM OF DVB-H CODEC AND TRANSMITTER...5

FIG.2.1TIME VARIANT CHANNEL FREQUENCY RESPONSE...9

FIG.2.2PILOT PATTERN IN DVB-T/H SYSTEMS...10

FIG.2.3CHANNEL ESTIMATION FUNCTION BLOCK DIAGRAM... 11

FIG.2.4THE FILTER DIAGRAM...12

FIG.2.5THE MODIFIED FILTER DIAGRAM...13

FIG.2.6THE TIME VARIANT CFR AT 1ST PILOT SUBCARRIER WITH DOPPLER...14

FIG.2.7BLOCK BASED ESTIMATOR MODEL & THE DYNAMIC CHANNEL MODEL...14

FIG.2.8ADAPTIVE WEIGHT FILTER AT EACH PILOT SUB-CARRIER...14

FIG.2.9THE RELATIONSHIP OF CFR AND NOISE...16

FIG.2.10THE CFR OF RAYLEIGH CHANNEL @AWGN25DB...16

FIG.2.11THE FLOW DIAGRAM...17

FIG.2.12THE 2X1D INTERPOLATION PROCESSING...19

FIG.2.131ST-ORDER PREDICTIVE INTERPOLATION IN TIME DOMAIN...20

FIG.2.14LINEAR INTERPOLATION IN TIME DOMAIN...21

FIG.2.15POLYNOMIAL INTERPOLATION IN FREQUENCY DOMAIN...22

FIG.3.1THE FORMAT (M, N) STRUCTURE...28

FIG.3.2THE BITS PRESENTATION OF DIVISION...28

FIG.3.3THE STATE DIAGRAM...29

FIG.3.4THE FLOW OF THE STATE 1 ...30

(9)

FIG.3.6TIMING DIAGRAM...32

FIG.4.1OVERALL DVB-T/H PLATFORM...33

FIG.4.2THE BASEBAND RECEIVER DESIGN...35

FIG.4.3FUNCTIONAL BLOCKS OF INNER RECEIVER...35

FIG.4.4CHANNEL MODEL OF DVB-T/H SYSTEM...36

FIG.4.5CHANNEL RESPONSE OF RAYLEIGH AND RICEAN (K=10DB) CHANNEL...38

FIG.4.6TU6 MODEL...39

FIG.4.7DOPPLER SPREAD MODEL...40

FIG.4.8RAYLEIGH DOPPLER SPECTRUM GENERATOR...42

FIG.4.9RAYLEIGH FADING DOPPLER SPECTRUM BY JAKE’S MODEL...42

FIG.4.10RICE FADING DOPPLER SPECTRUM BY JAKE’S MODEL...43

FIG.4.11MSE OF DIFFERENT FREQUENCY INTERPOLATOR IN GAUSSIAN CHANNEL...46

FIG.4.12MSE OF DIFFERENT FREQUENCY INTERPOLATOR IN RICEAN CHANNEL...47

FIG.4.13MSE OF DIFFERENT FREQUENCY INTERPOLATOR IN RAYLEIGH CHANNEL...48

FIG.4.14COMPARISON DIFFERENT FREQUENCY INTERPOLATOR IN DYNAMIC CHANNEL...51

FIG.4.15DIFFERENT TIME INTERPOLATOR UNDER RAYLEIGH CHANNEL...52

FIG.4.16DIFFERENT TIME INTERPOLATOR UNDER TU6 CHANNEL...53

FIG.4.17PERFORMANCE BETWEEN DIFFERENT R UNDER RAYLEIGH CHANNEL...54

FIG.4.18PERFORMANCE BETWEEN DIFFERENT R UNDER TU6 CHANNEL...55

FIG.4.19(A)PERFORMANCE UNDER STATIC RICEAN CHANNEL...57

FIG.4.19(B)PERFORMANCE UNDER RICEAN CHANNEL WITH 70HZ DOPPLER...57

FIG.4.20(A)PERFORMANCE UNDER STATIC RAYLEIGH CHANNEL...58

FIG.4.20(B)PERFORMANCE UNDER RAYLEIGH CHANNEL WITH 70HZ DOPPLER...58

FIG.4.21(A)PERFORMANCE UNDER TU6 CHANNEL WITH 10HZ DOPPLER...59

FIG.4.21(B)PERFORMANCE UNDER TU6 CHANNEL WITH 30HZ DOPPLER...59

(10)

FIG.5.1PLATFORM-BASED DESIGN METHODOLOGY...63

FIG.5.2ARCHITECTURE OF THE DVB-T/H BASEBAND RECEIVER...65

FIG.5.3POWER PROFILING...65

FIG.5.4CHIP PHOTO...66

FIG.5.5THE ARCHITECTURE FOR 2X1D LINEAR INTERPOLATION CHANNEL EQUALIZATION...68

FIG.5.6E[N2/X2] ESTIMATION BY CONTINUOUS PILOTS...69

FIG.5.7E[D2] ESTIMATION BY PREVIOUS 3 SAMPLES...69

FIG.5.8ARCHITECTURE FOR PROPOSED ESTIMATION...70

FIG.5.9HARDWARE ARCHITECTURE FOR PROPOSED CHANNEL EQUALIZATION...71

FIG.5.10PROPOSED ARCHITECTURE FOR 12 CYCLE...72

FIG.5.11PROPOSED ARCHITECTURE FOR 6 CYCLE...72

(11)

List of Tables

TABLE 1-1PARAMETERS FOR 8MHZ CHANNEL IN DVB-T STANDARD...4

TABLE 1-2PARAMETERS FOR 8MHZ CHANNEL IN DVB-H STANDARD...6

TABLE 2-1 STORAGE REQUIREMENTS FOR INTERPOLATION IN TIME DOMAIN...22

TABLE 2-2 THE COEFFICIENTS LIST...25

TABLE 2-3 THE COEFFICIENTS RELATIONSHIP...25

TABLE 3-1 THE PARAMETER RELATIONSHIP IN STATE2...31

TABLE 4-1TYPICAL URBAN RECEPTION (TU6) CHANNEL MODEL...39

TABLE 4-2RURAL AREA RECEPTION (RA6) CHANNEL MODEL...40

TABLE 4-3COMPARISON ON PERFORMANCE AND COST UNDER RAYLEIGH CHANNEL MODEL...52

TABLE 4-4COMPARISON ON PERFORMANCE AND COST UNDER TU6 CHANNEL MODEL...53

TABLE 4-5(A)COMPARISON ON PERFORMANCE BETWEEN DIFFERENT Β...60

TABLE 4-5(B)COMPARISON ON PERFORMANCE BETWEEN DIFFERENT Β...61

TABLE 4-5(C)COMPARISON ON PERFORMANCE BETWEEN DIFFERENT Β...61

TABLE 5-1CHIP SUMMARY...66

TABLE 5-2COEFFICIENTS TABLE FOR C1 AND C2 ...70

TABLE 5-3SYNTHESIS AND GATE-LEVEL SIMULATION RESULTS...74

(12)

Chapter 1 .

Introduction

In this chapter, we will describe the motivation of this research first. Introduction to the DVB-T/H standard will be made later. Finally, the organization of this thesis will be listed in the end of this chapter.

1.1 Motivation

Orthogonal frequency division multiplexing is a multicarrier transmission technique which uses parallel data transmission and frequency division multiplexing and was drawn firstly in 1960s [1-2]. Because of the high channel efficiency, OFDM is wildly applied in the new generation wireless access systems such as digital broadcasting systems [3-4] and wireless local area network [5-6].

In wireless communications, the receiver systems have to compensate the channel effects. Therefore, the channel equalizer and FEC techniques are exploited the system performance. The channel equalizer is used to recover original signal under non-perfect channel environment. In practical, the statistics of channel frequency response are not known, and time variant. In DVB-T/H system, we base on the pilots arrangement to estimate the channel and to compensate the non-perfect channel effects. Because of the DVB-T/H is (2K/4K/8K) point-modulation, which data in each OFDM is quite large. So different methods of collecting data for estimating the channel statistics will cost a lot of memory requirements. In DVB-H systems, the mobile issue is added. So the channel effects will degrade the performance seriously. This is a big challenge for defense the Doppler effects.

(13)

The objective of this thesis is to deign a low complexity channel equalizer scheme, and performance of proposed method can defense about 70Hz Doppler effects under practical hardware cost.

1.2 Introduction to DVB-T/H system

Digital Video Broadcasting-Terrestrial (DVB-T) has been subjected to technical discussion for many years and undoubtedly been shown as a great success in delivering high quality digital television by terrestrial means [3]. DVB-T standard has been produced by European Telecommunication Standard Institute (ETSI) in Aug, 1997. It has been applied in many countries around the world such as Taiwan. Although the DVB-T reception can be applied in mobile environment, the ability of reception for handheld terminals is still not good enough because of its high operation power. Therefore, Digital Video Broadcasting-Handheld (DVB-H) was also proposed based on the DVB-T technology to provide broadcast services for handheld devices such as PDAs or mobile phones [7]. The detailed concepts of DVB-T and DVB-H will be illustrated later.

The transmission system of the DVB-T standard is shown in Fig. 1.1. It contains the blocks for source coding, outer coding and interleaving, inner coding and interleaving, mapping, OFDM modulation, and frame adaptation, respectively. In the case of two-level hierarchy, the functional block diagram of the system must be expended to include the modules shown in dashed line. After the MPEG2 transport multiplexer, a Reed-Solomon (RS) shortened code (204,188, t=8) and a convolutional byte-wise interleaving with depth I=12 shall be applied to generate error protected packets. As Fig. 1.1 shows, the outer interleaver is followed by the inner coder. This coder is designed for a range of punctured convolutional codes, which allows code rates of 1/2, 2/3, 3/4, 5/6, and 7/8. If two-level hierarchical transmission is used, each of two parallel inner codes has its own code rate. Afterward, the

(14)

inner interleaver is block based bit-wise interleaving. The constellation mapping for OFDM subcarriers operates with various modes after the inner interleaver. The constellation modes are QPSK, 16-QAM, 64-QAM, non-uniform 16-QAM, and non-uniform 64-QAM, respectively. The transmission channel bandwidth is 6MHz, 7MHz, and 8MHz, respectively.

Fig. 1.1 Functional Block diagram of DVB-T system

The DVB-T system uses OFDM technique with various transmission parameters. The parameters for 8MHz channel bandwidth in DVB-T standard are listed in Table 1-1. Two modulation modes are defined: a 2k mode and an 8k mode. The 2k mode is suitable for short distance transmission and high speed mobile reception because of its short symbol duration and wide subcarrier spacing. On the contrary, the 8k mode is suitable for long distance transmission and deep multipath spread. Other parameters such as code arte, constellation mode, and guard interval length can also be decided properly according to the broadcasting channel condition of the local area.

An OFDM frame consists of 68 OFDM symbols and four frames constitute a super-frame. In addition to the transmitted data, an OFDM symbol contains several kinds of reference signals for synchronization and channel estimation such as scattered pilots,

(15)

continual pilots, and TPS (Transmission Parameter Signaling) pilots. Scattered pilots are inserted every 12 subcarriers and have an interval of three subcarriers in the next adjacent symbol. Continual pilots locate at fixed subcarrier index which contain 177 for 8k mode and 45 for 2k mode, respectively. Both scattered pilots and continual pilots are transmitted at boosted power level of 16/9 whereas the data subcarriers are normalized to 1, and modulated according to the PRBS (Pseudo Random Binary Sequence) sequence (X11+X2+1). The TPS pilots are used for signaling parameters related to transmission scheme, i.e. to channel coding and modulation. The TPS pilots are defined over 68 consecutive OFDM symbols and transmitted in parallel on 17 TPS subcarriers for 2k mode and 68 for 8k mode. Each OFDM symbol conveys one TPS bit which is differentially encoded in every TPS subcarrier. The TPS information contains frame number, constellation, hierarchy, code rate, guard interval, FFT mode, and BCH error protection code, respectively. Unlike continual and scattered pilots, TPS pilots are transmitted as the normal power level of 1 with DBPSK modulation.

Table 1-1 Parameters for 8MHz channel in DVB-T standard

Parameter 8k mode 2k mode

Number of subcarriers K 6817 1705

Value of carrier number Kmin 0 0

Value of carrier number Kmax 6816 1704

FFT size N 8192 2048

Symbol duration TU 896μs 224μs

Subcarrier spacing 1/TU 1.116KHz 4.464KHz

Spacing between Kmin and Kmax 7.61MHz 7.61MHz

Guard interval Ng/N 1/4,1/8,1/16,1/32 1/4,1/8,1/16,1/32

The DVB-H technology is a spin-off of the DVB-T standard. It is large extent compatible to DVB-T but takes into account the specific properties of the addressed

(16)

terminals- small, lightweight, portable, battery-powered devices in mobile environment. Unlike the DVB-T transport stream adopted from the MPEG2 standard, the DVB-H system is IP (Internet Protocol)-based, therefore the outer DVB-H interface is the IP interface. The IP data are embedded into the transport stream by means of the MPE (Multi Protocol Encapsulation) frame, an adaptation protocol defined in the DVB Data Broadcasting Specification [8]. One MPE frame contains one or more IP datagrams and has a maximum number of 1024 rows and a constant number of 255 columns. The block diagram of DVB-H codec and transmitter is as shown in Fig. 1.2.

mu x mu x MPEG2 TV Service MPEG2 TV Service MPEG2 TV Service MPEG2 TV Service MPEG2 TV Service MPEG2 TV Service MPEG2 TV Service MPEG2 TV Service

MPE MPE-FEC Time Slicing DVB-H Codec

MPE MPE-FEC Time Slicing DVB-H Codec DVB-T Modulator 8K 4K 2K DVB-H TPS DVB-T Modulator 8K 4K 2K DVB-H TPS TS Transmitter New in DVB-H

Fig. 1.2 Block diagram of DVB-H codec and transmitter

As we can see the DVB-H codec is composed of the MPE, MPE-FEC, and time slicing. In order to satisfy the low power issue in battery-powered terminals, a time-multiplexed transmission of different service is exploited. This technique, called time slicing, allows for selective access to desired data and results in a large battery power saving effect. The burst duration of time slicing is in the range of several hundred ms whereas the off-time may amount to several seconds. The lead time for power-on and resynchronization is assumed to be less than 250ms. Depending on the duty/turn-off ratio, the resulting power saving may be more than 90%. For mobile channels reception and long delay spread conditions, an enhanced error protection scheme on the link layer is needed. This scheme is called MPE-FEC and employs powerful channel coding and time interleaving. The MPE-FEC scheme consists of an RS code in conjunction with an extensive block interleaving. The RS (255, 191, 64) code is utilized to perform MPE-FEC error protection. Besides, a virtual block interleaving effect is

(17)

also performed by reading from and writing to the MPE frame in column direction whereas coding is applied in row direction.

As for the physical layer, the DVB-H is compatible with the DVB-T standard except some additional points. First, the DVB-H provides new TPS pilots which exploit the reserved TPS subcarriers defined in the DVB-T standard. The new contents of the TPS pilots provide the information about MPE-FEC and time slicing. Besides, an additional OFDM transmission mode and a new symbol interleaving method within the inner interleaver, 4k mode and in-depth interleaving, are also provided by the new TPS pilots. DVB-H provides an intermediate 4k mode with 4096-point FFT in the OFDM modulation. The 4k mode represents a compromise solution between the 2k and 8k mode to satisfy long distance transmission and mobile reception. The in-depth interleaving allows the symbol interleaver operates at 8k interleaving length while the 2k or 4k mode is applied to improve the interleaving performance. Besides, the DVB-H also supports 5MHz transmission channel bandwidth. The parameters for 8MHz channel bandwidth in DVB-H standard are listed in Table 1-2.

Table 1-2 Parameters for 8MHz channel in DVB-H standard

Parameter 8k mode 4k mode 2k mode

Number of subcarriers K 6817 3409 1705

Value of carrier number Kmin

0 0 0

Value of carrier number 6816 3408 1704

Symbol duration TU 896μs 448μs 224μs Subcar 1/TU 1.116KHz 2.232KHz 4.464KHz Sp d 7.61MHz 7.61MHz 7.61MHz 1/4,1/8,1/1 6,1/32 1/4,1/8,1/1 6,1/32 1/4,1/8,1/1 6,1/32 Kmax FFT size N 8192 4096 2048 rier spacing

acing between Kmin an

Kmax

(18)

1.3 Organization of This Thesis

i s f er d

algorithms of the proposed channel e cheme will be introduced. 3 we

odified architecture scheme. The simulation result and performance analysis introduce the design methodology, improved archi

This thesis is organ zed a ollows. In chapt stimation s

2, the signal mo els and the detailed In chapter propose the m

will be discussed in chapter 4. Chapter 5 will

tecture of the proposed design and the chip summary of DVB-T/H [28]. Conclusion and future work will be given in chapter 6.

(19)

Chapter 2 .

hannel Estimation Algorithms

uce the signal model and the effect of time variant channel in in different categories will be on between developed and the oposed algorithms are also made.

rest in mobile communication research lately. For s, the radio channel is usually frequency selective

me tion of radio channel appears unequal

in b

C

In this chapter, we introd

DVB-T/H system first. The algorithms of channel estimation illustrated in later sections. Some comparison and discussi pr

2.1 Introduction to channel estimation

OFDM is a bandwidth efficient signal scheme for digital communications. In OFDM systems, it has received a lot of inte

wideband mobile communication system

and ti variant. Furthermore, the channel transfer func

oth frequency and time domains. Therefore, a dynamic estimation of the channel is necessary for the demodulation of OFDM signals. In wideband mobile channels, the pilot-based signal correction scheme has been proven a feasible method for OFDM systems. Most channel estimation methods for OFDM transmission systems have been developed under assumption of a slow fading channel, where the channel transfer function is assumed stationary within one OFDM data block. In practice, the channel transfer function of a wideband radio channel may have significant changes even within one OFDM data block. Therefore, it is preferable to estimate channel characteristic based on the pilot signals in each individual OFDM data block.

(20)

on the subcarrier. ( )h n_l h n t( , ) h t_i( ) (n _i) i

δ τ

= =

∑

⋅ − This equation is comprised of the actual

channel impulse response (CIR) and the transmission filter. The transmitted signal

is 1 1 2 n , 0 j k N− π _N l

s =

∑

_k X e_{l k} , so the received signal is ( ) ( ) ( )

N = y nl =h nl ⊗s nl . The ⊗ operator is

symbol. For the m

channel to be constant during the transmission of one OFDM symbol denoted by ( )h n . _l

convolution, and oment, we assume the

Furthermore, when the convolution operation in time domain transfers to frequency domain it

be operation. So the demodula requency domain can

be shown byY_{l k}_, = FT y n( ( ))_l =H_{l k}_, ⋅X_{l k}_, , and the H is the channel frequency response. _{l k}_,

l means that it is the lth

comes a multiplication ted data symbol in f

F 2 , ₀ kn j l k l _n l π − =

For time variant channel environments, the CFR will vary as time and frequency. It is

1

( ( )) N ( ) N

H =FFT h n =

∑

− h n e (2-1)

illustrated in ponse will change as time varying because of

the Doppler ef h delay will cause the CFR with selective

Fig.2.1. The channel frequency res fects. Furthermore, the multipat fading in frequency domain.

10 20 30 40 50 60 70 0 50 100 150 200 0 0.5 1 1.5 2 2.5

Frequency

Time

CF

R

(21)

The pilot pattern is shown in Fig2.2. In DVB-T pilot carriers are transmitted together with data carriers, so that the channel transfer function is estimated both infrequency and in time. The use of pilots for estimation of the CFR is a main topic of research in OFDM system. Because of the scatted pilots the interpolation methods are adopted here too [9-11].

In this paper, the channel estimation methods for OFDM systems based on comb-type pilot sub-carrier arrangement are investigated. The channel estimation algorithm based on comb-type pilots is divided into pilot signal estimation and channel interpolation.

2.2 Motivation

OFDM is the most prevalent modulation scheme in modern and future wireless communication systems. However, in mobile reception, a loss of sub-carrier orthogonality due to Doppler spread leads to inter-carrier interference. There are several estimation methods, like Wiener filter [9] and MMSE [12] estimator. Furthermore, there are several ICI cancellation schemes [13]. The complexity of these methods is proportional to the number of adjacent carriers which are used to cancel ICI. Besides, they have an important assumption, that the channel state information (CSI) is known. This assumption is impractical in reality,

(22)

especially during mobile environment. Here, we will propose the method which can implement efficiently and realizable methods. In following content, we will introduce the proposed channel estimation scheme.

In this paper we assume that the channel is time variant. Therefore, the channel frequency response (CFR) for present symbol should be obtained independently. The proposed channel estimation method based on pilot signals and transform domain processing is depicted in Fig. 2.3.

2.3 Channel estimator for pilot signal

N(K), we will extract the pilot signal YM(K). The

first k

Fig. 2.3 Channel estimation function block diagram

Here we will focus on these three parts. First, the estimator can get the CFR at pilot location, and second, filtering can reduce the noise effect. Finally, we can get the CFR of whole symbol by interpolation methods. The three key points will be discussed in following.

When we receive the receiving data Y

ey point is to get the CFR at pilot location HP(K) by YM(K) and known pilot data XP(K).

We can use LS estimator directly by

H k

ˆ ( )

_p

=

Y k

_M

( ) /

X k

_p

( )

. However, this estimator will be easily affected by noise. To reduce the MSE of the LS estimator, we rely on a filter method based in the LS estimator. In fact, in most slowly variant channel environment, this estimator

(23)

can get better im

performa t

channel. In order to red average

if the pilot-based estim α1=1 and α0

1,

l k l

H₊ ₊H

provement [14-16]. We propose an adaptive filter which can get better nce in slowly variant channel, and it will not degrade the performance in fast varian

uce the estimation error, the predicted estimated is a weighted

ate and a previous estimated. The formulation is following (2-2), where =0 initially. The filter diagram is shown in Fig.2.4.

1 l 1,k lHˆl k, l 1Yl 1,k/Xl 1,k lHl k, , l 1, l [0,1] α ₊ α α ₊ ₊ ₊ α α α₊ = + = + ∈ (2-2)

H

, ,

/

, l k l k l k

H

=

Y

X

1, l+ k

Fig. 2.4 The filter diagram

he MSE of the estimate. Furthermore, we

prop

T weights αare chosen in order to minimize the

ose an algorithm to decide the weights. Because of the standard, the scatter pilots is four symbols a cycle, here we use three taps FIR. The formulation becomes to (2-3), and MSE is (2-4). 2 0 1 2 ( ) ( ) ( ) H H H H H H D H D 0 0 0 0 1 1 1 2 2 0 0 0 1 1 1 1 2 2 N N N X X X − − − − − − − − α α α α α α α − α − = + + = + + + + + + + (2-3) 2 2 2 0 1 2 [ ( ) ( ) ( ) ] E H H D H D H N N N 0 0 0 0 0 1 1 1 1 2 2 0 2 2 0 1 2 2 2 0 0 1 1 0 0 1 1 1 2 0 0 1 1 ( ) [( 1) ] MSE E H H N N N X X X E H D D X X X α α α α α α α α α α α − − − − − − − − − − − − = + + − + + + + + α α α − α − = − = + + + + + + + − (2-4)

where Di is caused by time variant channel and Ni is the AWGN noise. In MSE (2-4), we

assume the CFR H0 is much bigger than Di and Ni. H D_i ,H Ni

X >> >>

(24)

the first term 0 0 1 α α α+ + 2-5) equal to zero. 2 1 0 ( ₋ α₋ −1)H = (0 2 1 2 0 0 0 0 0 0 1 0 4( 1) (1 ) (1 ) 2 2 2 α α α α 0 0 1 1 α α α α α α α − = − − − = = ± − = − ( − − − + + − ± 2-6)

We can find the relationship between So we define the weights

(1 ) α0 and α-1 is shown in (2-6). 0 1 α = −β 1, ˆ , 1, 1, , (1 β)H_l₊ _k+βH_{l k} = −(1 β)Y_l₊ _k/X_l₊ _k +βH_{l k},β∈[0,1] α₋ =β (2-7)

So the diagram will become to Fig.2.5.

1, l k H ₊ = − (2-8)

H

_{l k}_, _{l k}_,

/

_{l k}_, 1, l k

H

₊

Y

X

=

nel with Fig. 2.5 The modified filter diagram

In Fig.2.6 we can find the time-variant CFR at someone sub-carrier in Ricean chan different Doppler effects. CFR will change more seriously as Doppler effects increasing.

(25)

1.5 50 100 150 200 250 0 300 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4

symbol number @ time axis

CF R a t 1 st pi lot s ubc ar rier Doppler 0Hz Doppler 10Hz Doppler 30Hz Doppler 70Hz

Fig. 2.6 The time variant CFR at 1 pilot subcarrier with Dopst pler

Fig. 2.7 shows the model we use, and we can find Di is like linear variance. We define

dynamic channel model in Fig. 2.7.

Fig. 2.7 Block based estimator model & the dynamic channel model We can base on the MSE (2-9) to change the weight βk at each pilot sub-carrier Fig. 2.8.

t filter at each pilot sub-carrier

Because of the standard, the scatter pilots is four symbols a cycle. If we assume the D2=2D1

The MSE in (2-4) becomes to (2-9).

(26)

2 1 2 0 0 2 2 2 2 2 2 4 1 2 2 2 2 2 2 3 4 2 3 4 1 2 ˆ ( ) ( (1 ) ) ( ) (1 ) (1 ) ( )[ 2 ] ( ) 1 2 2 2 2 D D MSE E H H N E D D E X N E D E X β β β β β β β β β β β β β β = = − ⎡ ⎤ = − + + _⎣ − + − + _⎦ ⎡ ⎤ ⎯⎯⎯⎯→ + + + _⎣ − + − + _⎦ (2-9)

In this equation, we need to determine the variance of CFR in three symbols E(D2) and

variance of A 2 2

2

WGN E(N /X ). Furthermore, we can find first term in MSE (2-9), as Doppler effects is increasing, the E(D ) will increase too. The second term AWGN noise effect can be average out with larger β. So MSE will trade off in these two terms. We can base on the MSE equation to decide the weight of each pilot sub-carrier.

In static channel, we can find the proposed estimator can get better MSE than without filter design. The CFR variance D is equal to zero in static channel.

2 2 2 2 2 0 2 2 2 1 ˆ ( ) ( ) (1 ) 1 1 ( ) ( ) n n i spec spec n i i N MSE E H H H E X N E E β β β β 2 2 ₂ _N β − β 2 ₁ 2 2 X −β X

In static channel we can find larger β

=∞ − = − = + × − × − − ⎯⎯⎯→ × ≤ (2-10)

can get better performance, but in fact the channel will ore time dependent as eans the channel varying too fast over the entation method in later hardware cost than the existing design, but it

2.4 Transform domain processing

, we use a low pass filter to redu

be time variant not only AWGN effects. Furthermore, the channel is m the β lager. When β convergence to 0 which m

previous estimator. We will show the simulation results and implem chapter. We can find it only needs less additional

can get better performance in the slow fading channel.

In fact, the CFR would be a smooth curve. According to this property ce the high pass noise effect [11].

(27)

( )

p

H m

ˆ ( )p

H m

Fig. 2.9 The relationship of CFR and noise

In Fig.2.9, we can see that the relationship of CFR and noise. Because of noise we can get the red circle CFR but the perfect CFR is white circle. So the basic concept of filtering is to get a smoother CFR (blue circle) by a LPF. In theory the blue circle H mp( ) will be closer

to perfect CFR than red circleH mˆ ( )_p .

We can see that, the ener low pass band. In Fig.2.10 we can see the noise

effect at high pass band. So we can reduce the noise in high pass band by a LPF. Fig.2.11 is diagrams.

Fig. 2.10 The CFR of Rayleigh channel @ AWGN 25dB

In filtering processing, first we let the CFR through a FFT transform. The blue signal is the perfect CFR through FFT transform. The red signal is the perfect CFR add noise @ 25dB.

gy is gathered in

the filtering process flow

0 100 200 300 400 500 600 0 50 100 150 200 250 300 350 400 FFT frquency [ 0~2pi ] |F F T (H )| noise effect (25dB) 4.5

High pass band

260 270 280 290 300 310 320 0 0.5 1 1.5 2 2.5 3 3.5 4

noise effect (25dB) at high frequency

|F

F

T

(H

(28)

LPF

FFT

IFFT

ˆ ( )p H m G pˆ ( )p ( ) p G p Select ( ) p H m

Fig. 2.11 The flow diagram From section 2.3 we can get the estimated CFR Ĥp(m).

( )

1 N m

− (2-11) The noise term N(m)/Xp(m) is a zero mean Gaussian random process. Variation of the true

CFR Hp(m p(m) with respect to ploying a transform doma Ĥp(m) becomes ˆ ( ) ( ) , 0,... ( ) p p p p H m H m m N X m = + =

) within one OFDM symbols is much slower than noise term N(m)/X index m. we can use this property to separate the two components by em

domain low-pass filter where the transform domain refers to the “frequency in” in DFT-IDFT transformations. The transform domain representation of

1 2 / 0 ˆ _{( )} p ˆ _{( )} p N j mp N p p m G p H m e π − − =

=

∑

, where p∈⎡_⎣0,N_p −1⎤_{⎦ is the transform dom}

the signal component Ĝp(p) is located at the lower frequency band (around p=0

-1), while the noise term is spread over the full band (p=0,…,Np

ng can be realized by simply setting the samples in the “high pass band” to ze

ˆ ( ),0_p _c, _p _c _p 1

G p p p N p p N

ain index. As expected

and p=Np -1). The low-pass

filteri ro, that is

( ) 0, p G p otherwise ⎧ _{≤ ≤} ₋ _{≤ ≤} ₋ , (2 ⎪ = ⎨ ⎪⎩ ₁₂₎

where pc is the cutoff frequency o form domain. Such a low-pass

-f the -filter in the trans

(29)

filtering reduces the noise component by an order 2pc/Np. The cutoff frequency pc of the

f the transform domain low-pass filter is an important parameter that affects the accuracy o channel estimation. Therefore the pc can be determined from the following relation.

2 2 1 2 0 ( ) ( ) c c p c p p p p p N p p G p G p 0 ( ) p p N p R G p = = −

∑

− = + =

∑

, (2-13)

where the numerator is the energy in the pass-band, the denominator represents the total

energy,R∈

[

0.9, 0.95

]

, and G p_p( ) G

pilot based channel estimation, an efficient interpolation technique is necessary in order to estimate

te domain. The Fig.2.12 shows the 2x1D diagram. is the average value of ˆ ( )_p p of the present data symbol and several previous ones.

2.5 Interpolation process

In DVB-T pilot carriers are transmitted together with data carriers. In block-type

channel at data sub-carriers by using the channel information at pilot sub-carriers. Here we propose the two dimensional interpolation based channel estimation for mobile DVB-T/H reception. As we known, the 2D filtering complexity is much higher than 2x1D filtering, but the performance of 2D filtering is similar to 2x1D filtering [17-19]. Here we will separa interpolation in time domain and in frequency

(30)

Fig. 2.12 The 2x1D interpolation processing

2.5.1 Interpolation in time domain

In time direction, the CFR is sampled at time instants T_t =4(T_u+T_g) apart. For mobile channels the correlation between these samples is determined by the bandwidth of the Jakes spectrum with a maximum Doppler frequency f and the residual local frequency offset _d

k f

Δ remaining after synchronization. The resulting bandwidth isB_t =2(f_d + Δf_k), and the

interpolation is over-sampled by a factor of max 1

t

T

r = = with respect to the

4 ( )

t t u g

T B ⋅ ⋅ T +T

Nyquist sampling timeT_max _t

For interpolation in time domain means that the casual and non-causal taps are used. For

e e non-causal data and the more latency to do

oper

For the received carriers Ck,i, where k denotes the carrier index and i denotes the symbol

. Interpolation is only feasible if r > . 1

implem ntation aspect, we need store th

ation. Furthermore, the complexity is dominated by th ded to provide to

store the additional OFDM symbols. In other hand, in DVB-T/H systems, we can’t ignore the carrier number in one OFDM symbol (1705 or 17), and each data of subcarrier will be

plex number format.

e memory nee

68 com

(31)

index. For CFR Ĥk,i at carriers Ck,i to be estim CFR at pilot carriers

where k=12n+i*3+1, n is an integer and 0<n<142 (in 2k mode).

ated. Ĥk,i is the estimated

st

A. 1 -order predictive [17]

The CFR is predicted using the nearest 2 CFR by setting the CFR value equal to the extrapolate value of these 2 CFR value as Fig.2.13 shows.

Frequency index Current symbol i Scattered pilots Extrapolated subcarriers Time k k-3 k-6 k-9 st _{e domain}

The linear extrapo bols to

predict the CFR of

Fig. 2.13 1 -order predictive interpolation in tim

lation is adopts CFR estimated at scatter pilots in the latest 7 sym currently received symbol at those carriers.

3, 1 3, 5 6, 2 6, 6 9, 3 9, 7 5 4 6 2 4 7 3 3, 6, 9, ˆ ˆ ˆ k i k i k i k i k i k i k i k i H H H H H H H H H − − − − − − − − − − − − − − − ⎧ × − = ⎪ ⎪ ⎪ × − × ⎪ ₌ ⎨ ⎪ ⎪ × − × = ⎪ ⎪⎩ 4 k i (2-14)

In this scheme, the extrapolation uses pilots only on previously received symbols and currently receiving symbol, no additional storage are needed. Therefore, it only eeds storage for previous CFR at pilot sub-carriers

n .

(32)

B. Linear interpolation

The Linear interpolation is shown in Fig.2.14

Currently symbol i received Time Frequency index Compensating symbol (i-4) Scattered pilots Interpolated subcarriers Data stored in memory

on in time domain

The linea t 7 symbols

Fig. 2.14 Linear interpolati

r interpolation is adopts CFR estimated at scatter pilots in the lates to interpolate the CFR of compensating symbol at those carriers.

3, 1 3, 5 6, 2 6, 6 9, 3, 4 6, 4 9, 7 9, 4 3 ˆ 4 2 2 ˆ ˆ k i k i k i k i k i k i k i k i k i H H H H H H H H H − − − − − − − − − − − − − − − − − − ⎧ + × = ⎪ ⎪ ⎪ × 3 4 3 4 + × ⎪ ₌ ⎨ ⎪ ⎪ = ⎪ ⎪⎩ × + (2-15)

In this scheme, it needs storage for 3 OFDM symbols for implementation of its non-causal properties, because after compensating symbol which data didn’t compensate yet.

So the memory is quite only needs storage for

CFR

ages in table 2-1. Although both are two taps interpolation methods, but linear interpolation needs store more 3 OFDM symbols, and the latency is 3 OFDM symbols time.

large. Then, before the compensating data, it at pilot sub-carriers.

(33)

Table 2-1 storage requirem St

ents for interpolation in time domain

orage requirements (2K mode) Latency

1st_{-order predictive} _{1138 (569*2) carriers} _{0 symbols}

Linear interpolation 5684 (3*1705+569) carriers 3 symbols

2.5.2 Interpolation in frequency domain

After interpolation in time domain between scattered pilots, we can get estimated CFR every three subcarriers. Then, we use these sampled CFR to interpolate the whole CFR at the rest data subcarriers. Since the interpolation in time domain is done, the sample interval in frequency domain is from 12 fc to 3fc, where fc is the subcarrier spacing. Here, we use Linear,

Parabolic, Second-order, and Cubic, four methods for interpolation in frequency domain, where Ĥ(k) is the result of the interpolation in frequency domain, k is the sub-carrier index.

Hp(m) = H(3* <3(m+1), and

=k/3-m.

nomial int oint base-poin x(i)} can be

range form . 2.15.

m) is the CFR after interpolation in time domain, where 3m<k μ

Classical poly erpolation of an N-p t set {ti,

performed by the Lag ulas [18-19]. It shows in Fig

0( ) '( ) k 0 k k ( ) ( ) n ( ) n ( ) ( ) k k k k x y x =

∑

∏

f x =

∑

C x f x (2-16) x x x = −

∏

= 0 1 1 ( )...( )( )...( ) ) i i n 0 1 1 ( ( )...( )( )...( ) i i i i i i i n x x x x x x x x C x x −x x −x₋− x −x+₊ x −x − − − − = (2-17)

(34)

A. Linear interpolation 0 1 ˆ ( ) _p( ) _p( 1) H k =C ×H m +C₋ ×H m+ where 0 1 1 C u C₋ u = − ⎧ ⎨ ₌ ⎩ (2-17) B. ˆ ( ) H k =C ×H where Second-order interpolation 1 p(m− +1) C0×H mp( )+C−1×H mp( + 1) 2 1 1 C₁ u+ u 2 0 2 1 2 2 1 1 1 2 2 C u C₋ u u ⎧ = − ⎪ ⎪⎪ _{= −} ⎨ ⎪ ⎪ = + ⎪⎩ -18) 1 H mp( 1) C 2 H mp( 2) − − = × − + × + × + + × + here (2 C. Cubic interpolation 1 0 ˆ ( ) _p( 1) _p( ) H k C H m C H m C 2 1 3 2u 6u + − w 1 2 3 0 2 3 1 1 3 1 1 1 2 2 1 1 1 1 6 6 C u C u u u C₋ u u ⎧ = − ⎪ ⎪ ⎪ _{= −} ₋ ₊ ⎪⎪ ⎨ ⎪ ⎪ ⎪ = − + ⎪⎩ (2-19) 1 0 1 2 ˆ ( ) _p( 1) _p( ) _p( 1) _p( 2) H k =C ×H m− +C ×H m +C₋ ×H m+ +C₋ ×H m+ 1 2 2 C₋ = +u u − u ⎪ 3 2

(35)

2 where 1 1 1 C u u ⎧ = − + ⎪ (2-20)

is only 1/3 or 2/3 two kinds of values, so the taps can be calculated in advance,

E between these interpolation methods. As we know, high order tter performance than low order interpolation. But if we concern the noise effects, the MSE of high order

interpola r than low order interpolation. The criteria are MSE, and

the fo n in following equation (2-21).

2 2 2 2 2 2 {| | } { ( ) [ ] [ ] (2 [ ] [ ]) (2 [ ]) k j j j i j k k j E H H E Cj E Nj Cj E Hj CiCj E Hi E Hj Cj E Hj H H ≠ − = = + + × − × × +

∑

2 0 2 1 3 2 2 2 1 1 1 2 2 3 1 2 2 1 1 2 2 C u u C u u C u u − − ⎪ ⎪ _{= −} ₋ ⎪⎪ ⎨ ⎪ ₌ ₋ ⎪ ⎪ ⎪ = − + ⎪⎩ Here, μ

and save in the registers. Next we discuss the MS

interpolation will use more samples to get smother curves, and gets be

tion will not be always bette rmulation detail is show

2

| ( ( )) _k | }

MSE=

∑

Cj× Hj Nj+ −H

(2-21)

ferent coefficients. The coefficients are listed on table 2-2, and the

ferent in each interpolation curve, so the higher order can get better

[ ])Hj H_k

In the same channel conditions, we can find that different interpolation methods which MSE will depend on dif

relationship is listed on table 2-3.

We can find that the first term in (2-21) will enhance the noise effect with high order interpolation in comparison of ₍ 2₎

j Cj

∑

. In table 2-3 we can find the enhance term of each

method. In the formulation, the other terms effects will be dif method. In fact the CFR would be a smooth

performance without noise effects.

(ex: 2 _[ 2_] ₍₂ _{[ ] [ ])} ₍₂ j i j j Cj E Hj CiCj E Hi E Hj Cj E ≠ + × −

∑

× × )

(36)

However, the noise effect term ₍ _{Cj E Nj}2_{) [} 2_]

j

∑

will be worse with higher order

interpolation. So there will be a crossover in simulation with different SNR noise. We can use the equation (2-21) to determine the crossover point with different channels.

ssover po

e coefficients list

C2 C3

The noise term will be dominant at low SNR< crossover point, but the other term effect will be dominant at high SNR> cro int. Then we can choose the better interpolation method for different channel cases.

Table 2-2 th C0 C1 Average 0 0.5 0.5 0 Linear 0 0.3333 0.6666 0 Lagrange (2 order) -0.1111 0.8889 0.2222 0 Lagrange (3 order) -0.0617 0.7407 0.3704 -0.0494

Table 2-3 the coefficients relationship

Average Linear Lagrange (2 order) Lagrange (3 order) 2 (Cj )

∑

0.5 0.5555 0.8519 0.6921 2CiCj

∑

0.5 0.4444 0.1481 0.3078 2Cj

∑

2.0 2.0 2.0 2.0

(37)

Chapter 3 Channel Equalization Algorithms

, we in lization algorithms, and we w how the

ritical path is the complex division operation. The division model is dominant hardware cost nd power consumption in channel equalizer. So we can simplify this division model and

ow the results of saving hardware cost and power consumption in later sections.

to channel equalization

e the bandwidth into many ding. Therefore, the equalization for each subcarrier becomes simple in frequency domain, ly a one-tap equalizer to compensate the channel fading effects. In OFDM–based

.

In this chapter troduce the channel equa ill s

c a sh

3.1 Introduction

It is mentioned in Chapter 2. In OFDM system, it will divid

subcarriers, so the channel frequency response of each subcarrier can be considered as flat fa

and it is on

communication systems, the received signal R[k] can be expressed by

[ ] [ ] [ ] [ ]

R k =S k H k⋅ +N k

Where S[k] is the transmitted signal, H[k] is the CFR, and N[k] is AWGN noise. The , (3-1)

estimated signal Ŝ[k] can be obtained by dividing the estimated CFR, Ĥ[k] from channel stimation. e [ ] ˆ[ ] ˆ [ ] R k S k H k =

propose one new method to simplify divider complexity without

transferring receiving data by

, (3-2) In related research, there was other approach via changing receiving data format to achieve divider-free method [20]. Here, we keep up the full-time complex dividing operation with new approach. We

(38)

re

and a few registers to implement.

3.2

In channel equalizer, it contains a complex number division. One complex division operation includes two real number divisions. As we know, the division hardware cost is proportional to square of word-lengths, but the signal bus needs sufficient digits to represent receiving signals in order to get enough accuracy. In DVB-T/H system, it will provide higher clock rate for 64Qam and Viterbi decoder. So we can reuse the hardware by raising clock rate. Furthermore, we can optimize the saturation cases and don’t need to add word-length to get enough decimal fractions of the quotient. Then according to multi-cycles division, we can use the shift-subtraction structure to simplify the hardware efficiently.

In addition, the division gate count is about 62.8% of equalizer, and the cycle time of DVB

3.3 Proposed division scheme

First, we introduce the format notations. In complex divider, the equation can be expressed by:

currence step based algorithm [21]. In recurrence step algorithm, it only requires an adder (substracter)

Motivation

-T/H systems for 8Mhz channels is about 109ns. Due to the long cycle time and the high hardware cost of long digits dividers, we propose a low cost architecture to implement the equivalent divider. 2 2 2 2

i e

a bi

ac bd

bc ad

fi

=

+

= +

(3-3) Dynamic range:

P

∈

{2

2 2

~ 2

−

2 2

}

(3-4) Saturation point:

α

c di

c

d

c

d

+

−

+

(m n− −1) (m n− −1) 2 2 ( 1)

2

m − −n

= ±

_(3-5)

(39)

s and n is at structure is show

are (m1, n1 ll produce some

intermediate 1, 2n1).

α. When

the output da α. The complex

division includes two real ore, in order

to get n2 bits in decimal ac t n2 bits left. The dividend

beco

igh. Fig. 3.1 The format (m, n) structure

First, we define the format (m, n) of the signed number, where m is the total bit

the bits of decimal. The form n in Fig.3.1. The formats of inputs a, b, c, d,

), and the formats of outputs e, f, are (m2, n2). In this process, it wi

values like (ac + bd), (bc - ad), and (c2 + d2), which formats are (2m

Since the output can only present in dynamic range P, we define saturation point ta is out of the range P, it will be saturated at saturation point

number divisions with 2m1 bits word-length. Furtherm

curacy, so the dividend should shif

mes (2m1 + n2) bits and the divisor is (2m1) bits. And we can find in Fig.3.2, we can find

the output of single cycle division is 2m1+n2 bits which is bigger than m2 bits. These bits

present the saturation cases and over design here. It needs (2m1+n2) bits subtractor. So if we

implement the divider by single cycle division model directly, the hardware will be cost h

(40)

In proposed separate one cycle

into many cy lify the divider to

subtraction by hardware reus

it will detect if state 3, else goes to

state 2. In state 2, it will do m ration and getting the

quotient by iterations. At last, it ate 3.The state diagram

is shown in Fig.3.3.

design, the multi-cycle division,

t

he basic concept is to cles and get quotient by iterative subtraction. So we can simp

e and raising clock rate.

First, the procedure of proposed division scheme consists of three states [21]. In state 1, the result is saturated or not. If saturation occurs, it goes to

ain function including subtraction ope will output the result of division in st

detect saturation

output the result

do main function

Next operation

_{Not saturated}

Saturation

Fig. 3.3 The state diagram

As mention before, because of the format (m , n ) of output so we can detect that if the

result is sa output

imme

We determ

present ‘1’ For this

In state 1, first we let quotien t, so we let A be the dividend

after shif

so it will not be affected. In this method, the relative position of dividend and divisor is

2 2

turated in the beginning. If the result is saturated, we can get the diately. In that case, other logics will be idle for power saving.

First, we define A is the minuend, B is the subtrahend, and sub is the result of subtraction. ine the quotient by subtracting B from A. In this algorithm, the quotient can only or ‘0’, so if A is larger than two times of B, the quotient can’t represent.

reason, we must make sure that A can not be larger than two times of B in state 2. t normalize to saturation poin

(41)

exactly to get the MSB of the quotient, and we can detect the saturation case easily. We only take one cycle for saturation detection, and we can save (2m1+n2-m2) cycles.

Here, A is the dividend >> (m2-n2-1), and B is the divisor. If A is larger than B, it will

represent that the quotient is saturation, and the quotient will be the saturation point α. If A is smaller than B, it will make sure that A can not be larger than two times of B, and it will go to state 2 to get the quotient. The flow of state 1 is shown in Fig.4.

Fig. 3.4 The flow of the state 1

In state 2, we can use subtraction to determine the quotient q[k] is ‘1’ akes sure A can not be larger than two times of B e can determine it by the sign bit of the subtraction and q[k] is ‘1’, A < B, the sign bit of sub is ‘1’

sub. Then, we update A depends on the sign bit of sub to get the next bit of quotient. We can get

2-1) cycles in state 2. The flow

between parameters is listed in

or ‘0’ by binary

property. Because it m . When A ≥ B, the q[k]

will be ‘1’ else not, w result. If A ≥ B, the

sign bit of sub is ‘0’ and q[k] is ‘0’. We can

find q[k] is the inverse of the sign bit of by (sub<<1) or (A<<1)

the quotient of format

(m2, n2) one by one bit through (m of the main function in state

(42)

Fig. 3.5 The flow of the main function in state 2 Table 3-1 the parameter relationship in state2

Sub>=0 Sub<0

Sign bit of sub “0” “1”

q[k] “1” “0”

Remainder (A) Sub<<1 A<<1

In state 3, it is output stage. e last cycle of state 2,

and goes to next new division operation.

Furthermore, we should determine the clock rate of this architecture which depends on

the cycles of one operati e is for state 1 to detect

if it is saturation. The following (m2-1) cycles are for compu (m2-1) bits of quotient

excluding sign bit. The sign bit can be dete before state 2 will output the complete quotient stably in the last . So there are cles needed in operation, in other word

the ratio between mbol : m2}. Th g diagram is shown in

Fig.3

It can output the whole quotient at th

on. It will take m2 cycles totally. The first cycl

ting the

rmine . It

cycle m2 cy one

clock rate and sy rate is {1 e timin

(43)

(44)

Chapter 4 .

imulation and Performance Analysis

ter, the overall simulation platform built for DVB-T/H system will be illustrated odel and some other distortion source such as Doppler delay spread and iscussed later. Finally, the performance analysis of the proposed channel ualizer scheme and comparison with state of the art will be performed.

In order to verify the performance of the proposed channel equalizer scheme, a complete VB-T/H baseband simulation platform is constructed in Matlab. The block diagram of the

S

In this chap

first. The channel m SCO model will be d eq

4.1 Simulation Platform

D

overall simulation platform is shown as Fig. 4.1.

Fig. 4.1 Overall DVB-T/H platform

(45)

system. By adding support of 4k IFFT/FFT, in-depth interleaving, and additional TPS information, the developed DVB-T system platform can share most of the function blocks with DVB-H system at the same time. The platform is composed of transmitter, channel, and receiver. A typical transmitter that receives data from MPEG2 encoder or IP datagram is completely established. The transmitter consist the full function of FEC blocks and OFDM modulation blocks. The coding rate, interleaving mode, constellation mapping mode, IFFT length, and guard-interval length are all parameterized and able to be selected while simulation. An oversampling and pulse shaping filter is added before data entering channel to simulate discrete signal as far as continuously. The oversampling rate is also parameterized and can be chosen according to the simulation accuracy. The roll-off factor of the pulse-shaping filter is chosen as a normal value α =0.15 because it is not defined in the DVB-T/H standard.

Various distortion models are adopted in the channel model to simulate real mobile environment such as multipath fading, Doppler spread, AWGN, CFO, and SCO. In practically, there are still some imperfect effects which contain co-channel interference, adjacent-channel interference, phase noise, and common phase error caused by imperfect front-end receiving. However, the distortion of these imperfect effects is relatively smaller compared with effective time-varying channel response caused by Doppler spread, CFO, and SCO. Therefore these effects are neglected in our simulation platform.

The baseband receiver in our system platform can be divided into inner receiver and outer receiver as Fig. 4.2 shows. The inner receiver includes all of the timing and frequency

synchronization function, FFT demodulation, ch ation, equalization, and pilot

remove blocks. The outer receiver consists of

annel estim

other functional blocks that following the de-mapping. The transmission parameters extracted by TPS decoder such as constellation mapping mode and Viterbi code rate will be sent the relative blocks as control parameters. Besides, the extracted TPS parameter such as guard interval length and IFFT/FFT mode

(46)

should be checked all the time during online receiving to prevent synchronization error. Once TPS check fail occurs, the acquisition and tracking of inner receiver must be shut down and then restart all the synchronization schemes. As for bit-error-rate (BER) measurement, the DVB-T standard defines quasi error-free condition, which means less than one uncorrelated error event per hour, while the BER of the output of the Viterbi decoder is equal to _{2 10}_× −4_.

Therefore, in order to verify the overall system performance, the BER after Viterbi decoder should be measured.

Fig. 4.2 The baseband receiver design

^ ζ ^ F ε ^ I ε ^ R ε ^ δ

(47)

Fig. 4.3 shows the detail functional blocks of the inner receiver. The main functional blocks consists of symbol timing offset synchronization, carrier frequency offset synchronization, SCO synchronization, channel estimation, and equalizer, respectively. Th acquisition parts (gray color) only operate in the beginning of the receiving and then are turned off when the tracking parts work, and the tracking parts works all the time until th receiver is turned off or TPS check error occurs. In this thesis, we only focus on the performance analysis of the channel estimation and equalization scheme. The detailed discussion of other functional blocks such as timing synchronization and CFO synchronization will be neglected in this work and can be found in [22].

e

4.2 Channel Model

The typical baseband equivalent channel model for DVB-T/H system platform is shown as in Fig. 4.4. The transmitted data will pass through multipath fading, Doppler delay spread, CFO, SCO, and AWGN in turn. The effects of co-channel interference, adjacent-channel interference, phase noise, and common phase error are neglected in our simulation. In the following sections, the detailed effect of each channel distortion will be illustrated.

⊕

⊗

2

j ft

e

πΔ (1+ζ)fs

.4 Channel model of DVB-T/H system Fig. 4

4.2.1 Multipath Fading Channel Model

In wireless communication transmission, the multipath fading is caused by the reception through different paths with different time delay and power decay. In DVB-T standard, two

(48)

types of multipath fading channel model are specified [3]. The fixed reception condition is modeled

by Rayleigh floating

the

In DVB-T standard, it only provides two static channel models which is described in section 4.2.1. However, the applications in DVB-T/H systems are not only fir fix reception, but also for mobile reception. Therefore, we refer to the channel models Typical Urban 6 (TU6) and Rural Area 6 (RA6) in GSM COST 207 project [23]. The two single-transmitter

(50)

profiles come from the set defined by the COST 207 project (GSM transmission). The technical specification of COST207 describes the equipment and techniques used to measure the channel characteristics over typical bandwidths of 10~20 MHz at near 900MHz. Therefore, the COST207 profiles are applicable to the DVB-T transmission situations. The detailed value of these parameters is listed in table 4-1 and table 4-2. The Fig4.6 shows the TU6 model, the Doppler spectrum filter will introduce in next section.

Fig. 4.6 TU6 model

Table 4-1 Typical Urban Reception (TU6) channel model

Tap number Delay(us) Power(dB) Doppler spectrum

1 0 -3 Rayleigh 2 0.2 0 Rayleigh 3 0.5 -2 Rayleigh 4 1.6 -6 Rayleigh 5 2.3 -8 Rayleigh 6 5.0 -10 Rayleigh

(51)

Table 4-2 Rural Area Reception (RA6) channel model

Tap number Delay(us) Power(dB) Doppler spectrum

1 0 0 Rice 2 0.1 -4 Ricean 3 0.2 -8 Rayleigh 4 0.3 -12 Rayleigh 5 0.4 -16 Rayleigh 6 0.5 -20 Rayleigh

4.2.3 D

trum

τ

(0)

oppler spec

types

Doppler

ay

Doppler

Attenuation

ay

Attenuation

Del

τ

(0)

Σ

j2π j2π )

_ｅ

ｅ

A. Pure Doppler

In DVB-T/H system, the reception ability in mobile environment is necessary. Hence a mobile radio channel including Doppler spread must be constructed. A simplified Doppler spread model is shown in Fig. 4.7 [24]. In the beginning, we assume a channel with a known and fixed number of paths P such as Rayleigh or Ricean with a Doppler frequency ( )k

d Fig. 4.7 Doppler spread model

應用於數位電視廣播系統之通道等化器設計

國立交通大學

電子工程學系 電子研究所碩士班

碩 士 論 文

應用於數位電視廣播系統之通道等化器設計

Channel equalizer for DVB-T/H System

學生 ： 馬英豪

指導教授 ： 李鎮宜 教授

應用於數位電視廣播系統之通道等化器設計

Channel equalizer for DVB-T/H System

研 究 生：馬英豪 Student：Ying-Hao Ma

指導教授：李鎮宜 Advisor：Chen-Yi Lee

國 立 交 通 大 學

電子工程學系 電子研究所 碩士班

碩 士 論 文

應用於數位電視廣播系統之通道等化器設計

學生：馬英豪 指導教授：李鎮宜 教授

國立交通大學

電子工程學系 電子研究所碩士班

摘要

Channel equalizer for DVB-T/H System

Student：Ying-Hao Ma Advisor：Dr. Chen-Yi Lee

Institute of Electronics Engineering

National Chiao Tung University

ABSTRACT

誌

謝

Contents

List of Figures

List of Tables

Chapter 1 .

Introduction

1.1

Motivation

1.2

Introduction to DVB-T/H system

1.3

Organization of This Thesis

Chapter 2 .

hannel Estimation Algorithms

C

2.1

Introduction to channel estimation

∑

∑

∑

Frequency

Time

CF

R

2.2

Motivation

2.3

Channel estimator for pilot signal

H k

ˆ ( )

=

Y k

( ) /

X k

( )

H



/

H

=

Y

X

H

/

H



Y

X

=

2.4

Transform domain processing

LPF

FFT

IFFT

電子工程學系電子研究所碩士班

碩士論文

學生：馬英豪

指導教授：李鎮宜教授

研究生：馬英豪 Student：Ying-Hao Ma

國立交通大學

電子工程學系電子研究所碩士班

碩士論文

學生：馬英豪指導教授：李鎮宜教授

電子工程學系電子研究所碩士班