Phương pháp tách sóng mù multiuser trong hệ thống ds cdma, mtc cdma và mtc mc cdma

I H C QU C GIA TP H TR NG CHÍ MINH I H C BÁCH KHOA @&? TR N NH T TR NG PH NG PHÁP TÁCH SÓNG MÙ MULTIUSER TRONG H TH NG DS-CDMA, MTC-CDMA VÀ MTCMC-CDMA CBHD: PGS.TS PH M H NG LIÊN Chuyên ngành : K thu t Khóa : 2006 Mã s ngành : 605270 nt LU N V N TH C S TP.H Chí Minh, tháng - 2008 CƠNG TRÌNH TR I Cán b h NG C HOÀN THÀNH I I C BÁCH KHOA C QU C GIA THÀNH PH H CHÍ MINH ng d n khoa c: (Ghi rõ h tên, c hàm, c ch ký) Cán b ch m nh n xét 1: (Ghi rõ h tên, c hàm, c ch ký) Cán b ch m nh n xét 2: (Ghi rõ h tên, Lu n v n Th c TR NG c I ov t iH I c hàm, c NG CH M ch ký) O V LU N V N TH C C BÁCH KHOA, ngày tháng n m i TR NG I H C BÁCH KHOA NG HÒA XÃ H I CH NGH A VI T NAM PHÒNG ÀO T O S H CL P-T DO - H NH PHÚC TPHCM, ngày NHI M tên tháng LU N V N TH C S c viên: TR N NH T TR NG Phái: Nam Ngày, tháng, n m sinh: 16/03/1982 N i sinh: Bình Chuyên ngành: MSHV: 01406333 I TÊN thu t n m nt nh TÀI: Ph ng pháp tách sóng mù multiser h th ng DS-CDMA, MTC-CDMA MTC-MC-CDMA II NHI M VÀ N I DUNG: - Tìm hi u t ng quan v h th ng CDMA, OFDM, MC-CDMA, MTC-CDMA - Nghiên c u ph ng pháp tách sóng mù multiuser áp d ng vào h th ng DS-CDMA, MTC-CDMA MTC-MC-CDMA - Vi t ch ng trình mơ ph ng, ánh giá k t qu nêu h III NGÀY GIAO NHI M (Ngày ký Quy t IV NGÀY HOÀN THÀNH NHI M V VÀ TÊN CÁN B H : nh giao ng phát tri n c a tài): tháng tài nm tháng n m NG D N (Ghi y h c hàm h c ): PGS.TS PH M H NG LIÊN CÁN B H NG D N CN B (H c hàm, h c v , h tên ch ký) i dung TR c ng lu n v n th c s NG PHÒNG T- MÔN QL CHUYÊN NGÀNH ã cH i H ng chuyên ngành thông qua Ngày tháng n m TR ii NG KHOA QL NGÀNH IC M N Tôi xin chân thành c m n t t c th y cô khoa i n - i n t , c bi t th y cô b môn vi n thông, nh ng ng i ã cung c p ki n th c v ng ch c làm n n t ng giúp tơi hồn thành lu n v n t t nghi p c bi t, xin g i l i c m n chân thành nh t n Cô Ph m H ng Liên s h ng d n nhi t tình c a Cô, giúp phát tri n ý t ng, cung c p ki n th c, tài li u su t th i gian th c hi n lu n v n Cu i l i cám n n ng i thân gia ình b n bè ng viên, giúp h c t p nghiên c u TP.HCM, 07/2008 Tr n Nh t Tr iii ng I NÓI U Cùng v i s phát tri n c a ngành công ngh nh i n t , tin h c , công ngh vi n thông nh ng n m v a qua phát tri n m nh m cung c p ngày nhi u lo i hình d ch v m i a d ng, an toàn, ch t l ng cao áp ng ngày t t yêu c u c a khách hàng Th k 21s ch ng t s bùng n thơng tin ó tin t c di ng óng vai trị quan tr ng Nhu c u thơng tin ngày t ng c v s l ong, ch t l lo i d ch v , i u ã thúc y th gi i pah tìm ki m m t ph thơng tin m i Và công ngh CDMA tr thành m c tiêu h thông tin di ng ng th c ng t i c a l nh v c ng th gi i Hi n nay, m ng thông tin di GSM , nhiên t c u v thông tin di ng Vi t Nam ang s d ng công ngh ng lai m ng thông tin s khơng áp ng c nhu ng, ó vi c nghiên c u tri n khai m ng thông tin di ng CDMA m t i u t t y u Các h th ng CDMA ang d n ch ng t kh n ng t tr i v dung l So v i ph ng ch t l ng v i nhi u d ch v ng ti n khác ng pháp a truy nh p truy n th ng phân chia theo th i gian TDMA phân chia theo t n s FDMA ph ng pháp truy nh p phân chia theo mã CDMA có nhi u u i m h n, ch ng h n dung l ph a ph ng m m l n h n nhi u so v i ng pháp FDMA TDMA, ch ng nhi u a truy n d li u v i t c ng, có tính b o m t cao, h tr khác nhau… Tuy nhiên, k thu t có khuynh h ng b nhi u liên chip ICI (inter-chip) Trong nh ng n m g n ây, k thu t i u ch a sóng mang, th OFDM (Orthogonal Frequency Division Multiplexing), ng g i c s d ng r ng rãi ng d ng vô n c ng nh h u n nh m kh c ph c nh ng h n ch c a vi c truy n tín hi u b ng h p b ng r ng Nhóm ký hi u h th ng OFDM s c phát song song sóng mang ph khác So v i k thu t i u ch khác, ký hi u OFDM có kho ng th i gian t v ng i dài nh ng b ng thơng h p Vì v y, kênh truy n fading có tính ch n l c t n s , ký hi u nh ch u nh h ng c a fading ph ng Bên c nh ó, sóng mang ph có búp ph ch ng l p lên làm t ng hi u qu s d ng b ng thơng th ng tính b n v ng i v i fading a h th ng ph c t p i u ch m 1993, ý t c th c hi n d dàng nh gi i c th c hi n mi n t n s ng v h th ng thông tin MC-CDMA(Multicarrier- CDMA) d a vi c k t h p k thu t CDMA OFDM ã vi c nghiên c u MC-CDMA làm t ng t c n u i mc ah ng, kh n ng tri t nhi u b ng h p, a sóng mang thu t IFFT vi c cân b ng kênh truy n thông, t ng nh ch t l i M c ính c a truy n d li u, t ng hi u qu b ng ng c a h th ng kênh truy n a nhanh chóng thu hút nhi u s quan tâm c a nhà nghiên c u m t nh ng h th ng thông tin th h m i t c c xem ng Nó c xem nh y h a h n v i kh n ng cung c p truy n cao, kh n ng a truy nh p ti t ki m b ng thơng Bên c nh s ịi h i t c ngày cao chúng cịn c n ph i có kh ng áp ng t t cho nhi u lo i d ch v khác nh video, nh t nh, d li u, tho i… Các lo i d ch v khác có nh ng yêu c u r t khác v ch t ng d ch v (QoS), ví d nh d ch v video c n có t c nh ng l i khơng c n m t t l l i bit (gói) th p, ng cl i cao th i gian th c i v i d ch v d li u t nh có nh ng yêu c u v t l l i bit (gói) th p nh ng l i không yêu c u m t s áp ng th i gian th c Xu t phát t nh ng yêu c u r t khác này, m t nh ng òi h i i v i h th ng thông tin vô n chúng ph i có kh ng cung c p nhi u lo i t c khác t ng ng v i t l l i bit khác H th ng MTC-CDMA (Multicode-CDMA) i nh m áp ng nhu c u v t c khác H th ng MTC-CDMA s d ng t p mã mà kích th thay i tùy theo t c c c a t p mã s yêu c u c i thi n ch t l ng c a h th ng MC-CDMA c ng nh h th ng MTC-CDMA kênh truy n fading, ta có s k t h p c a h th ng t o thành h th ng MTC-MC-CDMA (Multicode-Multicarrier-CDMA) H vi th ng MTC-MC-CDMA s k t h p u i m c a h th ng MC-CDMA MTCCDMA, ng th i c ng kh c ph c nh c i m c a t ng h th ng Chính v y, lu n v n ã t p trung nghiên c u v n sau: Nghiên c u h th ng DS- CDMA, MC-CDMA, MTC-CDMA, MTC-MC-CDMA ph l ng pháp tách sóng khác i v i t ng h th ng, ng c a t ng h th ng c ng nh t ng ph c bi t s t d ng ó th y c ch t ng pháp tách sóng khác C u trúc lu n v n: Lu n v n g m ph n chính: Ph n 1: Lý thuy t t ng quan h th ng thông tin di Ch ng 1: Gi i thi u v h th ng thông tin di Ch ng gi i thi u s l c v h th ng di ng ng ng t ong, ph ng pháp a truy nh p ph bi n Ch ng 2: Gi i thi u t ng quan h th ng CDMA Trong ch ng trình bày ng n g n v nguyên lý CDMA phân lo i h th ng CDMA th ng g p Các b mã dùng tr i ph nh : chu i gi ng u nhiên, chu i Gold, chu i Walsh-Hadamard, chu i Kasami… c ng ch c c p ng Ch ng 3: Các lo i nhi u nh h Trong ch ng t i h th ng CDMA ng trình bày lo i nhi u nh h CDMA nh : hi n t ng Fading, v n g n xa, hi n t ng ng n h th ng a ng, nhi u Gaussian tr ng, nhi u a truy nh p(Multiple Access Interference) Ph n 2: Gi i thi u h th ng MC-CDMA, MTC-CDMA, MTC-MCCDMA ph ng pháp tách sóng mù a user c i thi n ch t l ng c a h th ng Ch ng 4: Các h th ng MTC-CDMA, MC-CDMA MTC-MC- CDMA vii Trong ch song ki u M-ary ng gi i thi u mô hình h th ng MTC-CDMA ki u song ng th i, ch ng c ng trình bày k thu t OFDM MC- CDMA, phân tích mơ hình máy phát máy thu c a h th ng MC-CDMA c ng nh u khuy t i m c a k t h p th m nh c a hai h th ng MTC-CDMA MC-CDMA mơ hình MTC-MC-CDMA c ng c a phân tích ch ng Ch ng 5: Các ph ng pháp tách sóng h th ng DS-CDMA, MTC-CDMA MTC-MC-CDMA Trong ch ng trình bày ph a user truy n th ng ph ng pháp tách sóng n user, tách sóng ng pháp tách sóng mù a user Các ph ng pháp tách sóng mù a user s d ng k thu t SIMO v i antennas thu s d ng thu t tốn tách khơng gian nh : SVD hay PAST, PASTd Ph n 3: K t qu mô ph ng h Ch ng phát tri n c a ng 6: K t qu mô ph ng Các mô ph ng c so v i lý thuy t Ch c th c hi n Matlab 7.0 ki m ch ng k t qu thu ng s kh o sát so sánh BER c a h th ng DS- CDMA, MTC-CDMA MTC-MC-CDMA theo ph ng pháp tách sóng khác Ch tài ng 7: K t lu n h ng phát tri n c a viii tài ABSTRACT In this thesis, Blind Multiuser Detections and DS-CDMA, MCCDMA,MTC-CDMA, MTC-MC-CDMA systems are also proposed and analyzed in a frequency selective fading channel To improve quality of system is the combination of Multicode-CDMA system and Multicarrier-CDMA system By allowing each user to transmit multiple orthogonal codes, the proposed MTC-MCCDMA system can support various rates, as required by next genaration standards, and achieve spreading gain in both the time and frequency domain Non-Blind Multiuser Tranditional Detections and Blind Multiuser Detections are proposed and compared their performance via BER of systems and Blind Multiuser Detections are seen to have the best performance iv cL c Nh n xét i L i c m n .iii Abstract iv L i nói u .v M c l c ix Danh sách ch vi t t t xiv Danh sách hình v xvi Ch ng 1: Gi i thi u v h th ng thông tin di 1.1 S phát tri n c a thông tin di 1.2 Các ph ng ng .1 ng pháp a truy nh p .4 1.2.1 a truy nh p phân chia theo t n s FDMA 1.2.2 a truy nh p phân chia theo th i gianTDMA 1.2.3 a truy nh p phân chia theo mã CDMA Ch ng 2: Gi i thi u t ng quan h th ng CDMA 2.1 T ng quan 2.2 Phân lo i CDMA 2.2.1 DS-CDMA 10 2.2.2 FH-CDMA 13 2.2.3 TH-CDMA 14 ix Tài li u tham kh o [14] Nicholas D Sidiropoulos and Goran Z Dimie, “Blind multiuser detection in W-CDMA systems with large delay spread” University of Minnesota, USA [15] Richard T Causey and John R Barry “Blind multiuser detection using linear prediction” Georgia Institute of Technology, Atlanta, USA [16] Shohei Kikuchi and Akira Sano “Blind multiuser detection by accelerated subspace tracking” university of Keio, Yokahama, Japan [17] Giuseppe Ricci, Mahesh K Varanasi and Antonio De Maio “Blind multiuser detection via interference identification” IEEE transactions on communications Vol.50.NO.7, July 2002 [18] A Nafkha, C Roland, E Boutillon , “A Near-Optimal Multiuser Detector for MC-CDMA Systems using Geometrical Approach”, UBS University, France [19] Hans Dieter Schotten, Harald Elders – Bol, Axel Busboom, “Multicode – CDMA with Variable Sequence – Set”, Institue of Communications Engineering, Aachen University of Technology, Germany [20] K.Fazel, S.Kaiser, “Multi-Carrier and Spread Spectrum Systems”, John Wiley & Sons, ISBN 0-470-84899-5, 2003 [21] TS Nguy n Ph m Anh D ng, “ Lý thuy t tr i ph ng d ng”, Nhà Xu t B n B u i n Hà N i, 5-2000 [22] Dergio Verdú, “Multiuser Detection”, Cambridge University Press Các trang Web: http://www.comsoc.org http://scholar.lib.vt.edu http://www.telecomlab.oulu.fi http://www.epanorama.net http://www.ee.columbia.edu http://dsonline.computer.org http://www.mathworks.com 117 Ph l c PH L C DFT (Discrete Fourier Transform) FFT (Fast Fourier Transform) Written by Paul Bourke June 1993 Introduction This document describes the Discrete Fourier Transform (DFT), that is, a Fourier Transform as applied to a discrete complex valued series The mathematics will be given and source code (written in the C programming language) is provided in the appendices Theory 105 Ph l c Continuous For a continuous function of one variable f(t), the Fourier Transform F(f) will be defined as: and the inverse transform as where j is the square root of -1 and e denotes the natural exponent Discrete Consider a complex series x(k) with N samples of the form where x is a complex number 106 Ph l c Further, assume that that the series outside the range 0, N-1 is extended N-periodic, that is, x k = xk+N for all k The FT of this series will be denoted X(k), it will also have N samples The forward transform will be defined as The inverse transform will be defined as Of course although the functions here are described as complex series, real valued series can be represented by setting the imaginary part to In general, the transform into the frequency domain will be a complex valued function, that is, with magnitude and phase The following diagrams show the relationship between the series index and the frequency domain sample index Note the functions here are only diagramatic, in general they are both complex valued series 107 Ph l c For example if the series represents a time sequence of length T then the following illustrates the values in the frequency domain Notes • The first sample X(0) of the transformed series is the DC component, more commonly known as the average of the input series • The DFT of a real series, ie: imaginary part of x(k) = 0, results in a symmetric series about the Nyquist frequency The negative frequency samples are also the inverse of the positive frequency samples • The highest positive (or negative) frequency sample is called the Nyquist frequency This is the highest frequency component that should exist in the input series for the DFT to yield "uncorrupted" results More specifically if 108 Ph l c there are no frequencies above Nyquist the original signal can be exactly reconstructed from the samples • The relationship between the harmonics returns by the DFT and the periodic component in the time domain is illustrated below 109 Ph l c DFT and FFT algorithm While the DFT transform above can be applied to any complex valued series, in practice for large series it can take considerable time to compute, the time taken 110 Ph l c being proportional to the square of the number on points in the series A much faster algorithm has been developed by Cooley and Tukey around 1965 called the FFT (Fast Fourier Transform) The only requirement of the the most popular implementation of this algorithm (Radix-2 Cooley-Tukey) is that the number of points in the series be a power of The computing time for the radix-2 FFT is proportional to So for example a transform on 1024 points using the DFT takes about 100 times longer than using the FFT, a significant speed increase Note that in reality comparing speeds of various FFT routines is problematic, many of the reported timings have more to with specific coding methods and their relationship to the hardware and operating system Sample transform pairs and relationships • The Fourier transform is linear, that is a f(t) + b g(t) -> a F(f) + b G(f) a xk + b yk -> a Xk + b Yk 111 Ph l c • Scaling relationship f(t / a) -> a F(a f) f(a t) -> F(f / a) / a • Shifting f(t + a) -> F(f) e-j pi a f • Modulation f(t) ej pi a t -> F(t - a) • Duality Xk -> (1/N) xN-k Applying the DFT twice results in a scaled, time reversed version of the original series • The transform of a constant function is a DC value only 112 Ph l c • The transform of a delta function is a constant • The transform of an infinite train of delta functions spaced by T is an infinite train of delta functions spaced by 1/T • The transform of a cos function is a positive delta at the appropriate positive and negative frequency • The transform of a sin function is a negative complex delta function at the appropriate positive frequency and a negative complex delta at the appropriate negative frequency 113 Ph l c • The transform of a square pulse is a sinc function More precisely, if f(t) = for |t| < 0.5, and f(t) = otherwise then F(f) = sin(pi f) / (pi f) • Convolution f(t) x g(t) -> F(f) G(f) F(f) x G(f) -> f(t) g(t) xk x yk -> N Xk Yk x k yk -> (1/N) Xk x Yk Multiplication in one domain is equivalent to convolution in the other domain and visa versa For example the transform of a truncated sin function are two delta functions convolved with a sinc function, a truncated sin function is a sin function multiplied by a square pulse 114 Ph l c • The transform of a triangular pulse is a sinc2 function This can be derived from first principles but is more easily derived by describing the triangular pulse as the convolution of two square pulses and using the convolution-multiplication relationship of the Fourier Transform Sampling theorem The sampling theorem (often called "Shannons Sampling Theorem") states that a continuous signal must be discretely sampled at least twice the frequency of the highest frequency in the signal More precisely, a continuous function f(t) is completely defined by samples every 1/fs (fs is the sample frequency) if the frequency spectrum F(f) is zero for f > fs/2 fs/2 is called the Nyquist frequency and places the limit on the minimum sampling frequency when digitising a continuous sugnal If x(k) are the samples of f(t) every 1/fs then f(t) can be exactly reconstructed from these samples, if the sampling theorem has been satisfied, by 115 Ph l c where Normally the signal to be digitised would be appropriately filtered before sampling to remove higher frequency components If the sampling frequency is not high enough the high frequency components will wrap around and appear in other locations in the discrete spectrum, thus corrupting it The key features and consequences of sampling a continuous signal can be shown graphically as follows Consider a continuous signal in the time and frequency domain Sample this signal with a sampling frequency fs, time between samples is 1/fs This is equivalent to convolving in the frequency domain by delta function train with a spacing of fs 116 Ph l c If the sampling frequency is too low the frequency spectrum overlaps, and become corrupted Another way to look at this is to consider a sine function sampled twice per period (Nyquist rate) There are other sinusoid functions of higher frequencies that would give exactly the same samples and thus can't be distinguished from the frequency of the original sinusoid 117 LÝ L CH TRÍCH NGANG L C CÁ NHÂN H tên: TR N NH T TR NG Ngày tháng n m sinh: 16 tháng 03 n m 1982 i sinh: Bình nh a ch liên l c: 322/35 Nguy n Thái S n-F5-Gò V p-TpHCM QUÁ TRÌNH ÀO T O - T n m 2000 n n m 2005: h c Thành ph H Chí Minh, ngành i h c t i tr ng i H c Bách Khoa i n t – Vi n thông T t nghi p lo i i m trung bình: 7.14/10) - T n m 2006 n nay: h c Cao h c t i tr ng i H c Bách Khoa Thành ph H Chí Minh, chuyên ngành K thu t i n t Q TRÌNH CƠNG TÁC - T 3/2005 n 4/2006: cơng tác t i Công ty TMA Solutions 118 ... ng pháp tách sóng mù multiser h th ng DS-CDMA, MTC-CDMA MTC-MC-CDMA II NHI M VÀ N I DUNG: - Tìm hi u t ng quan v h th ng CDMA, OFDM, MC-CDMA, MTC-CDMA - Nghiên c u ph ng pháp tách sóng mù multiuser. .. hình MTC-MC-CDMA c ng c a phân tích ch ng Ch ng 5: Các ph ng pháp tách sóng h th ng DS-CDMA, MTC-CDMA MTC-MC-CDMA Trong ch ng trình bày ph a user truy n th ng ph ng pháp tách sóng n user, tách sóng. .. ng pháp tách sóng mù a user 67 ng pháp tách sóng mù multiuser b ng k thu t t nh n không gian con(Subspace Tracking) 67 5.3.1.1 Mơ hình d li u 67 5.3.1.2 Các b tách sóng mù