Pulse Shape Filtering in Wireless Communication-A Critical Analysis
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Protection of Data Transmission Systems from the Influence of Intersymbol Interference of Signals
59 Protection of data transmission systems from the influence of intersymbol interference of signals © Volodymyr Yartsev 1 and © Dmitry Gololobov 2 1 State University of Telecommunications, Kyiv, Ukraine 2 Taras Shevchenko National University of Kyiv, Ukraine [email protected], [email protected] Abstract. The problems of creating a regenerator of an optical system for trans- mitting discrete messages with the aim of protecting against the influence of in- tersymbol interference of signals using the methods of statistical theory for a mixture of probability distributions are considered. A demodulator adaptation model that calculates the weighted sum of 4 samples of the input signal and com- pares the resulting sum with a threshold value has been created and studied. The main operations for adaptation of the regenerator during demodulation of signals distorted by intersymbol interference are assigned under certain transmission conditions, which are formulated as the task of evaluating some parameters of the probability distribution of the mixture. A block diagram of a regenerating optical signal in which an algorithm for digital processing of a mixture is imple- mented is proposed. The analysis is carried out and the requirements for the pa- rameters of the analog-to-digital converter used in the regenerator are deter- mined. The results of modeling digital processing of a discrete test message to verify the process of adaptation of the device to the influence of intersymbol dis- tortions of signals are presented. The block diagram of a digital processing device is substantiated, in which high-speed nodes that perform real-time processing are combined with a microprocessor, which implements an algorithm for adapting the regenerator to specific message transmission conditions. -
Revision of Wireless Channel
ELEC6214 Advanced Wireless Communications Networks and Systems S Chen Revision of Wireless Channel • Quick recap system block diagram Wireless CODEC MODEM Channel • Previous three lectures looked into wireless mobile channels – To understand mobile communication technologies, one needs a deep understand of mobile communication media – Two main sources of hostility in mobile media are Doppler spread and multipath – Many techniques developed are counter measures for fading and frequency selective – How spatial/angular dimension fits into wireless mobile landscape • Front end of transceiver is Modem, which faces hostile (fading and frequency selective) communication media – Next eight lectures we will have a close look into Modem 57 ELEC6214 Advanced Wireless Communications Networks and Systems S Chen Digital Modulation Overview In Digital Coding and Transmission, we learn schematic of MODEM (modulation and demodulation) • with its basic components: clock carrier pulse b(k) x(k) x(t) s(t) pulse Tx filter bits to modulat. symbols generator GT (f) clock carrier channel recovery recovery GC (f) ^ b(k) x(k)^x(t) ^s(t) ^ symbols sampler/ Rx filter AWGN demodul. + to bits decision GR (f) n(t) The purpose of MODEM: transfer the bit stream at required rate over the communication medium • reliably – Given system bandwidth and power resource 58 ELEC6214 Advanced Wireless Communications Networks and Systems S Chen Constellation Diagram • Digital modulation signal has finite states. This manifests in symbol (message) set: M = {m1, m2, ··· , mM }, where each symbol contains log2 M bits • Or in modulation signal set: S = {s1(t),s2(t), ··· sM (t)}. There is one-to-one relationship between two sets: modulation scheme M S ←→ Q • Example: BPSK, M = 2. -
Digital Baseband Modulation Outline • Later Baseband & Bandpass Waveforms Baseband & Bandpass Waveforms, Modulation
Digital Baseband Modulation Outline • Later Baseband & Bandpass Waveforms Baseband & Bandpass Waveforms, Modulation A Communication System Dig. Baseband Modulators (Line Coders) • Sequence of bits are modulated into waveforms before transmission • à Digital transmission system consists of: • The modulator is based on: • The symbol mapper takes bits and converts them into symbols an) – this is done based on a given table • Pulse Shaping Filter generates the Gaussian pulse or waveform ready to be transmitted (Baseband signal) Waveform; Sampled at T Pulse Amplitude Modulation (PAM) Example: Binary PAM Example: Quaternary PAN PAM Randomness • Since the amplitude level is uniquely determined by k bits of random data it represents, the pulse amplitude during the nth symbol interval (an) is a discrete random variable • s(t) is a random process because pulse amplitudes {an} are discrete random variables assuming values from the set AM • The bit period Tb is the time required to send a single data bit • Rb = 1/ Tb is the equivalent bit rate of the system PAM T= Symbol period D= Symbol or pulse rate Example • Amplitude pulse modulation • If binary signaling & pulse rate is 9600 find bit rate • If quaternary signaling & pulse rate is 9600 find bit rate Example • Amplitude pulse modulation • If binary signaling & pulse rate is 9600 find bit rate M=2à k=1à bite rate Rb=1/Tb=k.D = 9600 • If quaternary signaling & pulse rate is 9600 find bit rate M=2à k=1à bite rate Rb=1/Tb=k.D = 9600 Binary Line Coding Techniques • Line coding - Mapping of binary information sequence into the digital signal that enters the baseband channel • Symbol mapping – Unipolar - Binary 1 is represented by +A volts pulse and binary 0 by no pulse during a bit period – Polar - Binary 1 is represented by +A volts pulse and binary 0 by –A volts pulse. -
ECE 463 Lab 3: Pulse Shaping and Matched Filtering
UIUC ECE 463 Digital Communication Laboratory Fall 2018 ECE 463 Lab 3: Pulse Shaping and Matched Filtering 1. Introduction The objective of this lab session is to introduce the basic concepts of pulse shaping, matched filter and pulse alignment. In digital communication, the message in digital must be converted into an analog signal to be transmitted. This conversion is done by the pulse shaping filter, which changes each symbol into a suitable analog pulse. Designing the pulse shape is important because the spectrum of the pulse dictates the spectrum of the whole transmission. However, to confine the spectrum, we have to smooth the pulse with slow transition. This requires the pulse extending beyond a symbol time, which introduces inter- symbol interference (ISI). Thus, there is a trade-off between the bandwidth and the ISI of the pulse shape. After transmission, the matched filter helps to recapture the symbols from the received pulses. The matched filter is aimed at reducing the sensitivity of noise by maximizing the signal-to-noise ratio (SNR) and minimizing the ISI at the receiver. In a more realistic channel model, the receiver never knows the precise arrival time of the pulse. Therefore, the receiver must know the exact symbol timing in order to correctly demodulate the transmitted symbols from the transmitter. 1.1. Contents 1. Introduction 2. Pulse Shaping 3. Matched Filtering 4. Pulse Alignment (Symbol Timing Recovery) 1.2. Report Submit the answers, figures and the discussions on all the questions. The report is due as a hard copy at the beginning of the next lab. -
Iterative Methods for Cancellation of Intercarrier Interference in OFDM Systems
MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Iterative Methods for Cancellation of Intercarrier Interference in OFDM Systems Andreas Molisch, Martin Toeltsch, Sameer Vermani TR2007-096 August 2008 Abstract We consider orthogonal frequency-division multiplexing systems with intercarrier interference (ICI) due to insufficient cyclic prefix and/or temporal variations. Intersymbol interference (ISI) and ICI lead to an error floor in conventional receivers. We suggest two techniques for the equalization of ICI. The first, called ”operator-perturbation technique” is an iterative technique for the inversion of a linear system of equations. Alternatively, we show that serial or parallel interference cancellation can be used to drastically reduce the error floor. Simulations show that, depending on the SNR and the origin of the ICI, one of the schemes performs best. In all cases our schemes lead to a drastic reduction of the bit error rate. IEEE Transactions on Vehicular Technology, 2007 This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c Mitsubishi Electric Research Laboratories, Inc., 2008 201 Broadway, Cambridge, Massachusetts 02139 MERLCoverPageSide2 2158 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. -
Root Raised Cosine (RRC) Filters and Pulse Shaping in Communication Systems
Root Raised Cosine (RRC) Filters and Pulse Shaping in Communication Systems Erkin Cubukcu Abstract This presentation briefly discusses application of the Root Raised Cosine (RRC) pulse shaping in the space telecommunication. Use of the RRC filtering (i.e., pulse shaping) is adopted in commercial communications, such as cellular technology, and used extensively. However, its use in space communication is still relatively new. This will possibly change as the crowding of the frequency spectrum used in the space communication becomes a problem. The two conflicting requirements in telecommunication are the demand for high data rates per channel (or user) and need for more channels, i.e., more users. Theoretically as the channel bandwidth is increased to provide higher data rates the number of channels allocated in a fixed spectrum must be reduced. Tackling these two conflicting requirements at the same time led to the development of the RRC filters. More channels with wider bandwidth might be tightly packed in the frequency spectrum achieving the desired goals. A link model with the RRC filters has been developed and simulated. Using 90% power Bandwidth (BW) measurement definition showed that the RRC filtering might improve spectrum efficiency by more than 75%. Furthermore using the matching RRC filters both in the transmitter and receiver provides the improved Bit Error Rate (BER) performance. In this presentation the theory of three related concepts, namely pulse shaping, Inter Symbol Interference (ISI), and Bandwidth (BW) will be touched -
Digital Phase Modulation: a Review of Basic Concepts
Digital Phase Modulation: A Review of Basic Concepts James E. Gilley Chief Scientist Transcrypt International, Inc. [email protected] August , Introduction The fundamental concept of digital communication is to move digital information from one point to another over an analog channel. More specifically, passband dig- ital communication involves modulating the amplitude, phase or frequency of an analog carrier signal with a baseband information-bearing signal. By definition, fre- quency is the time derivative of phase; therefore, we may generalize phase modula- tion to include frequency modulation. Ordinarily, the carrier frequency is much greater than the symbol rate of the modulation, though this is not always so. In many digital communications systems, the analog carrier is at a radio frequency (RF), hundreds or thousands of MHz, with information symbol rates of many megabaud. In other systems, the carrier may be at an audio frequency, with symbol rates of a few hundred to a few thousand baud. Although this paper primarily relies on examples from the latter case, the concepts are applicable to the former case as well. Given a sinusoidal carrier with frequency: fc , we may express a digitally-modulated passband signal, S(t), as: S(t) A(t)cos(2πf t θ(t)), () = c + where A(t) is a time-varying amplitude modulation and θ(t) is a time-varying phase modulation. For digital phase modulation, we only modulate the phase of the car- rier, θ(t), leaving the amplitude, A(t), constant. BPSK We will begin our discussion of digital phase modulation with a review of the fun- damentals of binary phase shift keying (BPSK), the simplest form of digital phase modulation. -
Digital Transmission Over Baseband Channels
Principles of Communications Chapter 5: Digital Transmission through Bandlimited Channels Selected from Chapter 9.1-9.4 of Fundamentals of Communications Systems, Pearson Prentice Hall 2005, by Proakis & Salehi Meixia Tao @ SJTU 1 Topics to be Covered A/D D/A Source Channel Detector User converter converter . Digital waveforms over bandlimited baseband channels . Band-limited channel and Inter-symbol interference . Signal design for band-limited channels . System design . Channel equalization Meixia Tao @ SJTU 2 Bandlimited Channel 5MHz, 10MHz 20MHz 15MHz, 20MHz . Modeled as a linear filter with frequency response limited to certain frequency range Meixia Tao @ SJTU 3 Baseband Signalling Waveforms . To send the encoded digital data over a baseband channel, we require the use of format or waveform for representing the data . System requirement on digital waveforms . Easy to synchronize . High spectrum utilization efficiency . Good noise immunity . No dc component and little low frequency component . Self-error-correction capability . … Meixia Tao @ SJTU 4 Basic Waveforms . Many formats available. Some examples: . On-off or unipolar signaling . Polar signaling . Return-to-zero signaling . Bipolar signaling – useful because no dc . Split-phase or Manchester code – no dc Meixia Tao @ SJTU 5 0 1 1 0 1 0 0 0 1 1 On-off (unipolar) polar Return to zero bipolar Manchester Meixia Tao @ SJTU 6 Spectra of Baseband Signals . Consider a random binary sequence g0(t) - 0,g1(t) - 1 . The pulses g0(t)g1(t)occur independently with probabilities given by p and 1-p,respectively. The duration of each pulse is given by Ts. s(t) gt0 (+ 2) TS gt1(− 2) TS ∞ Ts s(t) = ∑ sn (t) n=−∞ g0 ( t− nTs ), with prob. -
Spline Pulse Shaping with Isi-Free Matched Filter Receiver
SPLINE PULSE SHAPING WITH ISI-FREE MATCHED FILTER RECEIVER Jes´usIb´a˜nez, Carlos Pantale´on, Jos´eDiez, Ignacio Santamar´ıa DICOM, ETSII y Telecomunicaci´on,Universidad de Cantabria. Avda Los Castros s.n., 39005 Santander, Spain. Tel: +34 942 201388; fax: +34 942 201488 e-mail:[email protected] ∗ ABSTRACT idea, in this paper we propose to interpolate the discrete se- Although the raised cosine pulse shaping filter is a well- quence of symbols using splines. In this way, we construct an established standard in digital communications, in many ISI-free signal when sampled at the symbol rate. Although practical systems simpler approaches are useful. In this any reconstruction technique from the communications sym- paper a new family of pulse shaping filters with zero in- bols that exactly goes through the symbols is a zero ISI tersymbol interference after matched filtering is proposed. communications signal, splines have a number of advantages The method, based on the spline interpolation of the symbol that make them an interesting choice when spectral con- data, exploits two properties of splines: that the B-spline tent as well as complexity are of concern. The main advan- coefficients can be efficiently obtained via digital filtering, tage is that any spline interpolation model of odd-order may and that the B-spline kernels of order n can be constructed be computed by filtering the sequence of symbols with two from the convolution of n + 1 rectangular pulses. These matched filters, so it is quite simple to design an optimal re- two facts suggest how to decompose the filtering operations ceiver. -
Symbol-Based Multi-Layer Iterative Successive Interference
1 Symbol-Based Multi-Layer Iterative Successive Interference Cancellation for Faster-Than-Nyquist Signaling Qiang Li12, Feng-Kui Gong12, Pei-Yang Song1 and Sheng-Hua Zhai34 1 State Key Laboratory of Integrated Service Networks (ISN), Xidian University, Shaanxi, Xi’an 710071, China 2 Collaborative innovation center of information sensing and understanding, Shaanxi, Xi’an 710071, China 3 School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China 4 CAST-Xi’an Institute of Space Radio Technology, Xi’an 710071, China Abstract—A symbol-based multi-layer iterative successive in- interference (ISI). Nevertheless, the orthogonality of Nyquist terference cancellation (MLISIC) algorithm is proposed to elim- signaling is at the cost of sacrificing the spectrum efficiency. inate the inter-symbol interference (ISI) for faster-than-Nyquist By deliberately introducing ISI, higher transmission rate and (FTN) signaling. The computational complexity of the proposed MLISIC algorithm is much lower than most existing block-based spectrum efficiency can be supported in the FTN system. estimation algorithms. By comparison with existing symbol-based Besides, FTN transmission can moderate the need for high- algorithms, the proposed MLISIC algorithm has higher estima- order modulations and low rolling factors. Thus, the adverse tion accuracy. Furthermore, by means of utilizing more accurate effect of the phase noise distortion and the timing error can symbols and elaborate length of successive interference cancella- be mitigated. -
PAM Communication System Impulse Modulator
PAM Communication System {Ex: -3,-1,1,3} Binary Impulse Pulse message Mapping Modulation sequence Modulator Shaping π Cos(2 fct) Digital data transmission using pulse amplitude modulation (PAM) Bit rate Rd bits/sec Input bits are blocked into J-bit words and mapped into the sequence of symbols mk which are selected from an alphabet of M=2J distinct voltage levels fs=Rd/J is the symbol rate (baud rate) Impulse modulator Represent the symbol sequence by the Dirac impulse train The impulse modulator block forms this function. This impulse train is applied to a transmit pulse shaping filter so that the signal is band limited to the channel bandwidth. 1 Pulse Shaping and PAM When the message signal is digital, it must be converted into an analog signal in order to be transmitted. “pulse shaping” filter changes the symbol into a suitable analog pulse Each symbol w(kT) initiates an analog pulse that is scaled by the value of the signal Pulse Shaping Compose the analog pulse train entering the pulse shaping filter as which is w(kT) for t = kT and 0 for t = kT Pulse shaping filter output 2 Pulse Shaping 4-PAM symbol sequence triggering baud-spaced rectangular pulse Intersymbol Interference If the analog pulse is wider than the time between adjacent symbols, the outputs from adjacent symbols may overlap A problem called intersymbol interference (ISI) What kind of pulses minimize the ISI? Choose a shape that is one at time kT and zero at mT for all m≠k Then, the analog waveform contains only the value from the desired input symbol and no interference from other nearby input symbols. -
Iterative Intersymbol Interference Cancellation in Vestigial Sideband Nyquist–Subcarrier Modulation System
Iterative intersymbol interference cancellation in vestigial sideband Nyquist–subcarrier modulation system Na Liu Xue Chen Cheng Ju Rongqing Hui Downloaded From: http://opticalengineering.spiedigitallibrary.org/ on 10/26/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx Optical Engineering 53(11), 116109 (November 2014) Iterative intersymbol interference cancellation in vestigial sideband Nyquist–subcarrier modulation system Na Liu,a,* Xue Chen,a Cheng Ju,a and Rongqing Huib aBeijing University of Posts and Telecommunications, State Key Lab of Information Photonics and Optical Communications, P.O. Box 128, #10 XiTuCheng Road, HaiDian District, Beijing 100876, China bUniversity of Kansas, Department of Electrical Engineering and Computer Science, 3026 Eaton Hall, 1520 W. 15th Street, Lawrence, Kansas 66045, United States Abstract. The intersymbol interference caused by dispersion, chirp, and a vestigial sideband filter in intensity modulation and a direct detection single carrier system is analyzed theoretically and numerically. An iterative nonlinear intersymbol interference cancellation technique is proposed and experimentally demonstrated in a 40- Gbps 16-QAM Mach-Zehnder modulator-based vestigial sideband intensity modulation and direct detection half- cycle Nyquist–subcarrier modulation system over a 100-km uncompensated standard single-mode fiber trans- mission for the first time. The experimental results show that 2.2-dB receiver sensitivity improvement is obtained at the forward error correction limit by using the iterative technique. © 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) [DOI: 10.1117/1.OE.53.11.116109] Keywords: intensity modulation; direct detection; vestigial sideband; intersymbol interference. Paper 141412 received Sep. 11, 2014; accepted for publication Oct. 17, 2014; published online Nov. 12, 2014.