DOCSLIB.ORG

Communication Systems

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Communication Systems Communication Systems en.wikibooks.org January 26, 2014 On the 28th of April 2012 the contents of the English as well as German Wikibooks and Wikipedia projects were licensed under Creative Commons Attribution-ShareAlike 3.0 Unported license. A URI to this license is given in the list of figures on page 171. If this document is a derived work from the contents of one of these projects and the content was still licensed by the project under this license at the time of derivation this document has to be licensed under the same, a similar or a compatible license, as stated in section 4b of the license. The list of contributors is included in chapter Contributors on page 167. The licenses GPL, LGPL and GFDL are included in chapter Licenses on page 177, since this book and/or parts of it may or may not be licensed under one or more of these licenses, and thus require inclusion of these licenses. The licenses of the figures are given in the list of figures on page 171. This PDF was generated by the LATEX typesetting software. The LATEX source code is included as an attachment (source.7z.txt) in this PDF file. To extract the source from the PDF file, you can use the pdfdetach tool including in the poppler suite, or the http://www. pdflabs.com/tools/pdftk-the-pdf-toolkit/ utility. Some PDF viewers may also let you save the attachment to a file. After extracting it from the PDF file you have to rename it to source.7z. To uncompress the resulting archive we recommend the use of http://www.7-zip.org/. The LATEX source itself was generated by a program written by Dirk Hünniger, which is freely available under an open source license from http://de.wikibooks.org/wiki/Benutzer:Dirk_Huenniger/wb2pdf. Contents 0.1 Introduction .................................... 1 1 Communications Basics 3 1.1 Wideband vs Narrowband ............................ 3 1.2 Frequency Spectrum ............................... 3 1.3 Time Division Multiplexing ........................... 3 1.4 Zero Substitutions ................................ 10 1.5 Benefits of TDM ................................. 15 1.6 Synchronous TDM ................................ 15 1.7 Statistical TDM ................................. 16 1.8 Packets ...................................... 19 1.9 Duty Cycles .................................... 19 1.10 Introduction .................................... 19 1.11 What is FDM? .................................. 21 1.12 Benefits of FDM ................................. 23 1.13 Examples of FDM ................................ 23 1.14 Orthogonal FDM ................................. 23 1.15 Voltage Controlled Oscillators (VCO) ..................... 23 1.16 Phase-Locked Loops ............................... 24 1.17 Purpose of VCO and PLL ............................ 24 1.18 Varactors ..................................... 24 1.19 Further reading .................................. 24 1.20 What is an Envelope Filter? ........................... 24 1.21 Circuit Diagram ................................. 25 1.22 Positive Voltages ................................. 25 1.23 Purpose of Envelope Filters ........................... 25 1.24 Definition ..................................... 26 1.25 Types of Modulation ............................... 26 1.26 Why Use Modulation? .............................. 27 1.27 Examples ..................................... 27 1.28 non-sinusoidal modulation ............................ 27 1.29 further reading .................................. 28 1.30 What are They? ................................. 28 1.31 What are the Pros and Cons? .......................... 28 1.32 Sampling and Reconstruction .......................... 29 1.33 further reading .................................. 29 1.34 Twisted Pair Wire ................................ 30 1.35 Coaxial Cable ................................... 30 1.36 Fiber Optics .................................... 31 1.37 Wireless Transmission .............................. 31 1.38 Receiver Design .................................. 32 III Contents 1.39 The Simple Receiver ............................... 32 1.40 The Optimal Receiver .............................. 32 1.41 Conclusion ..................................... 33 1.42 further reading .................................. 33 2 Analog Modulation 35 2.1 Analog Modulation Overview .......................... 35 2.2 Types of Analog Modulation .......................... 35 2.3 The Breakdown .................................. 35 2.4 How we Will Cover the Material ........................ 35 2.5 Amplitude Modulation .............................. 36 2.6 AM Demodulation ................................ 56 2.7 AM-DSBSC .................................... 60 2.8 AM-DSB-C .................................... 62 2.9 AM-SSB ...................................... 63 2.10 AM-VSB ..................................... 70 2.11 Frequency Modulation .............................. 71 2.12 FM Transmission Power ............................. 77 2.13 FM Transmitters ................................. 78 2.14 FM Receivers ................................... 78 2.15 Phase Modulation ................................ 78 2.16 Wrapped/Unwrapped Phase ........................... 88 2.17 PM Transmitter ................................. 88 2.18 PM Receiver ................................... 88 2.19 Concept ...................................... 89 2.20 Instantaneous Phase ............................... 89 2.21 Instantaneous Frequency ............................. 89 2.22 Determining FM or PM ............................. 90 2.23 Bandwidth .................................... 90 2.24 The Bessel Function ............................... 91 2.25 Carson's Rule ................................... 91 2.26 Demodulation: First Step ............................ 91 2.27 Filtered Noise ................................... 92 2.28 Noise Analysis .................................. 92 3 Transmission 95 3.1 Electromagnetic Spectrum ............................ 95 3.2 Radio Waves ................................... 95 3.3 Fading and Interference ............................. 101 3.4 Reflection ..................................... 105 3.5 Diffraction ..................................... 106 3.6 Path Loss ..................................... 106 3.7 Rayleigh Fading .................................. 106 3.8 Rician Fading ................................... 106 3.9 Doppler Shift ................................... 106 3.10 Types of Noise .................................. 106 3.11 Noise Temperature ................................ 111 3.12 Noise Figure .................................... 111 IV Contents 3.13 Receiver Sensitivity ................................ 114 3.14 Cascaded Systems ................................ 114 3.15 Transmission Line Equation . 115 3.16 The Frequency Domain ............................. 122 3.17 Characteristic Impedance ............................ 126 3.18 Isotropic Antennas ................................ 126 3.19 Directional Antennas ............................... 128 3.20 Link-Budget Analysis .............................. 129 3.21 Further reading .................................. 130 3.22 Technical categorisations ............................. 130 3.23 Multipathing ................................... 130 3.24 Application systems ............................... 130 4 Digital Modulation 131 4.1 Definition ..................................... 131 4.2 Square Wave ................................... 131 4.3 Other pulses .................................... 132 4.4 Sinc ........................................ 132 4.5 Comparison .................................... 132 4.6 slew-rate-limited pulses ............................. 132 4.7 Raised-Cosine Rolloff ............................... 132 4.8 Binary symmetric pulses ............................. 133 4.9 Asymmetric Pulses ................................ 133 4.10 Asymmetric Correlation Receiver . 133 4.11 References ..................................... 133 4.12 What is "Keying?" ................................ 134 4.13 Amplitude Shift Keying ............................. 134 4.14 Frequency Shift Keying ............................. 135 4.15 Phase Shift Keying ................................ 136 4.16 Binary Transmitters ............................... 137 4.17 Binary Receivers ................................. 137 4.18 Pronunciation ................................... 137 4.19 Example: 4-ASK ................................. 137 4.20 Bits Per Symbol ................................. 137 4.21 QPSK ....................................... 138 4.22 CPFSK (MSK) .................................. 138 4.23 DPSK ....................................... 138 4.24 For further reading ................................ 138 4.25 Definition ..................................... 138 4.26 Constellation Plots ................................ 139 4.27 Benefits of QAM ................................. 139 4.28 For further reading ................................ 139 4.29 Definition ..................................... 140 4.30 Constellation Plots ................................ 140 4.31 Benefits of QAM ................................. 141 4.32 For further reading ................................ 141 4.33 Line Codes .................................... 141 4.34 Non-Return to Zero Codes (NRZ) . 144 V Introduction 4.35 Manchester .................................... 146 4.36 Differential Codes ................................. 146 4.37 Comparison .................................... 147 4.38 further reading .................................
Load more

Recommended publications
  • Digital Transmission 01204325 Data Communications and Computer Networks
    Digital Transmission 01204325 Data Communications and Computer Networks Chaiporn Jaikaeo Department of Computer Engineering Kasetsart University Based on lecture materials from Data Communications and Networking, 5th ed., Behrouz A. Forouzan, McGraw Hill, 2012. Revised 2021-05-07 Outline • Line coding • Encoding considerations • DC components in signals • Synchronization • Various line coding methods • Analog to digital conversion 2 Line Coding • Process of converting binary data to digital signal 3 Signal vs. Data Elements 1 data element = 1 symbol 4 Encoding Considerations • Signal spectrum ◦ Lack of DC components ◦ Lack of high frequency components • Clocking/synchronization • Error detection • Noise immunity • Cost and complexity 5 DC Components • DC components in signals are not desirable ◦ Cannot pass thru certain devices ◦ Leave extra (useless) energy on the line ◦ Voltage built up due to stray capacitance in long cables v Signal with t DC component v Signal without t DC component 6 Synchronization • To correctly decode a signal, receiver and sender must agree on bit interval 0 1 0 0 1 1 0 1 Sender sends: v 01001101 t 0 1 0 0 0 1 1 0 1 1 Receiver sees: v 0100011011 t 7 Providing Synchronization • Separate clock wire Sender data Receiver clock • Self-synchronization 0 1 0 0 1 1 0 1 v t 8 Line Coding Methods • Unipolar ◦ Uses only one voltage level (one side of time axis) • Polar ◦ Uses two voltage levels (negative and positive) ◦ E.g., NRZ, RZ, Manchester, Differential Manchester • Bipolar ◦ Uses three voltage levels (+, 0, and
    [Show full text]
  • Multi-Antenna Non-Line-Of-Sight Identification Techniques for Target Localization in Mobile Ad-Hoc Networks
    Michigan Technological University Digital Commons @ Michigan Tech Dissertations, Master's Theses and Master's Dissertations, Master's Theses and Master's Reports - Open Reports 2011 Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks Wenjie Xu Michigan Technological University Follow this and additional works at: https://digitalcommons.mtu.edu/etds Part of the Electrical and Computer Engineering Commons Copyright 2011 Wenjie Xu Recommended Citation Xu, Wenjie, "Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad- hoc networks", Dissertation, Michigan Technological University, 2011. https://doi.org/10.37099/mtu.dc.etds/58 Follow this and additional works at: https://digitalcommons.mtu.edu/etds Part of the Electrical and Computer Engineering Commons MULTI-ANTENNA NON-LINE-OF-SIGHT IDENTIFICATION TECHNIQUES FOR TARGET LOCALIZATION IN MOBILE AD-HOC NETWORKS By Wenjie Xu A DISSERTATION Submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY (Electrical Engineering) MICHIGAN TECHNOLOGICAL UNIVERSITY 2011 c 2011 Wenjie Xu This dissertation, "Multi-Antenna Non-Line-Of-Sight Identification Techniques for Target Localization in Mobile Ad-hoc Networks," is hereby approved in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY IN THE FIELD OF ELEC- TRICAL ENGINEERING. Department of Electrical and Computer Engineering Signatures: Dissertation Advisor Dr. Seyed A. (Reza) Zekavat Committee Member Dr. Daniel R. Fuhrmann Committee Member Dr. Zhi (Gerry) Tian Committee Member Dr. Vladimir D. Tonchev Department Chair Dr. Daniel R. Fuhrmann Date Contents List of Figures ..................................... vii List of Tables ...................................... xi Acknowledgments ...................................xiii Abstract ........................................ xv 1 Introduction ...................................
    [Show full text]
  • An Efficient Utilization of Power Spectrum Density for Smart Cities
    sensors Article Moving towards IoT Based Digital Communication: An Efficient Utilization of Power Spectrum Density for Smart Cities Tariq Ali 1,*, Abdullah S. Alwadie 1, Abdul Rasheed Rizwan 2, Ahthasham Sajid 3 , Muhammad Irfan 1 and Muhammad Awais 4 1 Electrical Engineering Department, College of Engineering, Najran University, Najran 61441, Saudi Arabia; [email protected] (A.S.A.); [email protected] (M.I.) 2 Department of Computer Science, Punjab Education System, Depaalpur 56180, Pakistan; [email protected] 3 Department of Computer Science, Faculty of ICT, Balochistan University of Information Technology Engineering and Management Sciences, Quetta 87300, Pakistan; [email protected] 4 School of Computing and Communications, Lancaster University, Bailrigg, Lancaster LA1 4YW, UK; [email protected] * Correspondence: [email protected] Received: 8 April 2020; Accepted: 14 May 2020; Published: 18 May 2020 Abstract: The future of the Internet of Things (IoT) is interlinked with digital communication in smart cities. The digital signal power spectrum of smart IoT devices is greatly needed to provide communication support. The line codes play a significant role in data bit transmission in digital communication. The existing line-coding techniques are designed for traditional computing network technology and power spectrum density to translate data bits into a signal using various line code waveforms. The existing line-code techniques have multiple kinds of issues, such as the utilization of bandwidth, connection synchronization (CS), the direct current (DC) component, and power spectrum density (PSD). These highlighted issues are not adequate in IoT devices in smart cities due to their small size.
    [Show full text]
  • 4.1 DIGITAL-TO-DIGITAL CONVERSION in Chapter 3, We Discussed Data and Signals
    A computer network is designed to send information from one point to another. This information needs to be converted to either a digital signal or an analog signal for trans• mission. In this chapter, we discuss the first choice, conversion to digital signals; in Chapter 5, we discuss the second choice, conversion to analog signals. We discussed the advantages and disadvantages of digital transmission over analog transmission in Chapter 3. In this chapter, we show the schemes and techniques that we use to transmit data digitally. First, we discuss digital-to-digital conversion tech• niques, methods which convert digital data to digital signals. Second, we discuss analog- to-digital conversion techniques, methods which change an analog signal to a digital signal. Finally, we discuss transmission modes. 4.1 DIGITAL-TO-DIGITAL CONVERSION In Chapter 3, we discussed data and signals. We said that data can be either digital or analog. We also said that signals that represent data can also be digital or analog. In this section, we see how we can represent digital data by using digital signals. The conver• sion involves three techniques: line coding, block coding, and scrambling. Line coding is always needed; block coding and scrambling may or may not be needed. Line Coding Line coding is the process of converting digital data to digital signals. We assume that data, in the form of text, numbers, graphical images, audio, or video, are stored in com• puter memory as sequences of bits (see Chapter 1). Line coding converts a sequence of bits to a digital signal. At the sender, digital data are encoded into a digital signal; at the receiver, the digital data are recreated by decoding the digital signal.
    [Show full text]
  • UNIT: 3 Digital and Analog Transmission
    UNIT: 3 Digital and Analog Transmission DIGITAL-TO-ANALOG CONVERSION Digital-to-analog conversion is the process of changing one of the characteristics of an analog signal based on the information in digital data. Figure 5.1 shows the relationship between the digital information, the digital-to-analog modulating process, and the resultant analog signal. A sine wave is defined by three characteristics: amplitude, frequency, and phase. When we vary anyone of these characteristics, we create a different version of that wave. So, by changing one characteristic of a simple electric signal, we can use it to represent digital data. Before we discuss specific methods of digital-to-analog modulation, two basic issues must be reviewed: bit and baud rates and the carrier signal. Aspects of Digital-to-Analog Conversion Before we discuss specific methods of digital-to-analog modulation, two basic issues must be reviewed: bit and baud rates and the carrier signal. Data Element Versus Signal Element Data element is the smallest piece of information to be exchanged, the bit. We also defined a signal element as the smallest unit of a signal that is constant. Data Rate Versus Signal Rate We can define the data rate (bit rate) and the signal rate (baud rate). The relationship between them is S= N/r baud where N is the data rate (bps) and r is the number of data elements carried in one signal element. The value of r in analog transmission is r =log2 L, where L is the type of signal element, not the level. Carrier Signal In analog transmission, the sending device produces a high-frequency signal that acts as a base for the information signal.
    [Show full text]
  • Ber Performance of Golden Coded Mimo-Ofdm System Over Rayleigh and Rician Fading Channels
    BER PERFORMANCE OF GOLDEN CODED MIMO-OFDM SYSTEM OVER RAYLEIGH AND RICIAN FADING CHANNELS A Vamsi Krishna G Dhruva Department of ECE, LNMIIT Department of ECE, LNMIIT Jaipur-303012, India Jaipur-303012, India [email protected] [email protected] V Sai Krishna V Sinha Department of ECE, LNMIIT Fellow IEEE, Department of ECE, LNMIIT Jaipur-303012, India Jaipur-303012, India [email protected] [email protected] Abstract— In this paper, we analyze the Bit Error Rate (BER) Interference (ICI) and ensures efficient utilization of performance of Golden coded Multiple-Input Multiple-Output bandwidth. The MIMO-OFDM has a great potential to meet Orthogonal Frequency Division Multiplexing (MIMO-OFDM) up the stringent requirement for boosting up the transmit system over Rician multipath fading channel. We also compare diversity and mitigation of the detrimental effects due to the performance of the MIMO-OFDM system using Golden code frequency selective fading [5]. in Rayleigh and Rician multipath fading channels. We discuss the effects of the presence of line-of-sight (LoS) component in the Designing Space-Time Block Codes (STBC) for frequency multipath fading environment which renders the improvement in selective MIMO channels is well motivated by broadband the overall performance of the Golden coded MIMO-OFDM. applications, where multi-antenna systems have to deliver This paper discusses the performance of Golden codes in a multimedia information content at high data rates[6]. frequency selective Rician fading channel. To deal with the Furthermore, STBC are used to improve MIMO performances frequency selective fading channel, we use the OFDM by providing a temporal and spatial multiplexing modulation (Orthogonal Frequency Division Multiplexing) modulation.
    [Show full text]
  • Performance Comparison of Rayleigh and Rician Fading Channels in QAM Modulation Scheme Using Simulink Environment
    International Journal of Computational Engineering Research||Vol, 03||Issue, 5|| Performance Comparison of Rayleigh and Rician Fading Channels In QAM Modulation Scheme Using Simulink Environment P.Sunil Kumar1, Dr.M.G.Sumithra2 and Ms.M.Sarumathi3 1P.G.Scholar, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, India 2Professor, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, India 3Assistant Professor, Department of ECE, Bannari Amman Institute of Technology, Sathyamangalam, India ABSTRACT: Fading refers to the fluctuations in signal strength when received at the receiver and it is classified into two types as fast fading and slow fading. The multipath propagation of the transmitted signal, which causes fast fading, is because of the three propagation mechanisms described as reflection, diffraction and scattering. The multiple signal paths may sometimes add constructively or sometimes destructively at the receiver, causing a variation in the power level of the received signal. The received signal envelope of a fast-fading signal is said to follow a Rayleigh distribution if there is no line-of-sight between the transmitter and the receiver and a Ricean distribution if one such path is available. The Performance comparison of the Rayleigh and Rician Fading channels in Quadrature Amplitude Modulation using Simulink tool is dealt in this paper. KEYWORDS: Fading, Rayleigh, Rician, QAM, Simulink I. INTRODUCTION TO THE LINE OF SIGHT TRANSMISSION: With any communication system, the signal that is received will differ from the signal that is transmitted, due to various transmission impairments. For analog signals, these impairments introduce random modifications that degrade the signal quality. For digital data, bit errors are introduced, a binary 1 is transformed into a binary 0, and vice versa.
    [Show full text]
  • Design of Return to Zero (RZ) Bipolar Digital to Digital Encoding Data Transmission
    IOSR Journal of Engineering (IOSRJEN) www.iosrjen.org ISSN (e): 2250-3021, ISSN (p): 2278-8719 Vol. 05, Issue 02 (February. 2015), ||V4|| PP 33-36 Design of Return to Zero (RZ) Bipolar Digital to Digital Encoding Data Transmission Amna mohammed Elzain1,Abdelrasoul Jabar Alzubaidi2 Alazhery University- Engineering college Sudan University of Science and technology –Engineering College- Electronics Engineering School Abstract: - Line encoding is the method used to represent the digital information on the media. A pattern, that uses either voltage or current, is used to represent the 1s and 0s of the digital signal on the transmission link. Common types of line encoding methods used in data communications are: Unipolar line encoding, Polar line encoding, Bipolar line encoding and Manchester line encoding. This paper deals with the design of bipolar digital to digital encoding (RZ) data transmission using latch SN 74373, darlington amplifier ULN 2003-500 m A, solid state relay, personnel computer and Turbo C++ programming language ). Keywords: - Bipolar, Encoding, Digital to Digital, Latch SN 74373, Darlington Amplifier ULN 2003-500 m A, Solid State Relay (SSR) ,Turbo C++ , Computer. I. INTRODUCTION A computer network is used for communication of data from one station to another station in the network [1]. Data and signals are two of the basic building blocks of any computer network. Data must be encoded into signals before it can be transported across communication media [2]. Encoding means conversion of data into bit stream [3]. There are different encoding schemes available: Analog-to-Digital Digital-to-Analog Analog-to-Analog Digital-to-Digital Digital-to-Digital Digital-to-Digital encoding is the representation of digital information by a digital signal .
    [Show full text]
  • M-Ary Aggregate Spread Pulse Modulation in Lpwans for Iot Applications
    M-ary Aggregate Spread Pulse Modulation in LPWANs for IoT applications Alexei V. Nikitin Ruslan L. Davidchack Nonlinear LLC Sch. of Mathematics and Actuarial Sci., Wamego, Kansas, USA U. of Leicester, Leicester, UK E-mail: [email protected] E-mail: [email protected] Abstract—In low-power wide-area networks (LPWANs), various However, the designed pulse train Gˆ»:¼ given by (1) can be trade-offs among the bandwidth, data rates, and energy per bit “re-shaped” by linear filtering: have different effects on the quality of service under different ∑︁ propagation conditions (e.g. fading and multipath), interference G »:¼ = ¹Gˆ ∗ 6ˆº»:¼ = 퐴9 6ˆ»: −:9 ¼ , (3) scenarios, multi-user requirements, and design constraints. Such 9 compromises, and the manner in which they are implemented, fur- where 6ˆ»:¼ is the impulse response of the filter and the asterisk ther affect other technical aspects, such as system’s computational denotes convolution. The filter 6ˆ»:¼ can be, for example, a complexity and power efficiency. At the same time, this difference lowpass filter with a given bandwidth 퐵. If the filter 6ˆ»:¼ has a in trade-offs also adds to the technical flexibility in addressing a broader range of IoT applications. This paper addresses a sufficiently large time-bandwidth product (TBP) [4], [5], most of physical layer LPWAN approach based on the Aggregate Spread the samples in the reshaped train G »:¼ will have non-zero values, Pulse Modulation (ASPM) and provides a brief assessment of its and G »:¼ will have a much smaller PAPR than the designed properties in additive white Gaussian noise (AWGN) channel.
    [Show full text]
  • A Novel Term Weighing Scheme Towards Efficient Crawl of Textual Databases
    International Journal of Computer Engineering and Applications, Volume XII, Special Issue, May 18, www.ijcea.com ISSN 2321-3469 DIGITAL AUDIO BROADCASTING UNDER DIFFERENT MODULATION SCHEMES AND CHANNELS Arvind Venkat M 1, Biswajit Singh 2, Sharon William Raj V 3 1Department of Electronics and Communication Engineering, VTU University 2Department of Electronics and Communication Engineering, VTU University 3Department of Electronics and Communication Engineering, VTU University ABSTRACT: Digital audio broadcasting (DAB) is a digital radio standard for broadcasting digital audio radio services, used in countries across Europe, the Middle East and Asia Pacific. The DAB standard was initiated as a European research project in the 1980s. DAB is more efficient in its use of spectrum than analogue FM radio, and thus offer more radio services for the same given bandwidth. DAB is more robust with regard to noise and multipath fading for mobile listening, since DAB reception quality first degrades rapidly when the signal strength falls below a critical threshold, whereas FM reception quality degrades slowly with the decreasing signal. DAB uses a wide-bandwidth broadcast technology and typically spectra have been allocated for it in Band III (174–240 MHz) and L band (1.452–1.492 GHz), although the scheme allows for operation between 30 and 300 MHz In a digital transmission, Bit Error Rate (BER) is the percentage of bits with errors divided by the total number of bits that have been transmitted, received or processed over a given period of time. The rate is typically expressed as 10 to the negative power. The main purpose is to calculate and compare Bit Error Rate of Digital Audio Broadcast under different channels using QPSK, BPSK modulation schemes for different modes of DAB.
    [Show full text]
  • Performance of Cell-Free Massive MIMO with Rician Fading and Phase Shifts
    1 Performance of Cell-Free Massive MIMO with Rician Fading and Phase Shifts Özgecan Özdogan, Student Member, IEEE, Emil Björnson, Senior Member, IEEE, and Jiayi Zhang, Member, IEEE Abstract—In this paper, we study the uplink (UL) and down- In its canonical form, cell-free massive MIMO uses MR link (DL) spectral efficiency (SE) of a cell-free massive multiple- combining because of its low complexity. Due to the fact that input-multiple-output (MIMO) system over Rician fading chan- MR combining cannot suppress the interference well, some nels. The phase of the line-of-sight (LoS) path is modeled as a uniformly distributed random variable to take the phase-shifts APs receive more interference from other UEs than signal due to mobility and phase noise into account. Considering the power from the desired UE. The LSFD method is proposed in availability of prior information at the access points (APs), the [7] and [8] to mitigate the interference for co-located massive phase-aware minimum mean square error (MMSE), non-aware MIMO systems. This method is generalized for more realistic linear MMSE (LMMSE), and least-square (LS) estimators are spatially correlated Rayleigh fading channels with arbitrary derived. The MMSE estimator requires perfectly estimated phase knowledge whereas the LMMSE and LS are derived without it. first-layer decoders in [9], [10]. The two-layer decoding tech- In the UL, a two-layer decoding method is investigated in order nique is first adapted to cell-free massive MIMO networks in to mitigate both coherent and non-coherent interference. Closed- [11] for a Rayleigh fading scenario.
    [Show full text]
  • Simulation Model for a Frequency-Selective Land Mobile Satellite Communication Channel
    CORE Metadata, citation and similar papers at core.ac.uk Provided by International Institute for Science, Technology and Education (IISTE): E-Journals Innovative Systems Design and Engineering www.iiste.org ISSN 2222-1727 (Paper) ISSN 2222-2871 (Online) Vol 3, No.11, 2012 Simulation Model for a Frequency-Selective Land Mobile Satellite Communication Channel Zachaeus K. Adeyemo 1, Olumide O. Ajayi 2* , Festus K. Ojo 3 1. Department of Electronic and Electrical Engineering, Ladoke Akintola University of Technology, PMB 4000, Ogbomoso, Nigeria 2. Department of Electronic and Electrical Engineering, Ladoke Akintola University of Technology, PMB 4000, Ogbomoso, Nigeria 3. Department of Electronic and Electrical Engineering, Ladoke Akintola University of Technology, PMB 4000, Ogbomoso, Nigeria *E-mail of corresponding author: [email protected] Abstract This paper investigates a three-state simulation model for a frequency-selective land mobile satellite communication (LMSC) channel. Aside from ionospheric effects, the propagation channels for LMSC systems are also characterized by wideband effects due to multipath fading which makes the channels time-variant and exhibit frequency-selective distortion. Hence, an adequate knowledge and modelling of the propagation channel is necessary for the design and performance evaluation of the LMSC systems. A three-state simulation model for a frequency-selective LMSC channel, which is a combination of Rayleigh, Rician and Loo fading processes, is developed. The propagation characteristics of the proposed
    [Show full text]