{"product_id":"problem-based-learning-in-communication-systems-using-matlab-and-simulink-isbn-9781119060345","title":"Problem-Based Learning in Communication Systems Using MATLAB and Simulink","description":"\u003cp\u003eDesigned to help teach and understand communication systems using a classroom-tested, active learning approach.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eDiscusses communication concepts and algorithms, which are explained using simulation projects, accompanied by MATLAB and Simulink\u003c\/li\u003e \u003cli\u003eProvides step-by-step code exercises and instructions to implement execution sequences\u003c\/li\u003e \u003cli\u003eIncludes a companion website that has MATLAB and Simulink model samples and templates (password: matlab) \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003eAcknowledgments xvii\u003c\/p\u003e \u003cp\u003eNotation and List of Symbols xix\u003c\/p\u003e \u003cp\u003eList of Acronyms xxi\u003c\/p\u003e \u003cp\u003eContent-Mapping Table with Major Existing Textbooks xxiii\u003c\/p\u003e \u003cp\u003eLab Class Assignment Guide xxv\u003c\/p\u003e \u003cp\u003eAbout the Companion Website xxvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 MATLAB and Simulink Basics 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Operating on Variables and Plotting Graphs in MATLAB 1\u003c\/p\u003e \u003cp\u003e1.2 Using Symbolic Math 3\u003c\/p\u003e \u003cp\u003e1.3 Creating and Using a Script File (m-File) 4\u003c\/p\u003e \u003cp\u003e1.4\u003csup\u003e [A]\u003c\/sup\u003eUser-Defined MATLAB Function 7\u003c\/p\u003e \u003cp\u003e1.5 Designing a Simple Simulink File 8\u003c\/p\u003e \u003cp\u003e1.6 Creating a Subsystem Block 12\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Numerical Integration and Orthogonal Expansion 16\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Simple Numerical Integration 16\u003c\/p\u003e \u003cp\u003e2.2 Orthogonal Expansion 18\u003c\/p\u003e \u003cp\u003eReferences 23\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Fourier Series and Frequency Transfer Function 24\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Designing the Extended Fourier Series System 24\u003c\/p\u003e \u003cp\u003e3.2 Frequency Transfer Function of Linear Systems 25\u003c\/p\u003e \u003cp\u003e3.3 Verification of the Frequency Transfer Function of Linear Systems in Simulink 27\u003c\/p\u003e \u003cp\u003e3.4 Steady-State Response of a Linear Filter to a Periodic Input Signal 29\u003c\/p\u003e \u003cp\u003eReferences 31\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Fourier Transform 33\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 The Spectrum of Sinusoidal Signals 33\u003c\/p\u003e \u003cp\u003e4.2 The Spectrum of Any General Periodic Functions 36\u003c\/p\u003e \u003cp\u003e4.3 Analysis and Test of the Spectra of Periodic Functions 37\u003c\/p\u003e \u003cp\u003e4.4 Spectrum of a Nonperiodic Audio Signal 40\u003c\/p\u003e \u003cp\u003eReferences 44\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Convolution 45\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Sampled Time-Limited Functions 45\u003c\/p\u003e \u003cp\u003e5.2 Time-Domain View of Convolution 48\u003c\/p\u003e \u003cp\u003e5.3 Convolution with the Impulse Function 50\u003c\/p\u003e \u003cp\u003e5.4 Frequency-Domain View of Convolution 51\u003c\/p\u003e \u003cp\u003eReference 54\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Low Pass Filter and Band Pass Filter Design 55\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1\u003csup\u003e [T]\u003c\/sup\u003eAnalysis of the Spectrum of Sample Audio Signals 55\u003c\/p\u003e \u003cp\u003e6.2 Low Pass Filter Design 57\u003c\/p\u003e \u003cp\u003e6.3 LPF Operation 61\u003c\/p\u003e \u003cp\u003e6.4 \u003csup\u003e[A]\u003c\/sup\u003eBand Pass Filter Design 63\u003c\/p\u003e \u003cp\u003eReference 65\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Sampling and Reconstruction 66\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Customizing the Analog Filter Design Block to Design an LPF 66\u003c\/p\u003e \u003cp\u003e7.2 Storing and Playing Sound Data 67\u003c\/p\u003e \u003cp\u003e7.3 Sampling and Signal Reconstruction Systems 68\u003c\/p\u003e \u003cp\u003e7.4 Frequency Up-Conversion without Resorting to Mixing with a Sinusoid 75\u003c\/p\u003e \u003cp\u003eReferences 77\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Correlation and Spectral Density 78\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Generation of Pulse Signals 78\u003c\/p\u003e \u003cp\u003e8.2 Correlation Function 79\u003c\/p\u003e \u003cp\u003e8.3 Energy Spectral Density 87\u003c\/p\u003e \u003cp\u003eReferences 89\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Amplitude Modulation 90\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Modulation and Demodulation of Double Sideband-Suppressed Carrier Signals 90\u003c\/p\u003e \u003cp\u003e9.2 Effects of the Local Carrier Phase and Frequency Errors on Demodulation Performance 95\u003c\/p\u003e \u003cp\u003e9.3 \u003csup\u003e[A]\u003c\/sup\u003eDesign of an AM Transmitter and Receiver without Using an Oscillator to Generate the Sinusoidal Signal 98\u003c\/p\u003e \u003cp\u003eReference 100\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Quadrature Multiplexing and Frequency Division Multiplexing 101\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Quadrature Multiplexing and Frequency Division Multiplexing Signals and Their Spectra 101\u003c\/p\u003e \u003cp\u003e10.2 Demodulator Design 104\u003c\/p\u003e \u003cp\u003e10.3 Effects of Phase and Frequency Errors in QM Systems 105\u003c\/p\u003e \u003cp\u003eReference 108\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Hilbert Transform, Analytic Signal, and SSB Modulation 109\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Hilbert Transform, Analytic Signal, and Single-Side Band Modulation 109\u003c\/p\u003e \u003cp\u003e11.2 Generation of Analytic Signals Using the Hilbert Transform 111\u003c\/p\u003e \u003cp\u003e11.3 Generation and Spectra of Analytic and Single-Side Band Modulated Signals 114\u003c\/p\u003e \u003cp\u003e11.4 Implementation of an SSB Modulation and Demodulation System Using a Band Pass Filter 117\u003c\/p\u003e \u003cp\u003eReferences 122\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Voltage-Controlled Oscillator and Frequency Modulation 123\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 \u003csup\u003e[A]\u003c\/sup\u003eImpact of Signal Clipping in Amplitude Modulation Systems 123\u003c\/p\u003e \u003cp\u003e12.2 Operation of the Voltage-Controlled Oscillator and Its Use in an FM Transmitter 126\u003c\/p\u003e \u003cp\u003e12.3 Implementation of Narrowband FM 130\u003c\/p\u003e \u003cp\u003eReferences 134\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Phase-Locked Loop and Synchronization 135\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Phase-Locked Loop Design 135\u003c\/p\u003e \u003cp\u003e13.2 FM Receiver Design Using the PLL 142\u003c\/p\u003e \u003cp\u003e13.3 \u003csup\u003e[A]\u003c\/sup\u003eData Transmission from a Mobile Phone to a PC over the Near-Ultrasonic Wireless Channel 146\u003c\/p\u003e \u003cp\u003eReferences 150\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Probability and Random Variables 151\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Empirical Probability Density Function of Uniform Random Variables 151\u003c\/p\u003e \u003cp\u003e14.2 Theoretical PDF of Gaussian Random Variables 152\u003c\/p\u003e \u003cp\u003e14.3 Empirical PDF of Gaussian RVs 153\u003c\/p\u003e \u003cp\u003e14.4 Generating Gaussian RVs with Any Mean and Variance 155\u003c\/p\u003e \u003cp\u003e14.5 Verifying the Mean and Variance of the RV Represented by MATLAB Function randn() 155\u003c\/p\u003e \u003cp\u003e14.6 Calculation of Mean and Variance Using Numerical Integration 156\u003c\/p\u003e \u003cp\u003e14.7 \u003csup\u003e[A]\u003c\/sup\u003eRayleigh Distribution 158\u003c\/p\u003e \u003cp\u003eReferences 159\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Random Signals 160\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Integration of Gaussian Distribution and the Q-Function 160\u003c\/p\u003e \u003cp\u003e15.2 Properties of Independent Random Variables and Characteristics of Gaussian Variables 162\u003c\/p\u003e \u003cp\u003e15.3 Central Limit Theory 165\u003c\/p\u003e \u003cp\u003e15.4 Gaussian Random Process and Autocorrelation Function 168\u003c\/p\u003e \u003cp\u003eReferences 173\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Maximum Likelihood Detection for Binary Transmission 174\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Likelihood Function and Maximum Likelihood Detection over an Additive White Gaussian Noise Channel 174\u003c\/p\u003e \u003cp\u003e16.2 BER Simulation of Binary Communications over an AWGN Channel 178\u003c\/p\u003e \u003cp\u003e16.3 \u003csup\u003e[A]\u003c\/sup\u003eML Detection in Non-Gaussian Noise Environments 182\u003c\/p\u003e \u003cp\u003eReferences 183\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Signal Vector Space and Maximum Likelihood Detection I 184\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1\u003csup\u003e [T]\u003c\/sup\u003eOrthogonal Signal Set 184\u003c\/p\u003e \u003cp\u003e17.2\u003csup\u003e [T]\u003c\/sup\u003eMaximum Likelihood Detection in the Vector Space 185\u003c\/p\u003e \u003cp\u003e17.3 MATLAB Coding for MLD in the Vector Space 187\u003c\/p\u003e \u003cp\u003e17.4 MLD in the Waveform Domain 189\u003c\/p\u003e \u003cp\u003eReferences 191\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Signal Vector Space and Maximum Likelihood Detection II 192\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 Analyzing How the Received Signal Samples are Generated 192\u003c\/p\u003e \u003cp\u003e18.2 Observing the Waveforms of 4-Ary Symbols and the Received Signal 195\u003c\/p\u003e \u003cp\u003e18.3 Maximum Likelihood Detection in the Vector Space 196\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Correlator-Based Maximum Likelihood Detection 200\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e19.1 Statistical Characteristics of Additive White Gaussian Noise in the Vector Space 200\u003c\/p\u003e \u003cp\u003e19.2 Correlation-Based Maximum Likelihood Detection 205\u003c\/p\u003e \u003cp\u003eReference 208\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Pulse Shaping and Matched Filter 209\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e20.1\u003csup\u003e [T]\u003c\/sup\u003eRaised Cosine Pulses 209\u003c\/p\u003e \u003cp\u003e20.2 Pulse Shaping and Eye Diagram 210\u003c\/p\u003e \u003cp\u003e20.3 Eye Diagram after Matched Filtering 216\u003c\/p\u003e \u003cp\u003e20.4 Generating an Actual Electric Signal and Viewing the Eye Diagram in an Oscilloscope 218\u003c\/p\u003e \u003cp\u003eReferences 223\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 BER Simulation at the Waveform Level 224\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e21.1 \u003ci\u003eE\u003csub\u003eB\u003c\/sub\u003e\/N\u003c\/i\u003e\u003csub\u003e0 \u003c\/sub\u003eSetting in Baseband BPSK Simulation 224\u003c\/p\u003e \u003cp\u003e21.2 Matched Filter and Decision Variables 228\u003c\/p\u003e \u003cp\u003e21.3 Completing the Loop for BER Simulation 230\u003c\/p\u003e \u003cp\u003e21.4 \u003csup\u003e[A]\u003c\/sup\u003eEffects of the Roll-off Factor on BER Performance When There is a Symbol Timing Error 234\u003c\/p\u003e \u003cp\u003e21.5 Passband BPSK BER Simulation and Effects of Carrier Phase Errors 235\u003c\/p\u003e \u003cp\u003eReference 238\u003c\/p\u003e \u003cp\u003e\u003cb\u003e22 QPSK and Offset QPSK in Simulink 239\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e22.1 Characteristics of QPSK Signals 239\u003c\/p\u003e \u003cp\u003e22.2 Implementation of the QPSK Transmitter 241\u003c\/p\u003e \u003cp\u003e22.3 Implementation of the QPSK Receiver 243\u003c\/p\u003e \u003cp\u003e22.4 SNR Setting, Constellation Diagram, and Phase Error 245\u003c\/p\u003e \u003cp\u003e22.5 BER Simulation in Simulink Using a Built-in Function sim( ) 247\u003c\/p\u003e \u003cp\u003e22.6 Pulse Shaping and Instantaneous Signal Amplitude 249\u003c\/p\u003e \u003cp\u003e22.7 Offset QPSK 252\u003c\/p\u003e \u003cp\u003eReferences 253\u003c\/p\u003e \u003cp\u003e\u003cb\u003e23 Quadrature Amplitude Modulation in Simulink 254\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e23.1 Checking the Bit Mapping of Simulink QAM Modulator 254\u003c\/p\u003e \u003cp\u003e23.2 Received QAM Signal in AWGN 258\u003c\/p\u003e \u003cp\u003e23.3 Design of QAM Demodulator 260\u003c\/p\u003e \u003cp\u003e23.4 BER Simulation 262\u003c\/p\u003e \u003cp\u003e23.5 Observing QAM Signal Trajectory Using an Oscilloscope 266\u003c\/p\u003e \u003cp\u003eReferences 268\u003c\/p\u003e \u003cp\u003e\u003cb\u003e24 Convolutional Code 269\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e24.1 Encoding Algorithm 269\u003c\/p\u003e \u003cp\u003e24.2 Implementation of Maximum Likelihood Decoding Based on Exhaustive Search 273\u003c\/p\u003e \u003cp\u003e24.3 Viterbi Decoding (Trellis-Based ML Decoding) 277\u003c\/p\u003e \u003cp\u003e24.4 BER Simulation of Coded Systems 284\u003c\/p\u003e \u003cp\u003eReferences 287\u003c\/p\u003e \u003cp\u003e\u003cb\u003e25 Fading Diversity and Combining 289\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e25.1 Rayleigh Fading Channel Model and the Average BER 289\u003c\/p\u003e \u003cp\u003e25.2 BER Simulation in the Rayleigh Fading Environment 292\u003c\/p\u003e \u003cp\u003e25.3 Diversity 295\u003c\/p\u003e \u003cp\u003e25.4 Combining Methods 296\u003c\/p\u003e \u003cp\u003eReferences 300\u003c\/p\u003e \u003cp\u003e\u003cb\u003e26 Orthogonal Frequency Division Multiplexing in AWGN Channels 302\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e26.1 Orthogonal Complex Sinusoid 302\u003c\/p\u003e \u003cp\u003e26.2 Generation of Orthogonal Frequency Division Multiplexing Signals 303\u003c\/p\u003e \u003cp\u003e26.3 Bandwidth Efficiency of OFDM Signals 306\u003c\/p\u003e \u003cp\u003e26.4 Demodulation of OFDM Signals 307\u003c\/p\u003e \u003cp\u003e26.5 BER Simulation of OFDM Systems 307\u003c\/p\u003e \u003cp\u003eReferences 310\u003c\/p\u003e \u003cp\u003e\u003cb\u003e27 Orthogonal Frequency Division Multiplexing over Multipath Fading Channels 311\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e27.1 Multipath Fading Channels 311\u003c\/p\u003e \u003cp\u003e27.2 Guard Interval, CP, and Channel Estimation 314\u003c\/p\u003e \u003cp\u003e27.3 BER Simulation of OFDM Systems over Multipath Fading Channels 319\u003c\/p\u003e \u003cp\u003eReferences 323\u003c\/p\u003e \u003cp\u003e\u003cb\u003e28 MIMO System—Part I: Space Time Code 324\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e28.1 System Model 324\u003c\/p\u003e \u003cp\u003e28.2 Alamouti Code 327\u003c\/p\u003e \u003cp\u003e28.3 Simple Detection of Alamouti Code 330\u003c\/p\u003e \u003cp\u003e28.4 \u003csup\u003e[A]\u003c\/sup\u003eVarious STBCs, Their Diversity Orders, and Their Rates 334\u003c\/p\u003e \u003cp\u003eReferences 335\u003c\/p\u003e \u003cp\u003e\u003cb\u003e29 MIMO System—Part II: Spatial Multiplexing 336\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e29.1 MIMO for Spatial Multiplexing 336\u003c\/p\u003e \u003cp\u003e29.2 MLD Based on Exhaustive Search for SM MIMO 337\u003c\/p\u003e \u003cp\u003e29.3 Zero Forcing Detection 340\u003c\/p\u003e \u003cp\u003e29.4 Noise Enhancement of ZF Detection 341\u003c\/p\u003e \u003cp\u003e29.5 Successive Interference Cancellation Detection 343\u003c\/p\u003e \u003cp\u003e29.6 BER Simulation of ZF, SIC, OSIC, and ML Detection Schemes 347\u003c\/p\u003e \u003cp\u003e29.7 Relationship among the Number of Antennas Diversity and Data Rate 350\u003c\/p\u003e \u003cp\u003eReferences 352\u003c\/p\u003e \u003cp\u003e\u003cb\u003e30 Near-Ultrasonic Wireless Orthogonal Frequency Division Multiplexing Modem Design 353\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e30.1 Image File Transmission over a Near-Ultrasonic Wireless Channel 353\u003c\/p\u003e \u003cp\u003e30.2 Analysis of OFDM Transmitter Algorithms and the Transmitted Signals 355\u003c\/p\u003e \u003cp\u003e30.3 Analysis of OFDM Receiver Algorithms and the Received Signals 357\u003c\/p\u003e \u003cp\u003e30.4 Effects of System Parameters on the Performance 361\u003c\/p\u003e \u003cp\u003eIndex 363\u003c\/p\u003e \u003cp\u003e\u003cb\u003eKwonhue Cho\u003c\/b\u003e\u003cb\u003ei\u003c\/b\u003e is a Professor in the Department of Information and Communication Engineering and the Principal Director of Broadband Wireless Communication (BWC) Laboratory at \u003cb\u003eYeungnam University\u003c\/b\u003e, \u003cb\u003eKorea\u003c\/b\u003e. His research areas include efficient multiple access, diversity schemes, and cooperative communications for Fifth-Generation (5G) and beyond systems. He is the inventor of FADAC-OFDM and PSW (Properly scrambled Walsh) codes.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eHuaping Liu\u003c\/b\u003e is a Professor with the School of Electrical Engineering and Computer Science at \u003cb\u003eOregon State University\u003c\/b\u003e, \u003cb\u003eUSA\u003c\/b\u003e. He was formerly a cellular network radio frequency systems engineer specializing on modeling, simulating, optimizing, and testing various digital communication systems. Dr. Liu received his PhD in Electrical Engineering at New Jersey Institute of Technology, USA.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eDesigned to help teach and understand communication systems using a classroom-tested, active learning approach.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThis book covers the basic concepts of signals, and analog and digital communications, to more complex simulations in communication systems.  \u003ci\u003eProblem-Based Learning in Communication Systems Using MATLAB and Simulink\u003c\/i\u003e begins by introducing MATLAB and Simulink to prepare readers who are unfamiliar with these environments in order to tackle projects and exercises included in this book. Discussions on simulation of signals, filter design, sampling and reconstruction, and analog communications are covered next. The book concludes by covering advanced topics such as Viterbi decoding, OFDM and MIMO. In addition, this book contains examples of how to convert waveforms, constructed in simulation, into electric signals. It also includes problems illustrating how to complete actual wireless communications in the band near ultrasonic frequencies.\u003c\/p\u003e \u003cp\u003eA content-mapping table is included in this book to help instructors easily find lab projects for communications, wireless communications, and signal and systems classes.\u003c\/p\u003e \u003cp\u003eSpecial features of this book:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eDiscusses communication concepts and algorithms, which are explained using simulation projects, accompanied by MATLAB and Simulink\u003c\/li\u003e \u003cli\u003eProvides step-by-step code exercises and instructions to implement execution sequences\u003c\/li\u003e \u003cli\u003eIncludes a companion website that has MATLAB and Simulink model samples and templates (link provided below)\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThis book is intended for students and instructors, enrolled in or teaching communications systems, analog and digital communications, and wireless communication courses.\u003c\/p\u003e","brand":"Wiley-IEEE Press","offers":[{"title":"Default Title","offer_id":47989858697445,"sku":"NP9781119060345","price":114.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119060345.jpg?v=1761785702","url":"https:\/\/k12savings.com\/es\/products\/problem-based-learning-in-communication-systems-using-matlab-and-simulink-isbn-9781119060345","provider":"K12savings","version":"1.0","type":"link"}