Lecture_1_-merged.pdf

Part I Elements of Digital Communications System Mobile and IoT Techniques slide 1 COMP 1247 Objectives: ❖ Study the general architecture of digital communica...

Part I Elements of Digital Communications System Mobile and IoT Techniques slide 1 COMP 1247 Objectives: ❖ Study the general architecture of digital communications system ❖ Identify the functions of each element of communications system ❖ Discuss different types of communication channels ❖ Discuss the frequency spectrum allocation Mobile and IoT Techniques slide 2 COMP 1247 Elements of Digital Communications System Input Source Channel Digital A/D Signal Encoder Encoder Modulator Channel Output Source Channel Digital Signal D/A Demodulator Decoder Decoder Mobile and IoT Techniques slide 3 COMP 1247 A/D ❖ Convert analog signal to digital format ❖ A / D conversion is achieved by using the following three operations: a) Sampling b) Quantization c) Encoding a) Sampling 0 ------- 000 1 ------- 001 2 ------- 010 3 ------- 011 4 ------- 100 5 ------- 101 6 ------- 110 7 ------- 111 b) Quantization c) Encoding Mobile and IoT Techniques slide 4 COMP 1247 Source Encoding or Data Compression ❖ The purpose of source encoder is to remove any redundancy in digital bits to minimize bandwidth requirements. ❖ It is also called “Data Compression” ❖ Data compression algorithms can be classified into two categories: ▪ Lossless compression ▪ Lossy compression ❖ Lossless compression algorithms usually exploit statistical redundancy in such a way as to represent the sender's data more concisely without error. ❖ Lossy data compression or perceptual coding, is possible if some loss of fidelity is acceptable. Mobile and IoT Techniques slide 5 COMP 1247 Channel Encoding or Forward Error Correction (FEC) ❖ The operation of the channel encoder is the inverse of the source encoder ❖ The main operation is to add redundancy in such a way that the system will be capable to detect and correct errors ❖ It is also called Forward Error Correction (FEC) ❖ The FEC can be classified into four categories: a) Repetition Coding b) Block Coding c) Convolutional Coding d) Turbo Coding Mobile and IoT Techniques slide 6 COMP 1247 Modulator ❖ Modulation is the process of converting the transmitted signal from base band frequency to RF frequency. ❖ The modulation techniques can be classified into two categories: 1. Analog Modulation 2. Digital Modulation ❖ Analog modulation can be classified into three categories: 1. AM 2. FM 3. PM ❖ Digital modulation can be classified into following categories: 1. ASK 2. FSK 3. PSK 4. QAM Mobile and IoT Techniques slide 7 COMP 1247 Communication Channels ❖ Wireline Channels ▪ Twisted-pair of wire lines (telephone lines) ▪ Coaxial cable ❖ Fiber Optic Channels ❖ Wireless Electromagnetic Channels ❖ Underwater Acoustic Channels ❖ Storage Channels Mobile and IoT Techniques slide 8 COMP 1247  Frequency Spectrum ❖ Generally, there are three types of frequencies in communication systems: 1. Baseband Frequency 2. Intermediate Frequency (IF) 3. Radiation Frequency (RF) ❖ Baseband Frequency: describes signals and systems whose range of frequencies is measured from zero to a maximum bandwidth. ❖ Intermediate Frequency: is a frequency to which a carrier frequency is shifted as an intermediate step in transmission or reception. ❖ Radiation Frequency: is the frequency that the transmitted signal will be radiated at from the antenna. ❖ Where c is the speed of the light (3x108 m/sec) and λ is the wavelength Mobile and IoT Techniques slide 9 COMP 1247 Frequency Spectrum Mobile and IoT Techniques slide 10 COMP 1247  Part II Spectrum Analyzer Mobile and IoT Techniques slide 11 COMP 1247  Outline Overview: What is spectrum analysis? What measurements do we make? Theory of Operation: Spectrum analyzer hardware Specifications: Which are important and why? Mobile and IoT Techniques slide 12 COMP 1247  Overview What is Spectrum Analysis? SPECTRUM ANALYZER 9 kHz - 26.5 GHz 8563A Mobile and IoT Techniques slide 13 COMP 1247  Overview. Types of Tests Made Modulation Noise Distortion Mobile and IoT Techniques slide 14 COMP 1247  Overview Frequency versus Time Domain Amplitude (power) Time domain Frequency Domain Measurements Measurements Mobile and IoT Techniques slide 15 COMP 1247  Overview Different Types of Analyzers Fourier Analyzer Parallel filters measured simultaneously A LCD shows full spectral display f1 f2 f Mobile and IoT Techniques slide 16 COMP 1247  Overview Different Types of Analyzers Swept Analyzer Filter 'sweeps' over range of interest A LCD shows full spectral display f1 f2 f Mobile and IoT Techniques slide 17 COMP 1247  Theory of Operation Spectrum Analyzer Block Diagram RF input attenuator IF gain IF filter mixer detector Input signal Pre-Selector Log Or Low Pass Amp Filter video filter local oscillator sweep generator Crystal Reference CRT display Mobile and IoT Techniques slide 18 COMP 1247 Theory of Operation MIXER Mixer input f LO- f sig f LO+ f sig RF IF f sig LO f sig f LO f LO Mobile and IoT Techniques slide 19 COMP 1247 Theory of Operation IF FILTER IF Filter Input Spectrum IF Bandwidth (RBW) Display Mobile and IoT Techniques slide 20 COMP 1247 Theory of Operation DETECTOR Detector amplitude "bins Positive detection: largest value " in bin displayed Negative detection: smallest value in bin displayed Sample detection: last value in bin displayed Mobile and IoT Techniques slide 21 COMP 1247 Theory of Operation Video Filter VIDEO FILTER Mobile and IoT Techniques slide 22 COMP 1247 Theory of Operation Other Components LO SWEEP GEN frequency LCD DISPLAY RF INPUT ATTENUATOR IF GAIN Mobile and IoT Techniques slide 23 COMP 1247 Theory of Operation How it all works together fs Signal Range LO Range f LO- f s f LO 0 1 2 3 (GHz) f LO+ f s fs IF filter 0 1 4 5 6 mixer fs 2 3 3.6 6.5 detector input 3.6 f IF sweep generator A LO f LO 0 1 2 3 (GHz) f 3 4 5 6 (GHz) LCD display 3.6 6.5 Mobile and IoT Techniques slide 24 COMP 1247 Theory of Operation Front Panel Operation Primary functions (Frequency, Amplitude, Span) Softkeys SPECTRUM ANALYZER 9 kHz - 26.5 GHz 8563A Control functions (RBW, sweep time, VBW) RF Input Numeric keypad Mobile and IoT Techniques slide 25 COMP 1247 Specifications SPECTRUM ANALYZER 9 kHz - 26.5 GHz 8563A Frequency Range Accuracy: Frequency & Amplitude Resolution Sensitivity Distortion Dynamic Range Mobile and IoT Techniques slide 26 COMP 1247  Coding Techniques Mobile and IoT Techniques slide 1 COMP 1247 Objectives ❖ Understand what channel coding is and why it is needed ❖ Discuss the difference between waveform and structured coding ❖ Discuss the difference between ARQ and FEC ❖ Discuss the behavior of different coding techniques ❖ Analyze linear block coding ❖ Analyze Humming code ❖ Design a single error correcting code Mobile and IoT Techniques slide 2 COMP 1247 What is Channel Coding? ❖ Class of signal transformations designed to improve communication performance and enabling the transmitted signals to better withstand against channel distortions such as noise, interference, and fading. ❖ Channel coding can be divided into two major classes: 1. Waveform coding: signal design (part of modulation techniques) 2. Structured coding: adding redundancy (will be focused on in this lecture) Mobile and IoT Techniques slide 3 COMP 1247 Waveform Coding ❖ Waveform Coding ▪ deals with transforming the transmitted waveform into “better waveform” robust to channel distortion ▪ Improving detector performance. ▪ Examples:  Antipodal signaling  Orthogonal signaling  Bi-orthogonal signaling  M-ary signaling  Trellis-coded modulation Mobile and IoT Techniques slide 4 COMP 1247 Structured Coding ❖ Structured Coding ▪ Adding redundancy bits to control the errors. ▪ There are two types of structured redundancy:  Automatic Repeat reQuest (ARQ), utilizes parity bits (redundant bits added to data) to detect that an error has been made and requires two-way link for dialogue between the transmitter and receiver.  Forward Error Correction (FEC), requires a one-way link only, since in this case the parity bits are designed for both the detection and correction of errors. Mobile and IoT Techniques slide 5 COMP 1247 Automatic Repeat reQuest (ARQ) ❖ Required a two-ways link between TX and Rx ❖ Need a buffer at the TX side (more complexity) ❖ Slower data transmission due to retransmission ❖ There are three different types of ARQ: ▪ Stop-and-Wait ARQ ▪ Go-Back-N ARQ ▪ Selective-Repeat ARQ Mobile and IoT Techniques slide 6 COMP 1247 Stop-and-Wait ARQ Mobile and IoT Techniques slide 7 COMP 1247 Go-Back-N ARQ Mobile and IoT Techniques slide 8 COMP 1247 Selective-Repeat ARQ Mobile and IoT Techniques slide 9 COMP 1247 Forward Error Correction (FEC) ❖ FEC is a structured sequences coding ▪ Adding structured redundancy (or redundant bits). ▪ The redundant bits are used to detect and correct errors. ▪ Improves overall performance of the communication system. ▪ Doesn’t require ACK. ▪ Faster than ARQ ❖ FEC Types are: ▪ Linear Codes  Repetition Codes  Block Codes  Hamming Codes  Reed-Solomon Codes  Cyclic Codes ▪ Non-Linear codes  Convolution codes  Turbo codes Mobile and IoT Techniques slide 10 COMP 1247 Repetition Codes ❖ Repetition Code (R3) & Majority Vote Decoding ▪ Binary Symmetrical Channel (BSC) 1 1-Pe 1 Input Data Encoded Data Pe 1 111 Tx Rx Pe 0 000 0 0 1-Pe ▪ The receiver will use the majority vote decoding (i.e. if the numbers of ones more the number of zeroes, then the detected bit will be 1). ▪ If the number of zeroes more than the number of ones, then the detected bit will be 0. If I/P is 1 Tx is 111 If I/P is 0 TX is 000 Received triplet 111 110 101 100 011 010 001 000 Detected bit 1 1 1 0 1 0 0 0 Mobile and IoT Techniques slide 11 COMP 1247  Repetition Codes ❖ Repetition Code (R3) & Majority Vote Decoding ❖ For uncoded date, the Bit Error Rate (BER) is: 1-Pe 1 1 𝑩𝑬𝑹𝑼𝑪 = 𝑷𝒆 Pe ▪ If 𝑃𝑒 = 0.1, 𝑡ℎ𝑒𝑛 𝑩𝑬𝑹𝑼𝑪 = 𝟎. 𝟏 Tx Rx Pe ▪ Probability of Correct 𝑷𝑪 = 𝟏 − 𝑩𝑬𝑹𝑼𝑪 = 𝟎. 𝟗 0 0 1-Pe ❖ For coded date, the BER will be: 𝑩𝑬𝑹𝑪 = 𝑷𝟑𝒆 + 𝟑𝑷𝟐𝒆 𝟏 − 𝑷𝒆 ֜ 𝑩𝑬𝑹𝑪 = 𝟑𝑷𝟐𝒆 − 𝟐𝑷𝟑𝒆 ▪ If 𝑃𝑒 = 0.1, 𝑡ℎ𝑒𝑛 𝑩𝑬𝑹𝑪 = 𝟑 𝟎. 𝟏 𝟐 − 𝟐 𝟎. 𝟏 𝟑 = 𝟎. 𝟎𝟐𝟖 ▪ Probability of Correct 𝑷𝑪 = 𝟏 − 𝑩𝑬𝑹𝑼𝑪 = 𝟎. 𝟗𝟕𝟐 !!! Mobile and IoT Techniques slide 12 COMP 1247 Linear Block Codes k n-k k bits n bits Data bits Encoder Coded Data bits FEC bits output n (block length) ❖ Step (1): the information sequence is segmented into message blocks, each block consisting of k successive bits. ❖ Step (2): the encoder add n-k bits generated from linear combination of the message bits. The result called codeward. ❖ This is called (n,k) block code or systematic linear block code. ❖ Coding Rate (CR) = k/n (also called code efficiency) ▪ CR = 1/2 , 2/3 , ¾ ❖ Smaller CR is more robust but less efficient ▪ CR = 1/2 means 100 % redundancy -- Maximum robustness Mobile and IoT Techniques slide 13 COMP 1247 Linear Block Codes Matrix Description ❖ Let the message block 𝑫 = 𝒅𝟏 , 𝒅𝟐 , … , 𝒅𝒌. Thus, there are 𝟐𝒌 distinct messages. ❖ Then the codeword will be 𝑪 = 𝒄𝟏 , 𝒄𝟐 , … , 𝒄𝒏. Thus, there are 𝟐𝒌 distinct codewords. 𝒄𝒊 = 𝒅𝒊 𝒇𝒐𝒓 𝒊 = 𝟏, 𝟐,... , 𝒌 𝒄𝒌+𝟏 = 𝒅𝟏 ∗ 𝒑𝟏𝟏 + 𝒅𝟐 ∗ 𝒑𝟐𝟏 +... +𝒅𝒌 ∗ 𝒑𝒌𝟏 𝒄𝒌+𝟐 = 𝒅𝟏 ∗ 𝒑𝟏𝟐 + 𝒅𝟐 ∗ 𝒑𝟐𝟐 +... +𝒅𝒌 ∗ 𝒑𝒌𝟐 - - - 𝒄𝒏 = 𝒅𝟏 ∗ 𝒑𝟏,𝒏−𝒌 + 𝒅𝟐 ∗ 𝒑𝟐,𝒏−𝒌 +... +𝒅𝒌 ∗ 𝒑𝒌,𝒏−𝒌 Mobile and IoT Techniques slide 14 COMP 1247 Linear Block Codes ❖ In coding theory, the additions and multiplications are performed in modulo-2 athematic. 𝟎+𝟎=𝟎 𝟎∗𝟎 =𝟎 𝟎+𝟏=𝟏 𝟎∗𝟏= 𝟎 𝟏+𝟎=𝟏 𝟏∗𝟎 =𝟎 𝟏+𝟏=𝟎 𝟏∗𝟏 =𝟏 𝟏 𝟎... 𝟎 𝒑𝟏𝟏 𝒑𝟏𝟐... 𝒑𝟏,𝒏−𝒌 𝟎 𝟏... 𝟎 𝒑𝟐𝟏 𝒑𝟐𝟐... 𝒑𝟐,𝒏−𝒌 𝒄𝟏 , 𝒄𝟐 ,... , 𝒄𝒏 = 𝒅𝟏 , 𝒅𝟐 ,... , 𝒅𝒌...... ∗ ∗............. ∗ ∗....... 𝟎 𝟎... 𝟏 𝒑𝒌𝟏 𝒑𝒌𝟐... 𝒑𝒌,𝒏−𝒌 ❖ Or 𝑪 = 𝑫 ∗ 𝑮 𝑤ℎ𝑒𝑟𝑒 𝑮 = 𝑰𝒌 𝑷𝒌,𝒏−𝒌 𝒌,𝒏 ❖ 𝑮 is called Generator Matrix Mobile and IoT Techniques slide 15 COMP 1247 Linear Block Codes ❖ Definition: the weight of the codeword is define as the number of 1s in the codeword. ❖ Theorem (1): The minimum distance 𝒅𝒎𝒊𝒏 of a linear block code is equal to the minimum weight of any nonzero word in the code. ❖ Example: The generator matrix for a (6,3) block code is given below. Find all codewords of this code? 100 011 𝐺 = 010 101 001 110 ❖ Solution: k=3 23 = 8 possible message blocks. For D=(1 1 1) 100011 ❖ 𝐶 = 𝐷𝐺 = 1 1 1 0 1 0 1 0 1 = 1 1 1 0 0 0 001110 Mobile and IoT Techniques slide 16 COMP 1247 Linear Block Codes ❖ The codewords of this code are: Messages Codewords Weight 000 000 000 0 001 001 110 3 010 010 101 3 011 011 011 4 100 100 011 3 101 101 101 4 110 110 110 4 111 111 000 3 ❖ Therefore, this code has a 𝒅𝒎𝒊𝒏 = 𝟑 Mobile and IoT Techniques slide 17 COMP 1247 Linear Block Codes ❖ Error Detection and Error Correction ▪ Associated with each (n,k) block code is a parity check matrix H, which is defined as: 𝐩𝟏𝟏 𝐩𝟐𝟏..... 𝐩𝐤𝟏 𝟏 𝟎 𝟎 𝟎... 𝟎 𝐩𝟏𝟐 𝐩𝟐𝟐..... 𝐩𝐤𝟐 𝟎 𝟏 𝟎 𝟎... 𝟎 𝐩𝟏𝟑 𝐩𝟐𝟑.... 𝐩𝐤𝟑 𝟎 𝟎 𝟏 𝟎... 𝟎 𝐇=.................................. = 𝑷𝑻 𝑰𝒏−𝒌 𝒏−𝒌 𝒙𝒏.................................................................... 𝐩𝟏,𝐧−𝐤 𝐩𝟐,𝐧−𝐤.. 𝐩𝐤,𝐧−𝐤 𝟎 𝟎 𝟎 𝟎.. 𝟏 ❖ Theorem (2): C is a codeword in the (n,k) block code generated by 𝑮 = 𝑰𝒌 𝑷 if and only if 𝑪𝑯𝑻 = 𝟎. Mobile and IoT Techniques slide 18 COMP 1247 Linear Block Codes ❖ Error Detection and Error Correction ▪ Let C be a codeword that was transmitted over a noisy channel and let R is the sum of C and an error vector E. thus: 𝑹=𝑪+𝑬 ▪ The receiver does the decoding operation by determining an (n-k) vector S defined as : 𝑺 = 𝑹𝑯𝑻 ▪ The vector S is called the error syndrome of R. 𝑺 = 𝑪 + 𝑬 𝑯𝑻 𝑺 = 𝑪𝑯𝑻 + 𝑬𝑯𝑻 Therefore 𝑺 = 𝑬𝑯𝑻 ▪ Thus, the syndrome of a received vector is zero if R is a valid codeword. The decoder uses S to detect and correct errors. Mobile and IoT Techniques slide 19 COMP 1247 Linear Block Codes ❖ Example: Consider a (7,4) block code generated by: 𝐼4 𝑃 𝟏𝟎𝟎𝟎 𝟏𝟏𝟏 𝟎𝟏𝟎𝟎 𝟏𝟏𝟎 𝑮= 𝟎𝟎𝟏𝟎 𝟏𝟎𝟏 𝟎𝟎𝟎𝟏 𝟎𝟏𝟏 Therefore, the parity check matrix for this code is: 𝟏𝟏𝟏 𝟏𝟏𝟏𝟎 𝟏𝟎𝟎 𝟏𝟏𝟎 𝑯= 𝟏𝟏𝟎𝟏 𝟎𝟏𝟎 𝟏𝟎𝟏 𝑻 𝟏𝟎𝟏𝟏 𝟎𝟎𝟏 𝑯 = 𝟎𝟏𝟏 𝟏𝟎𝟎 𝟎𝟏𝟎 𝑃𝑇 𝐼3 𝟎𝟎𝟏 ❖ For a message block D=(1 0 1 1), the codeword C is given by: 𝑪 = 𝑫𝑮 = 𝟏 𝟎 𝟏 𝟏 𝟎 𝟎 𝟏 ❖ For this codeword, the syndrome S is given by: 𝑺 = 𝑪𝑯𝑻 = 𝟎 𝟎 𝟎 Mobile and IoT Techniques slide 20 COMP 1247 Linear Block Codes ❖ If the third bit of the codeword C suffered an error in the transmission, then the received vector R will be: 𝑅 = 1001 001 = 1011 001 + 0010 000 =𝐶+𝐸 ❖ The syndrome of R will be: 𝑆 = 𝑅𝐻 𝑇 = 1 0 1 = 𝐸𝐻𝑇 ❖ Note that the syndrome S for an error in the third bit is the third row of the 𝑯𝑻 matrix. ❖ For this code, a single error in the ith bit of C would lead to a syndrome vector that would be identical to the ith row of the 𝑯𝑻 matrix. Mobile and IoT Techniques slide 21 COMP 1247 Linear Block Codes ❖ Hamming Code (Single Error Correction) ▪ Theorem (3): A linear block code with 𝑑𝑚𝑖𝑛 can correct up to 𝑑𝑚𝑖𝑛 − 1 Τ2 errors and detect up to 𝑑𝑚𝑖𝑛 − 1 errors in each codeword. ▪ Based on above theorem, a single error correction code must have 𝒅𝒎𝒊𝒏 = 𝟑. ▪ To design a single error correcting code, it should satisfies the following inequality: 𝟐𝒏−𝒌 − 𝟏 ≥ 𝒏 i.e. 𝒏 − 𝒌 ≥ 𝒍𝒐𝒈𝟐 𝒏 + 𝟏 ▪ So, given a message block size k, we can determine the minimum size n for the codeword from: 𝒏 ≥ 𝒌 + 𝒍𝒐𝒈𝟐 𝒏 + 𝟏 ▪ Note that n must be an integer. Mobile and IoT Techniques slide 22 COMP 1247 Linear Block Codes ❖ Example: Design a linear block code with 𝑑𝑚𝑖𝑛 = 3 and a message block size of eight bits? What is the efficiency of this code? ❖ Solution: we need to find n that satisfied 𝒏 ≥ 𝒌 + 𝒍𝒐𝒈𝟐 𝒏 + 𝟏. k=8 i.e 𝒏 ≥ 𝟖 + 𝒍𝒐𝒈𝟐 𝒏 + 𝟏 ▪ The smallest value of n that satisfies the above inequality is n=12. Thus we need a (12,8) block code. ▪ The efficiency of this code (or the code rate) is k/n=8/12=2/3 Mobile and IoT Techniques slide 23 COMP 1247 Linear Block Codes ❖ Example: The parity check bits of (6,3) symmetrical linear block code are generated by: 𝑐4 = 𝑑1 + 𝑑3 𝑐5 = 𝑑1 + 𝑑2 𝑐6 = 𝑑2 + 𝑑3 Where d1 , d2 , and d3 are the message bits. 1. Find the generator matrix G of this code? 2. Find the parity check matrix H of this code? 3. Find the minimum distance dmin of this code? 4. How many bits this code will be able to correct? 5. Calculate the syndrome for the received codeword R=[0 1 0 1 1 0] ? 6. Does this received codeword have an error? In which bit? Mobile and IoT Techniques slide 24 COMP 1247 Linear Block Codes ❖ Solution: 100 110 101 100 1- ANS: 𝐺 = 010 011 2- ANS: 𝐻 = 110 010 001 101 011 001 3- Messages Codewords Weight 000 000 000 0 001 001 101 3 010 010 011 3 011 011 110 4 100 100 110 3 101 101 001 4 110 110 101 4 dmin=3 110 111 111 000 3 011 𝑑𝑚𝑖𝑛 −1 101 4- ANS: =1 5- ANS: 𝑆 = 𝑅𝐻 𝑇 = 0 1 0 1 1 0 = [1 0 1] 2 100 010 001 6- ANS: there is an error in the 3rd bit Mobile and IoT Techniques slide 25 COMP 1247  Modulation Techniques Mobile and IoT Techniques slide 1 COMP 1247 Objectives ❖ Understand why modulation is needed ❖ Discuss the behavior of all different analog modulations ❖ Discuss the behavior of all different digital modulations Mobile and IoT Techniques slide 2 COMP 1247 Why is Modulation Needed? ❖ Ease of radiation ❖ To transmit the information signal over a specified medium ❖ Overcome equipment limitations ❖ Reduce noise and interference ❖ Regulated frequency assignment ❖ Channel multiplexing FDM (Frequency Division Multiplexing) Mobile and IoT Techniques slide 3 COMP 1247 Modulation Modulation Analog Modulation Digital Modulation ❖ AM (Amplitude Modulation) ❖ ASK (amplitude Shift keying) ❖ FM (Frequency Modulation) ❖ FSK (Frequency shift keying) ❖ PM (Phase Modulation) ❖ PSK (Phase shift keying) ❖ QAM (Quadrature Amplitude Modulation) ❖ MSK and GMSK (used in GSM) ❖ Spread Spectrum (used in CDMA & UMTS) ❖ OFDMA (used in WiMAX & LTE) ❖ Wireless communication systems mainly use digital modulation Mobile and IoT Techniques slide 4 COMP 1247 Modulation: Electrical Signal Parameters T A 0   2 3 2 2 X A 1 Wavelength S (t ) = Asin(2ft +  ) Signal Phase (0-3600) changes on reflection varies with distance Amplitude Frequency (Hz) phase noise must be known at Rx Determine signal power Is affected by noise How fast a signal varies in time High frequency signals are used as RF carriers Losses are proportional to frequency All oscillators in a system must have same reference source for frequency stability Mobile and IoT Techniques slide 5 COMP 1247 Modulation: Speed of Electromagnetic Wave f  = c f (MHz )  (m) = 300 v = c/  Wave velocity in a practical medium Medium permittivity ❖ Practical mediums slow down the RF signal ❖ Signal attenuation increases with decreasing wavelength ▪ Equivalently: high frequency signal are attenuated faster compared to low frequency signals Mobile and IoT Techniques slide 6 COMP 1247  Analog Modulation ❖ Amplitude Modulation (AM) ▪ The information is modulated inside the carrier’s amplitude  Mobile and IoT Techniques slide 7 COMP 1247  Analog Modulation ❖ Amplitude Modulation (AM) ▪ The modulation index k is ▪ defined as: ❖ If k >1 the carrier is said to be overmodulated which results in envelop distortion Mobile and IoT Techniques slide 8 COMP 1247 Analog Modulation ❖ Amplitude Modulation (AM) ▪ AM signal required BW of: ▪ 50 % of the TX power is wasted for the carrier ▪ Other versions of AM are: DSB and SSB ▪ In DSB the carrier is removed from transmitted signal (saving power) ▪ In SSB the carrier is removed and only half transmitted BW is used AM Signal in Frequency Domain (saving power and BW) Mobile and IoT Techniques slide 9 COMP 1247  Analog Modulation ❖ Frequency Modulation (FM) ▪ The information is modulated inside the carrier’s frequency Mobile and IoT Techniques slide 10 COMP 1247 Analog Modulation ❖ Frequency Modulation (FM) ▪ The modulation index for FM is defined as: is the frequency deviation constant ▪ The required transmitted BW for FM is (Carson’s rule): ▪ FM has better noise immunity but require higher transmitted BW Mobile and IoT Techniques slide 11 COMP 1247 Analog Modulation ❖ Phase Modulation (PM) ▪ The information is modulated inside the carrier’s phase Mobile and IoT Techniques slide 12 COMP 1247 Analog Modulation ❖ AM, FM, and PM comparison Mobile and IoT Techniques slide 13 COMP 1247 Digital Modulation Why digital modulation? ❖ Better noise immunity (regeneration) ❖ Supports complex signal conditioning and processing techniques ▪ Source coding ▪ Channel coding ▪ Encryption ▪ Equalization ❖ More efficient use of spectrum ❖ Uses DSPs to implement modulators and demodulators in software ❖ Software radio: alterations and improvements are easy to implement!! Mobile and IoT Techniques slide 14 COMP 1247 Digital Modulation Basics of digital modulation ❖ The bit rate ( ) defines the rate at which information is passed. ❖ The symbol rate (or baud rate ) ( ) defines the number of symbols per second. ❖ Each symbol represents n bits, and has M signal states, where: This is called M-ary signaling. ❖ The maximum rate of information (bps) transfer through a baseband channel is given by: where W = bandwidth of baseband channel. Mobile and IoT Techniques slide 15 COMP 1247 Digital Modulation Main Performance Parameters of Digital Modulation ❖ Power efficiency ▪ The required SNR ❖ Spectral efficiency ▪ The required BW ❖ Bit error rate (BER) ▪ The maximum allowable error rate Mobile and IoT Techniques slide 16 COMP 1247 Digital Modulation ❖ Amplitude Shift Keying (ASK) ▪ The carrier signal switched ON & OFF based on the input bit. ▪ ASK is heavily affected by noise and interference. Mobile and IoT Techniques slide 17 COMP 1247  Digital Modulation ❖ Frequency Shift Keying (FSK) ▪ Bandwidth occupancy of FSK depend on the spacing of the two symbols. ▪ A frequency spacing of 0.5 times the symbol period is typically used. ▪ Can be expanded to a M-ary scheme by employing multiple frequencies as different states. Mobile and IoT Techniques slide 18 COMP 1247 Digital Modulation Phase Shift Keying (PSK) ❖ Message impressed on signal Phase ▪ Signal amplitude and frequency remain constant S (t ) = A sin( 2ft + i ) i = 1, 2, …M ❖ Has better noise immunity ❖ M = 2: Binary PSK (BPSK) ❖ M = 4: Quadrature PSK (QPSK) ❖ Widely used in telecommunication systems Mobile and IoT Techniques slide 19 COMP 1247 Digital Modulation ASK, FSK and PSK Comparison Mobile and IoT Techniques slide 20 COMP 1247 Digital Modulation BPSK ❖ Codes only one bit per carrier phase change ❖ Most reliable in terms of data integrity ▪ System control info is transmitted using BPSK ❖ Needs RF BW equal to the bit rate Signal Constellation BPSK waveform Amplitude 1 1 0 0 1 0 Phase 1 Noise affects signal amplitude but information is carried in signal phase This makes BPSK most reliable in harsh interference environments BPSK modulation: symbol contains only one bit Mobile and IoT Techniques slide 21 COMP 1247 Digital Modulation QPSK ❖ Carrier phase has 4 states: M = 4, n = 2 bits/phase change ▪ Transmits two bits in each carrier phase ▪ Modulation spectral efficiency is 2 bps/Hz  Twice as fast as BPSK (transmits twice as much data in same BW) ❖ Minimum BW = Rb/2 11 10 01 00 10 11 00 01 10 11 QPSK Waveform QPSK Constellation ❖ QPSK needs more signal to noise ratio compared to BPSK Mobile and IoT Techniques slide 22 COMP 1247 Digital Modulation Quadrature Amplitude Modulation (QAM) 16 QAM ❖ 4 bits per symbol ▪ 4 times more data rate compared to BPSK ▪ Each constellation point is different from other point  Gray coding ❖ Can use more Tx power ▪ Longer reach 16- QAM Constellation ❖ Used in widely in digital systems Mobile and IoT Techniques slide 23 COMP 1247 Digital Modulation 64- QAM Constellation ❖ 6 bits per modulation symbol ▪ 6 times more data rate compared to BPSK ❖ 64-QAM Needs more SNR than that for 16-QAM which is more than the QPSK. ❖ 64-QAM gives more throughput than the 16-QAM which is more than the QPSK Mobile and IoT Techniques slide 24 COMP 1247 Digital Modulation: SNR Requirement Mobile and IoT Techniques slide 25 COMP 1247 Digital Modulation Digital Modulation Performance Summary Modulation Encoding BW (Hz) Baud Rate Spectral efficiency FSK 1 bit > Rb Rb