He holds a Master's degree in Communication Engineering from BITS-Pilani, India. It also analyzed reviews to verify trustworthiness. 1.1 Trading off simplicity and bandwidth 1.2 Industry trends 2. Next lets assign variables to represent the amplitude of the sine and cosine. If you're not sure which to choose, learn more about installing packages. Link to the black & white edition: https:. Science/Research . Please try your request again later. Full content visible, double tap to read brief content. It looks like WhatsApp is not installed on your phone. Digital Modulation. 9783030618599, 9783030618605. This book, an essential guide for understanding the implementation aspects of a digital modulation system, shows how to simulate and model a digital modulation system from scratch. PSK is of two types, depending upon the . ISBN 978-90-73461-44-4 5. Python Viswanathan M. Digital Modulations using Python pdf file size 5,92 MB added by Masherov 06/23/2021 04:55 Mathuranathan Viswanathan, 2019. Sorry, there was a problem loading this page. Why digital modulation? We just use imaginary/complex numbers to represent what we are transmitting. 1dda02c 18 minutes ago. Now back to sampling for a second. Pretending that h[n] is unknown, using only the input signal r[k] and the reference signal a[k], the LMS algorithm is invoked to design a FIR filter of length N = 5. A complex number also has a magnitude and phase, which makes more sense if you think about it as a vector instead of a point. The above equation now becomes: Even though we started with a complex number, what we are transmitting is real, which is good because you cant actually transmit something imaginary with electromagnetic waves. In this case our x-axis is 1024 equally spaced points between -0.5 MHz and 0.5 MHz. 2 commits. Once you start working with SDRs, you will often find a large spike in the center of the FFT. We go from sending to , meaning our carrier shifts phase by 90 degrees when we switch from one sample to another. Digital Modulations using Python ISBN-13 9781712342749 Publication Date December, 2019 Assembled Product Dimensions (L x W x H) 10.00 x 7.01 x 0.46 Inches ISBN-10 1712342746 Report incorrect product information Bestselling items that customers love # assume x contains your array of IQ samples, # we will only take the FFT of the first 1024 samples, see text below, # add the following line after doing x = x[0:1024], # start, stop, step. Get Started Samples Download. Top subscription boxes right to your door, 1996-2022, Amazon.com, Inc. or its affiliates, Visit Amazon's Mathuranathan Viswanathan Page, Learn more how customers reviews work on Amazon. A low-noise amplifier (LNA) is simply an amplifier designed for extremely low power signals at the input. Find many great new & used options and get the best deals for Digital Modulations Using Python : (Color Edition) by Mathuranathan Viswanathan (2019, Trade Paperback) at the best online prices at eBay! ax[1,1].set_title('IQ impairments & DC offsets');fig.show() 6.6 Performance of M-QAM modulation with receiver impairments In a wireless communication system, that uses OFDM with higher order modulations like M-QAM, the effect of receiver impairments is of great concern. Program 77: DigiCommPy\impairments.py: Function for adding DC impairments to IQ branches class ImpairmentModel(): def __init__(self,g=1,phi=0,dc_i=0,dc_q=0): # constructor < see section 6.1 for details > def receiver_impairments(self,r): < see section 6.1 for details > def __iq_imbalance(self,r): #private member function < see section 6.3 for details > def __dc_impairment(self,r): #private member function """ Add DC impairments in a complex baseband model Introduces DC imbalance between the inphase and quadrature components of the complex baseband signal r. Parameters: r: complex baseband signal sequence to impair Returns: z : impaired signal sequence """ return r + (self.dc_i+1j*self.dc_q) Correspondingly, the DC offsets on the branches are simply removed by subtracting the mean of the signal on the I,Q branches from the incoming signal. Here are the block diagrams of these three architectures, note that variations and hybrids of these architectures also exist: We refer to a signal centered around 0 Hz as being at baseband. Conversely, bandpass refers to when a signal exists at some RF frequency nowhere near 0 Hz, that has been shifted up for the purpose of wireless transmission. Phase Shift Keying (PSK) is the digital modulation technique in which the phase of the carrier signal is changed by varying the sine and cosine inputs at a particular time. , Item Weight Learn more how customers reviews work on Amazon, Independently published (December 2, 2019). Gain imbalance on the I,Q branches - g. DC offsets in the I and Q branches - dci , dcq . Lets say we sample at a rate Fs (samples shown in blue). The pilot estimation technique is well suited for wireless applications like WLAN, UMTS and LTE, where a known pilot sequence is transmitted as part of the data communication session. The AWGN noise model and the code to compute theoretical symbol error rates are given in sections 4.1.2 and 4.1.3 respectively. It places the signal of interest at an intermediate frequency, known as IF. This downconversion happens before we sample. ouss28 Update README.md. Developed and maintained by the Python community, for the Python community. Visible light is also electromagnetic waves, at much higher frequencies (400 THz to 700 THz). The term quadrature has many meanings, but in the context of DSP and SDR it refers to two waves that are 90 degrees out of phase. The following code re-uses the QAMModem class that was already defined in section 3.4.3 of chapter 3. There was a problem loading your book clubs. System impulse response (h): -0.5726 + 0.0607i 0.0361 - 0.5948i -1.1136 - 0.121i 0.5275 - 0.4212i 1.7004 + 1.8307i LMS adapted filter (w): -0.5726 + 0.0607i 0.0361 - 0.5948i -1.1136 - 0.121i 0.5275 - 0.4212i 1.7004 + 1.8307i References 1. The implemented simulation models shown in this book, provide an opportunity for an engineer to understand the basic implementation aspects of modeling various building blocks of a digital modulation system. In this section, we begin by constructing a model, shown in Figure 6.2 , to represent the effect of following RF receiver impairments Phase imbalance and cross-talk on I,Q branches caused by local oscillator phase mismatch - . Its so high that we dont use traditional antennas to transmit light. , Dimensions When we tune to a frequency with our SDR and receive samples, our information is stored in I and Q; this carrier does not show up in I and Q, assuming we tuned to the carrier. A learner-friendly, practical and example driven book, Digital Modulations using Python gives you a solid background in building simulation models for digital modulation systems in Python version 3. Lastly, you may be curious how fast signals travel through the air. Please try again later. The minimum rate in which we can sample is known as the Nyquist Rate. Most signals are around 100 kHz to 40 MHz wide in bandwidth, so through downconversion we can sample at a much lower rate. It will give you an output of a million frequency bins, after all, which is too much to show in a plot. "PyPI", . Digital Modulation Overview: In digital wireless communication systems, the modulating signal may be represented as a time sequence of symbols or pulses, where each symbol has m finite states. Well known compensation techniques for DC offsets and IQ imbalances are also discussed with code implementation and results. Lucky, Automatic equalization for digital communication, Bell System Technical Journal 44, 1965 4. The function to perform MQAM modulation and the coherent detection technique was already defined in sections 3.4.3 and 3.4.4. Digital Modulations using Python: (Black & White edition) : Viswanathan, Mathuranathan, Srinivasan, Varsha: Amazon.com.au: Books A learner-friendly, practical and example driven book, Digital Modulations using Python gives you a solid background in building simulation models for digital modulation systems in Python version 3. (a) FSK Modulation; (b) FSK Modulated output 4.4.3 Phase shift Keying Phase-shift keying (PSK) is a method of digital communication in which the phase of a transmitted signal is varied to convey information. 189 190 6 Receiver Impairments and Compensation Fig. digital, DC offsets dci and dcq on the I and Q branches are simply modelled as additive factors on the incoming signal. import sounddevice as sd. Our LO will be set to 95 MHz because that is the frequency to which we ask the SDR to tune. The following RF receiver impairment model implemented in Python, consists of two parts. In essence, together with the gain imbalance g and the phase mismatch rad , the impaired signals on the I,Q branches are represented as " # " #" # zi [k] 1 0 ri [k] = (6.1) zq [k] g.sin(rad ) g.cos(rad ) rq [k] For the given gain mismatch g and phase mismatch rad in radians, the following Python function introduces IQ imbalance in a complex baseband signal. The difference 1 g is a measure of amplitude deviation of Q branch from the perfectly balanced condition. The utility of this behavior is that we can control the phase and amplitude of a resulting sine wave by adjusting the amplitudes I and Q (we dont have to adjust the phase of the cosine or sine). To accurately sample any given signal, the sample rate must be at least twice the frequency of the maximum frequency component. Recall from high school physics class that radio waves are just electromagnetic waves at low frequencies (between roughly 3 kHz to 80 GHz). The phase mismatch between the local oscillator outputs is captured by the parameter . A learner-friendly, practical and example driven book, Digital Modulations using Python gives you a solid background in building simulation models for digital modulation systems in Python version 3.. In wireless communications this relationship becomes important when we get to antennas, because to receive a signal at a certain carrier frequency, , you need an antenna that matches its wavelength, , usually the antenna is or in length. PSK technique is widely used for wireless LANs, bio-metric, contactless operations, along with RFID and Bluetooth communications. If we attempt to receive a signal with too low a sample rate, that filter will chop off part of the signal. T.H. There is no notion of a baseband transmission, because you cant transmit something imaginary. For example, we could adjust I and Q in a way that keeps the amplitude constant and makes the phase whatever we want. Because the information is digital, this form of communications offers the advantage of a perfect reproduction of the transmitted signal. A third architecture, one that is popular because its how old radios worked, is known as superheterodyne. For the sake of simplicity, we use sine and cosine as our two sine waves that are 90 degrees out of phase. You have probably seen this relationship before: where is the speed of light, typically set to 3e8 when is in Hz and is in meters. Digital Filter Design using Python for Power Engineering Applications: An Open Source Guide [1st ed.] The implemented simulation models shown in this book, provide . Once the parameters given in equation 6.5 and 6.6 are estimated during the preamble transmission, the IQ compensation during the normal data transmission is as follows 6.5 Visualizing the effect of receiver impairments 197 wi = di dq Pest .di p wq = 2 kest 1 Pest (6.7) Program 82: DigiCommPy\compensation.py: Compensation of IQ imbalance during data transmission class PilotEstComp(): def __init__(self,impObj): # constructor < see previous program > def pilot_est(self): < see previous program > def pilot_iqImb_compensation(self,d): """ Function to compensate IQ imbalance during the data transmission Parameters: d : The impaired received complex signal sequence Returns: w : IQ imbalance compensated complex signal sequence Usage: from compensation import PilotEstComp pltEstCompObj = PilotEstComp(impObj) #initialize pltEstCompObj.pilot_iqImb_compensation(d) #call function """ # estimate the Kest, Pest for the given model using pilot transmission self.pilot_est() d_dcRemoved = d - (mean(real(d)) + 1j* mean(imag(d))) I=real(d_dcRemoved); Q=imag(d_dcRemoved) wi= I; wq = (Q - self.Pest*I)/sqrt(1-self.Pest**2)/self.Kest return wi + 1j*wq 6.5 Visualizing the effect of receiver impairments With the receiver impairments model and compensation techniques in place, let us visualize their effects in a complex plane. Take the FFT of our samples. What we do is sample the I and Q branches individually, using two ADCs, and then we combine the pairs and store them as complex numbers. A signal at baseband may be perfectly centered at 0 Hz like the right-hand portion of the figure in the previous section. The amplitude also changes. B. Razavi, RF microelectronics, ISBN 978-0137134731, Prentice Hall, 2 edition, October 2011 4. Frequency modulation Python matplotlib visualisation Raw frequency_modulation_visualisation.py This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. Something went wrong. v u L u 2 u u zq [k] u k=1 (6.5) Kest = u L u t z2 [k] i k=1 L (zi [k].zq [k]) Pest = k=1 (6.6) L k=1 z2i [k] 196 6 Receiver Impairments and Compensation where, the complex signal z = zi + jzq , represents the impaired version of the long preamble as given in the IEEE 802.11a specification [6]. Think DSP is an introduction to Digital Signal Processing in Python. SDRs are surprisingly similar. After viewing product detail pages, look here to find an easy way to navigate back to pages you are interested in. Find all the books, read about the author, and more. Monson H. Hayes , Statistical Digital Signal Processing and Modeling, chapter 4.4.5, Application FIR least squares inverse filter, Wiley, 1 edition, April 11, 1996. Digital-to-Analog signals is the next conversion we will discuss in this chapter. This book, an essential guide for understanding the implementation aspects of a digital modulation system, shows how to simulate and model a . 7. It presents the key topics with required theoretical background along with the implementation details in the form of Python scripts.Key topics: Basics of signal processing, essential for implementing digital modulation techniques - generation of test signals, interpreting FFT results, power and energy of a signal, methods to compute convolution . For this condition, the performance with the pilot based IQ compensation is better than that of the blind compensation technique. The adaptive filter should be able to identify the response of a short FIR filter whose impulse response is known prior to the test. In other words, at each time step, you will sample one I value and one Q value and combine them in the form (i.e., one complex number per IQ sample). Because the SDR tunes to a center frequency, the 0 Hz portion of the FFT corresponds to the center frequency. 1 review Get A Copy Amazon Stores Libraries Paperback, Grayscale, 216 pages Published December 2nd 2019 by Independently published More Details. Digital Modulations Using Python : (Color Edition) Item Length: 10in. 9781712321638 . Developed and maintained by the Python community, for the Python community. And its much easier to adjust two amplitudes and perform an addition operation compared to adjusting an amplitude and a phase. Mathuranathan uses non-trivial examples that are really useful and practical to learn from. As an example, lets say we want to view 5 MHz of spectrum at 100 MHz. Our SDRs go to great lengths to provide us with samples free of aliasing and other imperfections. Most of the time you see complex samples (IQ samples), you are at baseband. For example, if we have a sample rate of 10 Hz, then the sample period is 0.1 seconds; there will be 0.1 seconds between each sample. Offset QPSK, which involves adding a delay to one of two digital data streams used in the modulation process, reduces the maximum phase jump to 90. This paperback is a black & white edition. I have done FFT's for over a decade and even written a open source library, yet I learned a few things I did not fully understand by reading his book. Predominantly, such books utilize the sophisticated built-in functions or toolboxes that are already. modulation techniques. The ADC acts as the bridge between the analog and digital domains. Frequencies above 6 GHz have been used for radar and satellite communications for decades, and are now being used in 5G mmWave (24 - 29 GHz) to supplement the lower bands and increase speeds. It indicates that our sample rate was too low because the same samples could have come from two different functions, leading to ambiguity. Be the first to receive exclusive offers and the latest news on our products and services directly in your inbox. x Digital Signal Processing with Python Programming Statistical inferences The second chapter is devoted to statistical inference. py3, Status: Link to the color edition: https://www.amazon.com/dp/1712321633 .A learner-friendly, practical and example driven book, Digital Modulations using Python gives you a solid background in building simulation models for digital modulation systems in Python version 3. Someone might say, I have an SDR running at 2 MHz sample rate. What they mean is that the SDR receives two million IQ samples per second. ax[1,1].plot(real(r4),imag(r4),'r.') Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet, or computer - no Kindle device required. We work hard to protect your security and privacy. 1996-2022, Amazon.com, Inc. or its affiliates, No Import Fees Deposit & $10.69 Shipping to Germany. J. R. Treichler, I. Fijalkow, and C. R. Johnson, Jr., Fractionally-spaced equalizers: How long should they really be?, IEEE Signal Processing Mag., vol. In this text, only the single-branch IQ imbalance model and its corresponding compensation algorithms are described. Bring your club to Amazon Book Clubs, start a new book club and invite your friends to join, or find a club thats right for you for free. Note that N, the number of samples to simulate, becomes the FFT length because we take the FFT of the entire simulated signal. 6.4: Constellation plots for unimpaired (blue) and impaired (red) versions of 64-QAM modulated symbols: (a) Gain imbalance g = 0.8 (b) Phase mismatch = 12 (c) DC offsets dci = 0.5, dcq = 0.5 (d) With all impairments g = 0.8, = 12 , dci = 0.5, dcq = 0.5 The complete simulation code for this performance simulation is given next. Removing this extra noise is difficult because it is close to the desired output signal. The input bit pattern is "11010". Digital Modulations using Python: (Black & White edition) by Mathuranathan Viswanathan available in Trade Paperback on Powells.com, also read synopsis and reviews. Brief content visible, double tap to read full content. . All the IQ processing receiver structures suffer from problems due to amplitude and phase mismatches in their I and Q branches. Another option is to change the frequency of the carrier, i.e., shift it slightly up or down, which is what FM radio does. Technically, radio frequency (RF) is defined as the range from roughly 20 kHz to 300 GHz. 158-164. The presentation is geared for practicing enginee Download full-text PDF. We work hard to protect your security and privacy. Program 79: DigiCommPy\impairments.py: IQ imbalance model class ImpairmentModel(): def __init__(self,g=1,phi=0,dc_i=0,dc_q=0): # constructor < see section 6.1 for details > def receiver_impairments(self,r): < see section 6.1 for details > def __iq_imbalance(self,r): #private member function """ Add IQ imbalance impairments in a complex baseband. Its simply plotting complex numbers and treating them as vectors. This arrangement is called direct conversion, or zero IF, because the RF frequencies are being directly converted down to baseband. Learn more. source, Uploaded This refers to a variety of techniques. For a given complex number where is the real part and is the imaginary part: In Python you can use np.abs(x) and np.angle(x) for the magnitude and phase. Program 81: DigiCommPy\compensation.py: IQ imbalance estimation using Pilot transmission class PilotEstComp(): # Class: PilotEstComp (Pilot based estimation and compensation) # Attribute definitions: # self.impObj: reference to the object implementing the impairment model # self.Kest : estimated gain imbalance # self.Pest : estimated phase mismatch # self.preamble : time domain representation long preamble (IEEE 802.11a) def __init__(self,impObj): # constructor self.impObj = impObj self.Kest = 1 self.Pest = 0 # Length 64 - long preamble in IEEE 802.11a (frequency domain representation) preamble_freqDom = np.array([0,0,0,0,0,0,1,1,\ -1,-1,1,1,-1,1,-1,1,\ 1,1,1,1,1,-1,-1,1,1,\ -1,1,-1,1,1,1,1,0,1,\ -1,-1,1,1,-1,1,-1,1,\ -1,-1,-1,-1,-1,1,1,\ -1,-1,1,-1,1,-1,1,1,\ 1,1,0,0,0,0,0]) from scipy.fftpack import ifft self.preamble=ifft(preamble_freqDom,n = 64) def pilot_est(self): """ IQ imbalance estimation using Pilot transmission Computes: Kest - estimated gain imbalance Pest - estimated phase mismatch """ # send known preamble through the impairments model r_preamb = self.impObj.receiver_impairments(self.preamble) # remove DC imbalance before IQ imbalance estimation z_preamb= r_preamb - (mean(real(r_preamb)) + 1j* mean(imag(r_preamb))) # IQ imbalance estimation I=real(z_preamb); Q=imag(z_preamb) self.Kest = sqrt(sum((Q*Q))/sum(I*I)) # estimated gain imbalance self.Pest = sum(I*Q)/sum(I*I) # estimated phase mismatch def pilot_iqImb_compensation(self,d): < see next program > Let d = di + jdq be the impaired version of complex signal received during the normal data transmission interval. Lets use the first 1024 samples as an example to create a 1024-size FFT. The input can be a complex number or an array of complex numbers, and the output will be a real number(s) (of the data type float). Lets say we have some random function, , which could represent anything, and its a continuous function that we want to sample: We record the value of at regular intervals of seconds, known as the sample period. Enhancements you chose aren't available for this seller. Please choose a different delivery location. demodulation, , ISBN-10 Free shipping for many products! The unimpaired sequence and the sequence affected by receiver impairments are plotted on a complex plane as shown in Figure 6.4. Take the complex number 0.7-0.4j as an example: A complex number is really just two numbers together, a real and an imaginary portion. The details of the individual sub-functions for the IQ imbalance model and DC offset model are described in the subsequent sections. Fortunately, this process of offtuning, a.k.a applying an LO offset, is often built into the SDRs, where they will automatically perform offtuning and then shift the frequency to your desired center frequency. Furthermore, the RF frontend may also introduce DC offsets in the IQ branches, leading to more performance degradation. We dont actually have to generate a sine wave, shift by 90, multiply or addthe SDR does that for us. Author: Mathuranathan Viswanathan Genre: Technology & Engineering Topic: Mobile & Wireless Communications Item Width: 7in. The effect of IQ imbalance is quite disastrous for higher order modulations that form the basis for many modern day communication systems like IEEE 802.11 WLAN, UMTS, LTE, etc. Why 90 degrees out of phase? The code re-uses many functions defined in chapter 3 and chapter 4. Alternatively, if you know your signal is not changing fast, its adequate to use a few thousand samples and find the PSD of those; within that time-frame of a few thousand samples you will likely capture enough of the signal to get a nice representation. Phil Schniter, MMSE Equalizer Design, March 6, 2008, http://www2.ece.ohio-state.edu/schniter/ee501/ handouts/mmse eq.pdf 8. Perform an FFT shift, covered in the previous chapter, to move 0 Hz in the center and negative frequencies to the left of center. Apr 25, 2020 To plot this PSD we need to know the values of the x-axis.
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