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HOME | WIRELESS PI
Not only do we need to understand. E = mc2 E = m c 2. from Albert Einstein’s theory of special relativity but also come up with optimal strategies to reproduce as closely as possible the said person or object from the incoming beam. This is a process that requires excellent mental models of the underlying mass ↔ ↔ energyconversion
HOW A FREQUENCY LOCKED LOOP (FLL) WORKS BASICS OF SYNCHRONIZATION Performing synchronization using this training is known as data-aided synchronization. Most widespread wireless communication systems in today’s world such as LTE and WiFi implement algorithms based upon this approach. One problem with data-aided synchronization strategy is the waste of resources. The power and time spent on transmitting DIGITAL FILTER AND SQUARE TIMING RECOVERY FSK DEMODULATION IN GNU RADIO Binary FSK (BFSK) is the simplest form of FSK where the two bits 0 and 1 correspond to two distinct carrier frequencies F 0 F 0 and F 1 F 1 to be sent over the air. The bits can be translated into symbols through the relations. where F c F c is the nominal carrier frequency and ΔF Δ F is the peak frequency deviation from this carrierfrequency.
MUELLER AND MULLER TIMING SYNCHRONIZATION ALGORITHM Mueller and Muller Timing Synchronization Algorithm. Proposed in 1976, Mueller and Muller algorithm is a timing synchronization technique that operates at symbol rate, as opposed to most other synchronization algorithms that require at least 2 samples/symbol. The most confusing thing communication engineers and radio hobbyists find about this COSTAS LOOP FOR CARRIER PHASE SYNCHRONIZATIONEBOOK - WIRELESS PI
Wireless Communications from the Ground Up - An SDR Perspective - 10 Chapters (PDF, 828 pages) EFFECT OF TIME SHIFT IN FREQUENCY DOMAIN WINDOWING AN OFDM SIGNAL IN TIME DOMAIN A very similar technique is known as Windowed-OFDM (W-OFDM) in which windowing is applied in a manner that the window overlaps with the complete OFDM symbol as well as the CP and the cyclic suffix. Moreover, the window amplitude is −3 − 3 dB at the start and end of the OFDM symbol. For a perfect reconstruction of the OFDM symbol,the cyclic
HOME | WIRELESS PI
Not only do we need to understand. E = mc2 E = m c 2. from Albert Einstein’s theory of special relativity but also come up with optimal strategies to reproduce as closely as possible the said person or object from the incoming beam. This is a process that requires excellent mental models of the underlying mass ↔ ↔ energyconversion
HOW A FREQUENCY LOCKED LOOP (FLL) WORKS BASICS OF SYNCHRONIZATION Performing synchronization using this training is known as data-aided synchronization. Most widespread wireless communication systems in today’s world such as LTE and WiFi implement algorithms based upon this approach. One problem with data-aided synchronization strategy is the waste of resources. The power and time spent on transmitting DIGITAL FILTER AND SQUARE TIMING RECOVERY FSK DEMODULATION IN GNU RADIO Binary FSK (BFSK) is the simplest form of FSK where the two bits 0 and 1 correspond to two distinct carrier frequencies F 0 F 0 and F 1 F 1 to be sent over the air. The bits can be translated into symbols through the relations. where F c F c is the nominal carrier frequency and ΔF Δ F is the peak frequency deviation from this carrierfrequency.
MUELLER AND MULLER TIMING SYNCHRONIZATION ALGORITHM Mueller and Muller Timing Synchronization Algorithm. Proposed in 1976, Mueller and Muller algorithm is a timing synchronization technique that operates at symbol rate, as opposed to most other synchronization algorithms that require at least 2 samples/symbol. The most confusing thing communication engineers and radio hobbyists find about this COSTAS LOOP FOR CARRIER PHASE SYNCHRONIZATIONEBOOK - WIRELESS PI
Wireless Communications from the Ground Up - An SDR Perspective - 10 Chapters (PDF, 828 pages) EFFECT OF TIME SHIFT IN FREQUENCY DOMAIN WINDOWING AN OFDM SIGNAL IN TIME DOMAIN A very similar technique is known as Windowed-OFDM (W-OFDM) in which windowing is applied in a manner that the window overlaps with the complete OFDM symbol as well as the CP and the cyclic suffix. Moreover, the window amplitude is −3 − 3 dB at the start and end of the OFDM symbol. For a perfect reconstruction of the OFDM symbol,the cyclic
TRAINING | WIRELESS PI Training. I can help your company with a live or online training on wireless communications and software defined radios. The topics for available options are listed in each category below. You can select the right training according to the competence level of the audience as displayed by the Gaussian curve here. Beginner. Intermediate orAdvance.
ABOUT | WIRELESS PI
Some biography. After obtaining a PhD in Electrical Engineering from Texas A&M University, I have mostly worked on DSP algorithms development for real world demonstrations of wireless systems such as a MIMO-OFDM testbed, a low-SNR receiver and phase of arrival based localization. As a dad of 3 kids, my time is spent on slowly emptyingthe queue
WIRELESS PI
After obtaining a PhD from Texas A&M University, I have worked on DSP algorithms development for real world demonstrations of wireless systems such as a MIMO-OFDM testbed, low-SNR receiver and phase of arrival based localization. As a dad of 3 kids, my time is spent on slowly emptying the queue of projects that entertain me the most. THE FUNDAMENTAL PROBLEM OF SYNCHRONIZATION Depending on its design parameters, the PLL will try to lock onto the incoming phase within a specific time duration. However, that phase is jumping around by $0^\circ$, $\pm 90^\circ$ or $180^\circ$ at every symbol boundary due to modulating data, never allowing our mechanism to converge.This is the fundamental problem every synchronization subsystem needs to address and is illustrated in EFFECT OF TIME SHIFT IN FREQUENCY DOMAIN where a time shift of −T /4 − T / 4 is seen to impart a phase shift of −π/2 − π / 2 in frequency domain. This makes sense because if a full period T T of the two complex sinusoids summing up in time domain to produce a cosine spans 360∘ 360 ∘, then a shift of −1/4 − 1 / 4 of 360∘ 360 ∘ is −90∘ − 90 ∘. This is THE CONCEPT OF FREQUENCY The frequency of this complex sinusoid is defined as this angular velocity normalized by 2π 2 π so that the units are cycles/second instead of radians/second. F = 1 2π ⋅ Δθ Δt F = 1 2 π ⋅ Δ θ Δ t. Note that as time passes, V (t) V ( t) is shown in Figure above as coming out of the page. ADDITIVE WHITE GAUSSIAN NOISE (AWGN) Additive White Gaussian Noise (AWGN) The performance of a digital communication system is quantified by the probability of bit detection errors in the presence of thermal noise. In the context of wireless communications, the main source of thermal noise is addition of random signals arising from the vibration of atoms in the receiverelectronics.
SAMPLING A CONTINUOUS-TIME SIGNAL Sampling theorem. As shown above, sampling in time domain at intervals of T S T S creates periodicity in frequency domain with a period of F S = 1/T S F S = 1 / T S. Therefore, a band-limited continuous-time signal with highest frequency (or bandwidth) B B Hz can be uniquely recovered from its samples provided that the sample rate F S ≥2B F S INTERPRETING TIME DOMAIN DERIVATIVE IN Although this article explains the concepts in terms of mathematical constants e and j as well as integration, my book on SDR steers clear of the complex notation and integrals to describe the underlying concepts from the ground up to an advanced level.. One of the properties of Fourier Transform is that the derivative of a signal in time domain gets translated to multiplication of the signal PHASE LOCKED LOOP (PLL) IN A SOFTWARE DEFINED RADIO (SDR A Phase Locked Loop (PLL) is a device used to synchronize a periodic waveform with a reference periodic waveform. In essence, it is an automatic control system, an example of which is a cruise control in a car that maintains a constant speed around a given threshold.Wireless Pi
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An Easy Visual Guide to SDR Learn about SDR and wireless communications through (a) great visualizations, (b) simple mathematics and (c) answers to a lot of `why' questions. See the sample contents below.series Star Trek:
“Beam me up, Scotty!” It refers to the futuristic teleportation machine, known as a Transporter, which disassembles a person or object into an energy pattern, then beam it to a target site where it is reassembled into the original matter. FROM MECHANICS TO ENERGY BEAMS ------------------------- Imagine that such a device is invented at a point in the future. Until then, the knowledge of a person relating to transportation through automobiles is based on an automobile engine, pistons, crankshaft and so on. Suddenly we find ourselves in a completely different territory because designing and building the technology for transporting a person from location A to location B is now based around mass-energy equivalence in physics, according to which mass and energy are the same physical entity and can be converted into each other. Not only do we need to understandE=mc2E=mc2
from Albert Einstein’s theory of special relativity but also come up with optimal strategies to reproduce as closely as possible the said person or object from the incoming beam. This is a process that requires excellent mental models of the underlying mass ↔↔ energy conversion phenomena, not the mechanics of the engine. FROM ELECTRONICS TO DSP ------------------------- In not as dramatic but still a similar manner, wireless communications has profoundly transformed as a science in the previous years due to the digital revolution. * On the transmitter side, we have become able to send into air a sequence of numbers stored in a processor memory. * On the receiver side, we have become able to acquire the momentary value of the incoming analog signal and convert it into its digital representation which is nothing but a sequence of numbers, known as a discrete-time sequence. After the great advancement in computational power, most of the radio circuits capable of performing analog signal processing (e.g., by using resistors, capacitors, inductors, op amps — basically physics and devices) have been replaced by powerful digital processors that can perform the necessary number crunching (basically algorithms run by computer programs) to unravel the original digital information. In a true software radio, this is a process that requires excellent mental models of the underlying discrete-time sequences, not the electronics of the circuits. Shown on the right side above is a discrete-time sequence that consists of a few random bits 0s and 1s mapped to signal levels -1s and +1s, respectively. Why does it look more complicated than a stream of -1s and +1s? Because in the real world, this signal has been distorted by the following impairments before presenting itself to the Rx processing machine. * Carrier phase offset: 17˚ * Timing phase offset: 31% of a bit time * Carrier frequency offset: 11% of the bit rate * Multipath channel: A direct path and two reflected paths with relative amplitudes of 0.6 and 0.2 arriving after relative delays of 0.76 and 1.03, respectively (If you are unfamiliar with the above terms, there is no need to worry. This website has plenty of explanations on these topics.) The _I_ and _Q_ parts shown in the above figure are the two components of a complex signal. I cover complex numbers as a starting point to build our Digital Signal Processing (DSP) toolkit. Also, I like to view the same _IQ_ signal in a 3D figure as shown below which offers several advantages over the separate two 2D figures. By just looking at the above figure, it is hard to believe that extracting the original stream of bits 0s and 1s from this complex sequence is even possible after so much distortion. Nevertheless, this amazing (ad)venture can be accomplished through implementation of the DSP algorithms, which is all a Software Defined Radio (SDR) is about.WHY WIRELESS PI?
------------------------- My name is Qasim Chaudhari and I write about software defined radio and wireless communications in a different style as compared to several other wonderful resources available on these topics (without claiming any superiority over them). * As you will find in the introduction of my book, any language, including that of mathematics, is an unnatural mode of communication. On the other hand, showing an image makes almost every single person on the planet immediately get the concept. A figure imprints a massive amount of parallel information in our brains that is much easier to process and recall later. Since a human mind handles images very well, I try to visualize equations through beautiful figures. * I only rely on school level mathematics to explain all the concepts. The only things to know are a sine, cosine and a summation as well as (occasionally) a derivative. * Almost everything I have written has been built from the ground up and intuitive explanations are presented behind the ideas. In the past when only humans could read, we wrote scientific material in a machine-like manner. Now when the machines are learning to read, why not turn towards a more human-like style. In my opinion, there is no harm in writing technical stuff with a human touch and everyday examples. You can read more about me here.
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Privacy | Terms An Easy Visual Guide to SDR Learn about SDR and wireless communications through (a) great visualizations, (b) simple mathematics and (c) answers to a lot of `why' questions. See the sample contents below.GET YOUR COPY HERE
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