A description of a real space-time code

Understanding Space-Time Codes: Alamouti Scheme

In major cellular and wireless networks today, space diversity is employed with the help of multiple Tx antennas and/or multiple Rx antennas giving rise to Multiple Input Multiple Output (MIMO) systems. There are three different modes in which multiple antennas can be deployed: Beamforming Spatial Multiplexing Space-Time Coding In this article, we discuss space-time coding that achieves Tx diversity through multiple antennas at the Tx and simple linear processing at the Rx. This simplicity made this technique quite suitable for the past generations of cellular and other infrastructure based networks. There are two main kinds of space-time codes: Space-Time Block

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QAM constellation diagrams for M = 4, 16 and 64

QAM Constellations in Digital Communication Standards

Quadrature Amplitude Modulation (QAM) is one of the most spectrally efficient modulation schemes. This is why it is used in a wide range of digital and wireless communication systems. Recently, Ref. [1] describes a list of QAM schemes used in the standards as below which I think can be useful for an interested reader. Standard QAM Alphabet Size $M$ Bits/Symbol $\log_2 M$ Digital Video Broadcasting – Cable (DVB-C) 16 to 256 4 to 8 Digital Video Broadcasting – Cable 2 (DVB-C2) 16 to 4096 4 to 12 Digital Video Broadcasting – Terrestrial (DVB-T) 16 and 64 4 and 6 Digital

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(Top) An 8-PSK waveform. (Bottom) Two constellation diagrams: one at the Tx shown by thick red lines and the other at the Rx for a phase offset of 17 degrees shown by dotted purple lines

I/Q Signals 101: Neither Complex Nor Complicated

There was a recent discussion on GNU Radio mailing list in regards to the simplest possible intuition behind I/Q signals. Why is I/Q sampling required? Question: The original question from Kristoff went like this: “… when you mention `GNU Radio complex numbers’, you also have to mention I/Q signals, which is a topic that is very difficult to explain in 10 seconds to an audience who has never seen anything about I/Q sampling before.” Comment: According to Jeff Long: “This is a great thing to try to figure out. If we can come up with an answer that gives someone

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Experimental setup for low SNR receiver

Design of a Low-SNR Receiver

Wireless communication is energy inefficient due to the nature of the medium that spreads out energy in an unguided manner, as opposed to guided media like optical fiber and coaxial cable. To avoid wastage of power, one solution is to lower the transmit (Tx) power but then the receiver is left with the herculean task of efficiently demodulating the receive symbols at a low SNR. This article describes the design and implementation of one such receiver. Background The physical layer of a receiver system consists of three major parts, namely the frontend, the inner receiver, and the outer receiver. The

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Scatter plot for a QPSK signal after filtering through a channel

An Introduction to Constant Modulus Algorithm (CMA)

In many kinds of equalizers such as maximum likelihood sequence estimation, the channel response is available at the Rx through any channel estimation procedure that requires a training sequence. For adaptive equalization such as Least Mean Square (LMS) equalizers or Decision Feedback Equalization (DFE), first the training sequence symbols and then symbol decisions are employed to tune the equalizer taps. There are many applications, however, where the Rx needs to acquire the equalizer coefficients without any help from the Tx in the form of known symbols. This is a non-data-aided scenario that is primarily required in mobile communication systems where

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