Tag: Inter-Symbol Interference (ISI)

Scatter plot for a QPSK signal after filtering through a channel
Wireless/SDR

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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Classification of carrier frequency synchronization algorithms
Wireless/SDR

Classification of Carrier Frequency Synchronization Techniques

We have discussed before that carrier phase synchronization is done at the end of the Rx signal processing chain due to the very nature of the DSP implementation. And that almost all DSP based phase synchronization algorithms are timing-aided. Timing acquisition implies knowing the symbol boundaries in the Rx sampled waveform which is equivalent to identifying the optimal sampling instants where the eye opening is maximum and Inter-Symbol Interference (ISI) from the neighbouring symbols is zero. In the case of Carrier Frequency Synchronization (CFO), this is not true. From a previous post on the effect of CFO, we know that

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Square-root Nyquist filters for three different excess bandwidths
DSP / Wireless/SDR

How to Design Nyquist and Square-Root Nyquist Pulse Shaping Filters

The radio spectrum is a very precious resource like real estate and must be utilized judiciously. Pulse shaping filters control the spectral leakage of the transmitted signal in a wireless channel due to the strict restrictions to comply with a spectral mask. This is even more important for the upcoming 5G wireless systems which are based on a variety of wireless transmission protocols (such as mobile networks, Internet of Things (IoT) and machine to machine communications) combined in one comprehensive standard. Even for wired channels, there is always a natural bandwidth of the medium (copper wire, coaxial cable, optical fiber)

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OFDM slices the spectrum just like a bread
Wireless/SDR

A Beginner’s Guide to OFDM

In the recent past, high data rate wireless communications is often considered synonymous to an Orthogonal Frequency Division Multiplexing (OFDM) system. OFDM is a special case of multi-carrier communication as opposed to a conventional single-carrier system.  The concepts on which OFDM is based are so simple that almost everyone in the wireless community is a technical expert in this subject. However, I have always felt an absence of a really simple guide on how OFDM works which can prove useful for technical persons not wanting to deal with too much technicalities, such as DSP experts outside communications, computer programmers, ham

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Phase jumps at every zero crossing from modulating data onto the carrier phase for a QPSK waveform
Wireless/SDR

The Fundamental Problem of Synchronization

We have seen in the effect of phase rotation that the matched filter outputs do not map back perfectly onto the expected constellation, even in the absence of noise and no other distortion. Unless this rotation is small enough, it causes the symbol-spaced optimal samples to cross the decision boundary and fall in the wrong decision zone. And even for small rotations, relatively less amount of noise can cause decision errors in this case, i.e., noise margin is reduced. In fact, for higher-order modulation, the rotation becomes even worse because the signals are closely spaced with each other for the

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