Symbolic representation of linear phase rotation that changes with frequency index

Effect of Time Shift in Frequency Domain

Children usually ask questions like “How many hours have passed?” And they have no idea about the start time to be taken as a reference. Just like the zero of a measuring tape, a zero reference for time plays a crucial role in analyzing the signal behaviour in time and frequency domains. Until now, we assumed that reference time $0$ coincides with the start of a sine and a cosine wave to understand the frequency domain. Later, we will deal with symbol timing synchronization problem in single-carrier systems and carrier frequency synchronization problem in multicarrier systems, both of which address

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Classification of carrier frequency synchronization algorithms

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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SINAD for signal, noise and distortion

How to Compute SINAD in a Radio Receiver

In theory, the quantity that determines the performance of a radio receiver is the Signal to Noise Ratio (SNR). In linear terms, this is simply the ratio of the signal power versus the noise power appearing at the demodulator input. \[ SNR = 10\log_{10} \frac{P_S}{P_N} \] where $P_S$ is the signal power and $P_N$ is the noise power within the spectrum. However, when experimental measurements are carried out in order to verify the theoretical conclusions, SNR alone is not enough and there is another quantity, known as SINAD, that governs the receiver performance. What is SINAD SINAD stands for Signal

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Decision boundary for multivariate logistic regression

Logistic Regression in Machine Learning

A hundred thousand years ago, our ancestors used to roam in the savannas and jungles. It was absolutely necessary for them to judge (or classify) everything they encounter: a movement in the bushes could be due to a harmless rabbit or a dangerous tiger, a fruit on a plant could be nutritious or poisonous, and so on. Then came the wizards who invented language and then people developed agriculture, writing and industry. The advancement in civilization and the quest for scientific knowledge revealed the benefits of a wide spectrum and viewing shades of gray instead of of simple black and

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A 2x2 MIMO spatial multiplexing system

Linear Detection Algorithms in MIMO Systems

In the past 100 years, scientists have imagined new ways of boosting the capacity of wireless channels. Around the middle of 20th century, we began to truly understand the role of fundamental players in this equation, namely power and bandwidth. It was realized that the capacity of a wireless channel increases logarithmically with SNR and hence quickly approaches the region of diminishing returns. Nevertheless, with a few exceptions, almost all the research was exclusively focused on single antenna systems. It was only in mid 1990s that the power of using multiple antennas at both ends of the link was discovered.

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