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how do you even measure the frequency of a digital signal? This may be the source of your confusion. In digital communications, data is transmitted using an analog, continuous-time waveform. This is necessary because only this kind of waveform can exist in the physical world. Like all waveforms, it has a bandwidth, and its Fourier Transform determines what ...

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Orthogonality might be considered in literature as background knowledge. The definition is somehow a converse version. If $\cdot$ denotes an inner product (or a dot or scalar product), and whenever $\mathbf f_a \cdot \mathbf f_b = 0$, then $f_a$ and $f_b$ are said to be orthogonal. Note that, if $\mathbf f_a$ is zero, it is orthogonal to everything.

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They are little bit different in performing the $DFT$ and the adding of $CP$. her you can read more details about those differences : https://sci-hub.tw/10.1109/ICC.2009.5198846 Good luck

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Here's an attempt at an answer, by comparing your equations with the more commonly used ones. We can write the "pulse rate" or the "signaling rate" $R_p$, measured in baud, or equivalently in pulses per second or symbols per second, as: $$R_p = \frac{1}{k} R_b,$$ where $R_b$ is the bit rate, and $k$ is the number of bits carried by a pulse. To elaborate: a ...

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It's not possible to recover the original signal $X$ based on $h$ perfectly !! $Filter$ or $conv$ are usually performed in time domain, so it's similar "But not exactly" to $y = conv(X,h)$ , So in that case after you know $h$ or in other words after you estimate $h$ , you need to use any equalizer like $ZF$ or $MMSE$ to get back $X$. Of course, ...

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In general, what you want is impossible! Not every operation is reversible. In frequency domain, that becomes obvious: a system's frequency response $H(f)$ might have actual zeros at some points, and thus, no inverse filter exists. Multiplication with zero can't be undone, since no matter what was at that frequency before filtering, it's 0 afterwards and we ...

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First (i) I know that analog signals are continuous and digital signals are discrete. Analog signal are represented by a continuous time-varying quantity like voltage. How are digital signals represented in actual practice? I mean to ask how are the 0s & 1s actually represented/transmitted over a transmission medium? Are they represented ...

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What the CDF of the capacity tells you is how it distributes, which allows you to say something about the quantiles. Ergodic capacity tells you: what capacity will we see on average? Quantiles are more relevant in practice: what capacity can we guarantee with 95% certainty? 99%? 99.9%? For this, you need a CDF and more often than not, you'll see a heavy-...

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The diagram from the textbook in the opening post appears to have some mistakes. For this IFFT method, the box that says 'QAM modulator' should just be a complex number converter (such as a digital QAM converter that produces a complex number from 'x' binary bits at a time - that is meant to represent a vector on a QAM grid). And there should be two D/A ...

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