Due to a Sampling Clock Offset (SCO), a fast Rx clock collects extra samples

Effect of Sampling Clock Offset on a Single-Carrier Waveform

We have discussed before the distortion caused by a symbol timing offset on the communication waveform. We have also derived a maximum likelihood estimate of the clock phase offset. In this article, we describe the impact of a sampling clock offset in a single-carrier waveform, also commonly known as a clock frequency offset or timing drift. A clock frequency offset is defined as the rate mismatch between the Tx and Rx clocks. Just like a carrier phase and frequency offset, the clock used to sample the incoming continuous-time signal at a rate $T_S=1/F_S$ contains a phase and frequency offset as

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A Tuned radio Frequency Receiver (TRF) selects the desired channel through a bandpass filter

Tuned Radio Frequency (TRF) Receiver

The tasks of a communications receiver to demodulate the transmitted signal begin with selecting the signal within a specific bandwidth at a desired frequency, commonly known as a particular channel. In another article, we discuss specifications for a radio receiver such as dynamic range, noise floor and sensitivity. Today we discuss an architecture used in earlier generations of radios. To avoid interference from the neighboring channels, the most straightforward approach is to filter out the spectral contents outside this channel and amplify the desired signal in one or more RF amplification stages. This was one of the earliest techniques employed

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The Arrival of 6G

Recently, IEEE Communications Society published an article “What will 6G be?” Some of the important points it highlighted are the following. More spectrum is needed for more bits: As with all new Gs, more spectrum is needed to entertain more bits 🙂 Sometimes I wonder where exactly we have made a phenomenal progress in delivering orders of magnitude higher data rates. According to Gerhard Fettweis, several bands between 100 and 300 GHz show some promise. Bits/s/$m^3$: Since the success of a company is measured in the revenue generated, and not exactly the bits delivered per second, the real focus is

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Computing noise power within a specified bandwidth

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 receiver electronics. You can also watch the video below. The term additive white Gaussian noise (AWGN) originates due to the following reasons: [Additive] The noise is additive, i.e., the received signal is equal to the transmitted signal plus noise. This gives the most widely used equality in communication systems. \begin{equation}\label{eqIntroductionAWGNadditive} r(t) = s(t)

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Coverage and throughput in different bands

Channel Propagation Effects in mmWave Systems

In a previous article, we have discussed in detail the free space propagation in mmWave systems. We saw that the received power at any distance is independent of the carrier frequency as long as the effective antenna aperture is taken into account. Today, we describe the role of atmospheric effects such as water vapors, oxygen, rain and penetration loss in materials that impact the signal propagation at higher carrier frequencies. Important parameters of small-scale fading in a wireless channel such as delay spread and Doppler spread are also explained in the context of mmWave systems. Atmospheric Effects In realistic channels,

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