Constructive and destructive interference arising from the different delays of multipath

Small-Scale Fading in a Wireless Channel

Small-scale fading is a phenomenon that arises due to the unguided nature of the wireless medium. Dramatic variations in signal amplitude occur at the Rx from constructive and destructive interference of multipath components originating from the surrounding environment that give rise to small-scale fading. This is the main challenge for designing efficient high-rate wireless communication systems which spawned an array of research activities in the past 50 years aimed to bring the wireless transmission rates closer to their wire counterparts. The technologies for 5G systems have been chosen with the benefit of experience gained from actual implementations over these years.

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Intuition behind LMS algorithm

Least Mean Square (LMS) Equalizer – A Tutorial

The LMS algorithm was first proposed by Bernard Widrow (a professor at Stanford University) and his PhD student Ted Hoff (the architect of the first microprocessor) in the 1960s. Due to its simplicity and robustness, it has been the most widely used adaptive filtering algorithm in real applications. An LMS equalizer in communication system design is just one of those beautiful examples and its other applications include noise and echo cancellation, beamforming, neural networks and so on. Background The wireless channel is a source of severe distortion in the received (Rx) signal and our main task is to remove the

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mmWave and THz bands

An Introduction to mmWave Band

Rising wireless traffic demands a continuous improvement in aggregate data rates delivered within a geographical area. One of the fundamental resources to achieve this goal is increasing the bandwidth. A wider bandwidth directly translates into higher throughput, just like increasing the number of lanes on a road directly impacts the traffic handled at peak times. This is the original reason for opening up the higher GHz and THz bands where vast amounts of empty spectrum is available. A bird’s eye view of the history of wireless transmission reveals that the wireless throughput increase during the past century has relied far

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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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A quasi-static assumption implies that the channel stays the same for each block but varies from one block to the next

A Time-Varying Wireless Channel

Today we will discuss three strategies that are usually adopted for handling a wireless channel that is varying with time and hence acting differently on different data symbols. For a channel impulse response $c(t)$, number of multipath $N_{MP}$, channel gains $\gamma_i(t)$ and delays $\tau_i(t)$ for the $i$-th path, respectively, we can write \begin{equation*} c_B(t) = \sum _{i=0}^{N_{MP} -1} \gamma_i(t) \cdot \delta(t-\tau_i(t)) \end{equation*} i.e., channel gains $\gamma_i(t)$ and channel delays $\tau_i(t)$ are varying with time albeit at different rates. With the movement in the channel, the taps in a frequency selective channel are changing according to the rotation rates of path

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