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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Diversity implies two or more independent replicas of the same information

Multiple Antenna Techniques

When computing approaches the physical limits of clocking speeds, we turn towards multi-core architectures. When communication approaches the physical limits of transmission speeds, we turn towards multi-antenna systems. What exactly are the benefits that led to scientists and engineers choosing multiple antennas as the foundation of 4G and 5G PHY layers? While having spatial diversity was the original incentive for adding antennas at the base stations, it was discovered in mid 1990s that multiple antennas at Tx and/or Rx sides open up other possibilities not foreseen in single antenna systems. Let us now describe three main techniques in this context.

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Analog beamforming

What is the Difference between Analog, Digital and Hybrid Beamforming?

Beamforming is one of the most practical solutions to overcome higher path loss and atmospheric attenuation in mmWave bands. How it is implemented is a matter of great interest to RF industry due to the conflicting requirements of efficiency and flexibility. In a tradeoff between cost, size and complexity, analog beamforming is combined with digital beamforming to give rise to a hybrid solution, an architecture of choice in current 5G mmWave systems. Nevertheless, digital beamforming is inevitably the direction of future and it is only a matter of time before it will be used in 5G networks in high bands

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A symbolic representation of aligning the Tx weights and Rx weights according to the channel conditions for maximum throughput

Singular Value Decomposition (SVD) – A Tutorial with an Application to Wireless Systems

Singular Value Decomposition (SVD) is a powerful concept in linear algebra whose relevance has significantly increased in recent times. Some of the notable examples are its applications in machine learning, data science and wireless communication systems. In this tutorial, I will explain the logic behind SVD from a non-mathematical viewpoint using a wireless application that forms the backbone of high speed wireless systems such as WiFi, 4G and 5G. What is Orthogonality and Why We Like It Orthogonality is a concept that comes with heavy mathematical details. However, it can be explained in a simple and non-rigorous manner. Look at

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