Category Archives: Standards

GSM, WCDMA, LTE, 5G.

5G Millimeter Waves: Are They Really Harmful

There has been a continuous debate about harmful effects of Electromagnetic Radiations ever since they came into existence. Most of the research results suggest that there are no harmful effects, if the rules and regulations are followed. But there is a small body of research that suggests that there might be some harmful effects and more research needs to be carried out. This is particularly important now as 5G Wireless Technology is being rolled out around the world and it uses millimeter waves for which we have limited data. Also, 5G would be using much smaller cells meaning that base stations would be closer to human beings.

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Low Density Parity Check Codes

We have previously discussed Block Codes and Convolutional Codes and their coding and decoding techniques particularly syndrome-based decoding and Viterbi decoding. Now we discuss an advanced form of Block Codes known as Low Density Parity Check (LDPC) codes. These codes were first proposed by Robert Gallager in 1960 but they did not get immediate recognition as they were quite cumbersome to code and decode. But in 1995 the interest in these codes was revived, after discovery of Turbo Codes. Both these codes achieve the Shannon Limit and have been adopted in many wireless communication systems including 5G.

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Reconfigurable Intelligent Surfaces Explained

Wireless channel is inherently unpredictable and this results in loss of information as it travels from the transmitter to the receiver. The main reason for this is that multiple copies of the wireless signal arrive at the receiver which sometimes add constructively and at other times destructively, causing deep fades. The deciding factor between signal copies (think of them as echoes) adding constructively or destructively is the relative phase. If the phases are aligned the signals add up but if the phases are not aligned, we get a fade (fades can be as deep as 60-80dB). Wireless engineers over the years have worked around this problem by using multiple antennas also called antenna arrays.

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Beyond Massive MIMO

Recently Björnson and Marzetta in their publication on Antenna Arrays [1] discussed five possible future research directions. In their opinion Massive MIMO is no longer a theoretical concept and it is already being adopted in the industry. It is not uncommon to find 64 element antenna arrays being deployed in wireless communication systems. So we now need to look beyond Massive MIMO or MaMIMO as it is popularly referred to. Here are three possible future research directions that we find most interesting.

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60 GHz Millimeter Wave Band – Seems Like a Free Lunch

Let us start by first listing down the advantages of the 60 GHz Millimeter Wave Band, a band spread between 57 GHz and 64 GHz. This unlicensed band was first released in the US in 2001 but with limited allowance for transmit power (EIRP of 40 dBm). Later on, in 2013, this limit was increased to allow for greater transmit power (EIRP of 82 dBm) and larger range. The higher EIRP can be achieved with an antenna gain of 51 dBi or higher (EIRP is simply the product of transmit power and antenna gain). But first the advantages:

  1. Unlicensed band means you do not have to pay for using the frequencies in this band.
  2. Wide bandwidth of 7 GHz allows high data rate transmissions. Remember Shannon Capacity Theorem?
  3. High atmospheric absorption resulting in greater path loss (up to 20 dB/km) and shorter range. This means lesser co-channel interference and higher reuse factor.
  4. Smaller antenna sizes allowing for multiple antennas to be put together in the form of an array providing high gain.
  5. This band is quite mature and electronic components are cheap and easily available.
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Massive MIMO and Antenna Correlation

Some Background

In a previous post we calculated the Bit Error Rate (BER) of a Massive MIMO system using two different channel models namely deterministic and probabilistic. The deterministic channel model is derived from the geometry of the array (ULA in this case) and the distribution of users in the cell. Whereas probabilistic channel model assumes that the channel is flat fading and can be modeled, between each transmit receive pair, as a complex, circularly symmetric, Gaussian random variable with mean of zero and variance of 0.5 per dimension.

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