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41 | 5G NR does this by using scalable orthogonal frequency-division multiplexing (ODFM) waveforms that allow different subcarrier signal spacing to fit the various channel widths that different frequency ranges provide. Higher frequencies provide wider channels and greater subcarrier spacing. Lower frequencies use smaller channel widths and narrower subcarrier spacing. Scaling subcarrier spacing to available channel widths enables the 5G framework to operate across a broad range of frequencies. The result makes it possible to deploy 5G in existing 4G Long-Term Evolution (LTE) networks. It also makes it possible for 5G communications systems to switch between low- and high-frequency bands based on use cases or workload requirements. The challenge for antenna designers is physics. A 1GHz signal, which is in FR1, has a wavelength of about 30 centimeters (cm). A 28GHz signal in FR2 has a wavelength of 1.07mm. The same antenna will not work for these two signals, so 5G devices operating in both FR1 and FR2 bands will require at least two sets of antennas. This is manageable in large equipment and base stations that have room for multiple antenna arrays. It becomes a significant design challenge for small devices and cell phones. Some manufacturers—Qualcomm®, for instance—have begun releasing compact radio-frequency (RF) modules capable of operating with antenna arrays in multiple 5G bands. Device Density, Data Throughput, and Massive MIMO One challenge presented by the 5G specification is the need to support much higher densities of connected devices that are operating simultaneously at much higher data rates. This will require higher cell densities and more extensive use of the multiple input, multiple output (MIMO) antenna technologies already in use in 4G LTE networks. MIMO is an antenna array of multiple transmitting and receiving antennas (which in current LTE networks, often contains an 8 x 8 antenna array). MIMO uses spatial multiplexing to break a signal into encoded streams that it simultaneously transmits through different antennas in the array. Both the transmitting and receiving devices have multiple antennas and signal processing for encoding and decoding multiplexed signals. This makes it possible to: • Communicate with multiple users and devices simultaneously. • Communicate with higher throughput. Many variations of MIMO exist. A key variation for 5G is massive MIMO (mMIMO), an antenna design that packs many more antenna elements into a dense array than previous MIMO versions. Lower-frequency antennas are larger, which creates practical limits to how many antenna elements will fit in a reasonably sized low-frequency MIMO array. Millimeter wavelengths work with much smaller antennas, which makes it possible to build mMIMO arrays in small packages. Some manufacturers are building mMIMO antennas that contain 128 elements. By increasing the number of data streams, mMIMO increases signal capacity without requiring more spectrum, which in turn increases data rates and link reliability. Beamforming, Directionality, and User Equipment Tracking Beamforming is a method of shaping a transmission to create a well- defined antenna pattern targeted at a specific receiving antenna. It is done by adjusting phase and amplitude transmissions through different antenna elements in an array of equally spaced antennas. Beamforming can be used to reduce interference, and it also increases range by concentrating beam energy. Initial 5G deployments using mid- band frequencies will employ 4 x 4 or 8 x 8 MIMO antennas set up to enable beamforming, similar to what is currently available in LTE. High frequency (millimeter wavelength) 5G deployments will take advantage of adaptive arrays using larger mMIMO antennas with many more antenna elements and capable of tighter beamforming and real-time steering. 5G beamforming depends on a transmitting device's determination of the optimum signal path to its receiver. The transmitter does this by analyzing the sounding reference signals (SRSs) sent between the transmitter and the receiver, and then evaluating these signals to establish the channel state. Based on channel state information (CSI), the transmitter applies beamforming algorithms that transmit shaped radio patterns in the optimum direction and during the best schedule for the best reception. Beamforming will bounce transmissions off buildings if that is the optimum path to a receiver. In an environment where many devices use the same mMIMO channels, algorithms will time data packets to avoid packet collisions, minimizing signal interference.

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