- NOMA is a non-orthogonal multiple access technology that can improve spectral efficiency by allowing all users to use all time-frequency resources simultaneously through techniques like power domain multiplexing and successive interference cancellation. However, it increases complexity. - Full duplex technology aims to allow simultaneous uplink and downlink transmission but faces challenges from strong self-interference. Solutions involve antenna separation and self-interference cancellation. - OAM uses the orbital angular momentum of electromagnetic waves to create orthogonal channels at the same frequency but faces challenges in application to cellular networks from atmospheric effects. - Machine learning can optimize 5G across all layers to dynamically improve spectrum efficiency based on conditions.

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Four wireless technologies after 5G
Written By Calio Huang
5G NR is a contradictory complex, and it is difficult to have both capacity and coverage. 5G
expands the system capacity by expanding the bandwidth of the spectrum. The frequency range
extends from below 3GHz in the 4G era to the millimeter wave band, and the single carrier
bandwidth is increased from 20MHz to more than 100MHz. But the higher the frequency band,
the smaller the coverage of the base station, and the operator has to build more base stations.
Today, mainstream 5G deployments use 5G mid-band, which compromises capacity and coverage
advantages, taking into account outdoor and indoor coverage, and further increases cell capacity
and coverage through Massive MIMO technology, allowing operators to build on existing 4G sites
A wide coverage 5G network. However, future-oriented traffic will increase exponentially. Limited
mid-band resources alone are definitely not enough. For this reason, operators have to expand to
the millimeter-wave band. This has brought unprecedented pressure to network construction
investment.
How to do?
Only through technological innovation, we can continuously improve the efficiency of the
spectrum, allow more bits to be carried per Hz, and make 5G deployment as good and
economical as possible. Today we will introduce several major wireless technologies that deserve
attention in the post 5G era and even the 6G era.
NOMA
Multi-access is the core technology of mobile communication. From 1G to 5G, we have
experienced FDMA, TDMA, CDMA and OFDMA. These multiple-access solutions all adopt
orthogonal design to avoid mutual interference between multiple users. The field of mobile
communications has been dedicated to improving the efficiency of the spectrum through the
orthogonality of radio waves. We have adopted various orthogonal methods such as frequency

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division, time division, space division, and code division, but when the orthogonal space is
exhausted, we should How to do?
It's time for NOMA to play.
NOMA, non-orthogonal multiple access, is a multiple access technology planned for 5G (R16
version), which can significantly improve the spectral efficiency of mobile communication
networks.
As we all know, 4G and current 5G use OFDMA (Orthogonal Frequency Division Multiple Access).
The time-frequency resources occupied by each user are separated and mutually orthogonal.
Due to the constraint of orthogonality, each UE is allocated a certain Subcarrier, each UE occupies
part of the frequency resources. And NOMA is different from OFDMA, it is based on
non-orthogonal design, each UE can use all the resources.
NOMA and OFDMA
So, the question is, how does NOMA avoid mutual interference between multiple users?
The basic idea of NOMA is that multiple UE signals are superimposed on the transmitting end,
occupying all time-frequency resources, and sent through the air interface, and on the receiving
end, based on MUD (multi-user detection) and SIC (serial interference cancellation) technology
Decode signals and extract useful signals.
There are two main ways of NOMA: based on the code domain and based on the power domain.
Based on the code domain, a non-orthogonal spreading code is assigned to each user (similar to
the WCDMA code, except that the WCDMA code is orthogonal). Based on the power domain,
that is, each user signal at the transmitting end is superimposed at a different power level.
Taking the power domain-based NOMA scheme as an example, the working principle is as
follows:
The three UE signals are assigned different power levels. The UE1 closest to the base station has
the best channel conditions and is assigned the lowest power, while the UE3 furthest from the
base station is assigned the highest power, and the UE2 in the middle position is assigned a
moderate power. power.
At the transmitting end of the base station, UE1, UE2, and UE3 all occupy the same
time-frequency resources, and the signals of the three are superimposed in the power domain
and transmitted through the air interface.
At the UE receiving end, the SIC first decodes the signal with the strongest received signal
strength, such as UE1, because the power allocated to it is much lower than UE3, it may first
decode the signal of UE3, and determine whether it is its own useful signal by MA signature If not,
delete the signal of UE3, and then repeat the process until it finds its own useful signal.
For UE3, since the power allocated to it is higher than that of UE1 and UE2, the first decoded
signal may be its own useful signal, so it can be decoded directly.
Since NOMA allocates all air interface resources to all users, spectrum efficiency can be improved.
Especially at the cell edge, due to the poor wireless environment, 5G networks using orthogonal
multiple access have to use sparse modulation and coding to overcome channel damage, which
will cause PRB resources to "waste". However, in NOMA, all users use all PRB resources,
regardless of whether they are at the cell center or the edge, thereby improving spectrum
efficiency.

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It is worth mentioning that NOMA can also be used in conjunction with Massive MIMO. Under
Massive MIMO, a physical sector can be split into multiple virtual sectors within the scope of the
broadcast beam. The users served by the virtual sector use NOMA. Because the virtual sectors
are orthogonal, the system capacity can also be increased Further doubling.
However, NOMA also has its own challenges. First, MUD / SIC requires additional calculations,
stronger hardware support, and higher power consumption. Although it is not a problem for the
base station side, it is troublesome for the terminal, which will increase the terminal cost and
power consumption. Second, under NOMA, the base station needs to allocate power to all UEs in
groups, which requires the base station to accurately understand the channel conditions of each
UE.
Full duplex
Today 5G uses TDD duplex mode. In the 4G era, TDD and FDD are included, but strictly speaking,
TDD and FDD are only "half-duplex" because TDD transmits uplink and downlink signals at
different time slots on the same frequency band. Uplink and downlink signals are transmitted on
symmetrical frequency bands, respectively.
The full-duplex technology can realize simultaneous uplink and downlink signal transmission
(sending and receiving signals) in the same frequency band, which will undoubtedly greatly
improve spectrum efficiency. At the same time, because full duplex sends and receives data at
the same time, feedback information can be received after sending the data, which can also
reduce transmission delay.
However, the biggest challenge encountered by full duplex is that the transmitted signal
generates strong self-interference on the received signal. For example, in a cellular network, the
transmission power can be as high as tens of watts, and the received power is only a few
picowatts. This means that the transmission Interfering signals can be billions of times stronger
than the useful signals received, and wireless transmitters will quickly saturate the receiver.
Due to factors such as duplexer leakage, antenna reflection, and multipath reflection, the
transmitted signal is doped into the received signal, resulting in strong self-interference.
How to eliminate these interferences? Fortunately, since the transmitted signals are known, the
transmitted signals can be used as a reference to eliminate self-interference. However, the
reference signal is relatively easy to obtain in the digital domain. When a digital signal is
converted to an analog signal, it is difficult to obtain a reference from it due to the effects of
linear distortion and non-linear distortion. Therefore, to eliminate self-interference in full duplex,
the RF domain is the biggest challenge. Self-interference cancellation technology is currently
progressing, but implementation complexity and cost are too high.
One way to solve this problem is to separate the transmitting and receiving antennas, install
them spaced apart from each other, and then implement decoupling through antenna sidelobe
suppression and other methods, plus space path loss, which can greatly reduce self-interference.
However, this method is feasible on the base station side, but is not feasible on the terminal side
due to space constraints. Therefore, in the end, full-duplex technology may be deployed on the
base station side, while the terminal side may continue to use TDD duplex technology.
OAM
In addition to time, frequency, and polarization, is there a new available orthogonal state of radio

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waves? That is the orbital angular momentum OAM of electromagnetic radiation.
Affected by the spiral phase factor, electromagnetic waves with OAM are called "vortex
electromagnetic waves" and spiral in the direction of propagation. The phase rotation structure
of an electromagnetic wave having OAM is called an OAM mode. Radio waves with different
OAM modes are orthogonal to each other and do not interfere with each other. Therefore,
multiple signals modulated on different OAM modes can be transmitted at the same frequency
point, thereby improving spectrum efficiency. In theory, there are dozens of different OAM values
to modulate the wireless signal, which can effectively improve the spectral efficiency by dozens
of times.
OAM reuse principle
However, so far, the actual demonstration of OAM has been limited to near-field applications.
Atmospheric turbulence can distort OAM of radio waves and cause crosstalk, so OAM has a lot of
work to do before it can be applied to cellular networks.
Machine learning
Machine learning can be used to optimize 5G air interfaces to improve spectrum efficiency.
All layers of 5G NR can be optimized through machine learning. For example, machine learning
can optimize modulation, FEC, MIMO, signal detection, power control, and beamforming at the
physical layer, and machine learning can optimize scheduling, HARQ, and traffic at layer 2. Control,
machine learning can also optimize layer three mobility management, load management and
connection management. Machine learning, especially deep reinforcement learning, can
dynamically make optimization decisions based on traffic conditions and wireless environments
to keep the network in the best state at all times.
Taking the modulation method as an example, a higher-order modulation method can increase
the transmission rate. For example, in the 4G era, we hope that all UEs can maximize the use of
256QAM to obtain better spectral efficiency. But this is impossible in reality, because as the SINR
decreases (such as when the UE is located at the cell edge), the higher-order QAM constellation
will be distorted, making it more difficult for the receiver to demodulate. With machine learning,
it is possible to demodulate a higher order modulation method with a lower SINR by learning
complex distortion patterns, thereby improving the spectral efficiency of the system.