Today, I will demonstrate a technology we call super-QAM, which can significantly increase speeds
and lower energy usage. Some recent exciting news is that 3GPP approved 'Green Networks' as part of
5G release 18. This opens a great opportunity for super-QAM and other technologies to make
5G a greener network. Let's first have a quick look at how super-QAM works. The key concept
is to reduce the noise in the receiver in an iterative fashion to incrementally improve the
signal quality. The iteration cycle goes through three steps: first reducing the phase noise,
then addressing non-linearities from the power amplifier, and finally rectifying IQ imbalances.
This iterative cycle is performed in two phases. First on the reference signal to achieve a clean
channel estimation and then on the data itself to achieve the best possible signal quality.
With improved signal quality we can utilize higher order modulation, which improves throughput speeds.
If we can improve the signal quality so we can use 1024-QAM, then the throughput speed increases. And
as we increase the order of the modulation the throughput speed keeps increasing, and increasing.
When we reach 16K-QAM we have boosted the throughput speed with 75% from where we started. In
our first demo I will show our non-real-time setup that is operating in sub 7 GHz spectrum band.
The setup is comprised of an FPGA board which is used to transmit predefined signals through 8
channels. Each channel has a base station power amplifier, preceded by controlled attenuator and
a pre-amp stage. A realistic fading channel for each path is then emulated by an 8x8 channel emulator.
Finally the received signal is captured by a set of UXR scopes. Here we see the spectrum of the
transmitted signal... And when increasing the signal transmit power, we can see the non-linearity floor
going up. Let's see how super-AQM can clean up a noisy 16K-QAM signal. Since 16K-QAM has
so many points, we have to zoom in to see what happened. In the top left corner, we see how the
signal looked like before we started. If we look at the subsequent plots, we can see how super-QAM
is able to significantly improve the signal quality. We repeat this testing for different
transmit powers and in this diagram we can see how super-QAM allows proper decoding of 16K-QAM.
In our second demo I will show you our millimeter wave setup, which we are running over-the-air
in real-time. Here you can see our anechoic chamber, where we set up a transmitter chain
creating a test signal using two layers, which are transmitted using an RF head
with 64 antenna elements per layer. To model different levels of signal qualities, we
apply different levels of transmit gain. On the receiver side we are using our mobile test device
with Snapdragon X50 5G modem-RF system that can perform the super-QAM technology in real-time.
On the spectrum analyzer we can see the spectrum of the transmitted signal
and when we increase the transmit power we can see the non-linearity floor going up. Here you can see
our real-time demo interface, where we can adjust different parameters like number of iterations.
We can also see the performance in terms of block error rate error, vector magnitude, ACLR and the
throughput speed. As you can see, before super- QAM is applied we have inadequate performance
with block error rate of 100% and error vector magnitude worse than minus 30 dB.
Now let's see what happens if we apply super-QAM. On this plot we can see how the 1k-QAM constellation
looks like after each iteration. On the top left we see how it looked before we started.
The next one shows after we apply one digital post distortion iteration... and then another one
combined with phase noise correction... followed by three more phase noise correction iterations.
As you can see, the signal is much improved compared to when we started. And the error vector
magnitude is reduced to -38 dB, which allows for proper decoding of 1K-QAM with low error rates.
As you can see the measured throughput is 1.3 Gbps over 100 MHz
channel or about 10 Gbps over a more typical 800 MHz channel. This represents a 66%
gain over today's 64 QAM. In this demonstration we have seen how our super-QAM technology
can improve the signal quality to support higher order modulation.
In our sub 7 GHz lab setup we were able to support a revolutionary 16k-QAM. And in our
millimeter wave over-the-air setup running in real- time we demonstrated 1K-QAM. With super-QAM
we can both significantly boost data speeds and reduce energy utilization for greener networks.