At Qualcomm Technologies, we are pioneering the future of wireless communications as we expand
5G into new use cases and deployments. Our work in cellular positioning started a few decades ago,
and last year, we showcased our OTA prototypes for wide-area positioning.
This year, we're continuing to push the technology boundary to enable enhanced positioning services.
In this video, we'll showcase how we are taking positioning into the millimeter wave
spectrum as well as supporting improved performance for narrowband IoT devices.
For data communications, 5G millimeter wave unlocks extreme network capacity and takes
user experiences to new heights. On the other hand, millimeter wave can
also support new classes of non-data services such as enabling precise cellular positioning.
This year, we have implemented positioning capability in our over the air test network
in San Diego, California to showcase the level of accuracy achievable in a millimeter wave network.
Here is our millimeter wave test network setup, which operates in the 28 Gigahertz band.
There are four transmission and reception points that cover the hotspot deployment.
In this test, we have a 5G NR mobile test device based on the Snapdragon 5G Modem-RF system
that moves along the courtyard. In this demo, we are utilizing a multi-TRP downlink AoD positioning
approach, where the device measures and estimates the angle of departure of the reference signals
sent from the transmission points. The numbers in the user interface mark the different locations
where we took positioning measurements of the device. Let's select a location.
We now see the KPIs associated with the measurements in comparison with the ground truth.
The dark blue dot in the middle of the circle is the actual device location.
The lighter blue dots are the positioning error, and the red circle marks the error
threshold in the xy plane. Cycling through the different measured locations, we can see
the average positioning accuracies are in the meter range. In addition to this OTA prototype,
we have also simulated 5G millimeter wave positioning performance with various techniques
under a wide range of locations and conditions such as for an indoor factory as well as a city
level macro deployment, which showed comparable performance under similar assumptions. In
conclusion, 5G millimeter wave can deliver precise positioning for diverse use cases and deployments.
While we exploit the wide bandwidth nature of 5G to achieve high positioning accuracy, many 5G IoT
devices will operate more efficiently with lower bandwidth, like wearables and industrial sensors.
With 20 Megahertz or 5 Megahertz 5G NR-Light, pure timing-based techniques do not work as well,
since the narrow bandwidth reduces time domain resolution and network synchronization errors lead
to less accurate positioning. To deliver improved positioning accuracy for narrowband devices, a
device-based positioning technique like multi-cell downlink angles of departure can be utilized.
Based on the positioning reference signals sent from the gNodeB, the device can estimate the
angle of departure based on relative differences in beam RSRP, or received signal strength, which
is not sensitive to the reduced bandwidth. With multiple downlink AoD measurements, the position
of the device can be determined. Our system simulation utilizes an urban micro model,
with 57 cells operating in the 4 Gigahertz band. For each of the gNodeB, we assumed a massive
MIMO implementation of 256 antenna elements with 64 digital ports. On the device side,
we assumed low complexity IoT sensors with a single antenna. In the first scenario,
we have 5 Megahertz narrowband devices utilizing a timing based positioning technique, downlink TDOA
positioning accuracy gets impacted by the reduced time resolution and network synchronization errors.
We then switch the positioning methodology to a multi-cell downlink AoD, and our simulations
show the accuracy improves significantly compared to the previous case. In conclusion,
multi-cell downlink AoD is a positioning solution that can deliver
accurate low-power and wide-area positioning for a massive number of low-complexity 5G IoT devices
over 5 Megahertz channels with asynchronous base stations.