8,552 research outputs found
Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions
Massive MIMO is a compelling wireless access concept that relies on the use
of an excess number of base-station antennas, relative to the number of active
terminals. This technology is a main component of 5G New Radio (NR) and
addresses all important requirements of future wireless standards: a great
capacity increase, the support of many simultaneous users, and improvement in
energy efficiency. Massive MIMO requires the simultaneous processing of signals
from many antenna chains, and computational operations on large matrices. The
complexity of the digital processing has been viewed as a fundamental obstacle
to the feasibility of Massive MIMO in the past. Recent advances on
system-algorithm-hardware co-design have led to extremely energy-efficient
implementations. These exploit opportunities in deeply-scaled silicon
technologies and perform partly distributed processing to cope with the
bottlenecks encountered in the interconnection of many signals. For example,
prototype ASIC implementations have demonstrated zero-forcing precoding in real
time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing
of 8 terminals). Coarse and even error-prone digital processing in the antenna
paths permits a reduction of consumption with a factor of 2 to 5. This article
summarizes the fundamental technical contributions to efficient digital signal
processing for Massive MIMO. The opportunities and constraints on operating on
low-complexity RF and analog hardware chains are clarified. It illustrates how
terminals can benefit from improved energy efficiency. The status of technology
and real-life prototypes discussed. Open challenges and directions for future
research are suggested.Comment: submitted to IEEE transactions on signal processin
Living IoT: A Flying Wireless Platform on Live Insects
Sensor networks with devices capable of moving could enable applications
ranging from precision irrigation to environmental sensing. Using mechanical
drones to move sensors, however, severely limits operation time since flight
time is limited by the energy density of current battery technology. We explore
an alternative, biology-based solution: integrate sensing, computing and
communication functionalities onto live flying insects to create a mobile IoT
platform.
Such an approach takes advantage of these tiny, highly efficient biological
insects which are ubiquitous in many outdoor ecosystems, to essentially provide
mobility for free. Doing so however requires addressing key technical
challenges of power, size, weight and self-localization in order for the
insects to perform location-dependent sensing operations as they carry our IoT
payload through the environment. We develop and deploy our platform on
bumblebees which includes backscatter communication, low-power
self-localization hardware, sensors, and a power source. We show that our
platform is capable of sensing, backscattering data at 1 kbps when the insects
are back at the hive, and localizing itself up to distances of 80 m from the
access points, all within a total weight budget of 102 mg.Comment: Co-primary authors: Vikram Iyer, Rajalakshmi Nandakumar, Anran Wang,
In Proceedings of Mobicom. ACM, New York, NY, USA, 15 pages, 201
- …