418,201 research outputs found
Slocalization: Sub-{\mu}W Ultra Wideband Backscatter Localization
Ultra wideband technology has shown great promise for providing high-quality
location estimation, even in complex indoor multipath environments, but
existing ultra wideband systems require tens to hundreds of milliwatts during
operation. Backscatter communication has demonstrated the viability of
astonishingly low-power tags, but has thus far been restricted to narrowband
systems with low localization resolution. The challenge to combining these
complimentary technologies is that they share a compounding limitation,
constrained transmit power. Regulations limit ultra wideband transmissions to
just -41.3 dBm/MHz, and a backscatter device can only reflect the power it
receives. The solution is long-term integration of this limited power, lifting
the initially imperceptible signal out of the noise. This integration only
works while the target is stationary. However, stationary describes the vast
majority of objects, especially lost ones. With this insight, we design
Slocalization, a sub-microwatt, decimeter-accurate localization system that
opens a new tradeoff space in localization systems and realizes an energy,
size, and cost point that invites the localization of every thing. To evaluate
this concept, we implement an energy-harvesting Slocalization tag and find that
Slocalization can recover ultra wideband backscatter in under fifteen minutes
across thirty meters of space and localize tags with a mean 3D Euclidean error
of only 30 cm.Comment: Published at the 17th ACM/IEEE Conference on Information Processing
in Sensor Networks (IPSN'18
Efficient Integer Frequency Offset Estimation Architecture for Enhanced OFDM Synchronization
An integer frequency offset (IFO), in orthogonal
frequency-division multiplexing (OFDM) systems, causes a circular
shift of the sub-carrier indices in the frequency domain.IFO
can be mitigated through strict RF front-end design but this
is challenging and expensive. Therefore, IFO is estimated and
removed at baseband, allowing the RF front-end specification
to be relaxed, thus reducing system cost. For applications
susceptible to Doppler shift, and multi-standard radios requiring
wide frequency range access, careful RF design may be
insufficient without IFO estimation. This paper proposes a novel
approach for IFO estimation with reduced power consumption
and computational cost. A four-fold resource sharing architecture
reduces computational cost, while a multiplierless technique and
carefully optimised wordlengths yield further power reduction
while maintaining a good accuracy. The novel method is shown
to achieve excellent performance, similar to the theoretically
achievable bound. In fact, performance is significantly better
than conventional techniques, while being much more efficient.
When implemented for IEEE 802.16-2009, the proposed method
saves 78% power over the conventional technique on low-power
FPGA devices. The method is applicable to IEEE 802.11 and
IEEE 802.22
Multi Detector Fusion of Dynamic TOA Estimation using Kalman Filter
In this paper, we propose fusion of dynamic TOA (time of arrival) from
multiple non-coherent detectors like energy detectors operating at sub-Nyquist
rate through Kalman filtering. We also show that by using multiple of these
energy detectors, we can achieve the performance of a digital matched filter
implementation in the AWGN (additive white Gaussian noise) setting. We derive
analytical expression for number of energy detectors needed to achieve the
matched filter performance. We demonstrate in simulation the validity of our
analytical approach. Results indicate that number of energy detectors needed
will be high at low SNRs and converge to a constant number as the SNR
increases. We also study the performance of the strategy proposed using IEEE
802.15.4a CM1 channel model and show in simulation that two sub-Nyquist
detectors are sufficient to match the performance of digital matched filter
MmWave Massive MIMO Based Wireless Backhaul for 5G Ultra-Dense Network
Ultra-dense network (UDN) has been considered as a promising candidate for
future 5G network to meet the explosive data demand. To realize UDN, a
reliable, Gigahertz bandwidth, and cost-effective backhaul connecting
ultra-dense small-cell base stations (BSs) and macro-cell BS is prerequisite.
Millimeter-wave (mmWave) can provide the potential Gbps traffic for wireless
backhaul. Moreover, mmWave can be easily integrated with massive MIMO for the
improved link reliability. In this article, we discuss the feasibility of
mmWave massive MIMO based wireless backhaul for 5G UDN, and the benefits and
challenges are also addressed. Especially, we propose a digitally-controlled
phase-shifter network (DPSN) based hybrid precoding/combining scheme for mmWave
massive MIMO, whereby the low-rank property of mmWave massive MIMO channel
matrix is leveraged to reduce the required cost and complexity of transceiver
with a negligible performance loss. One key feature of the proposed scheme is
that the macro-cell BS can simultaneously support multiple small-cell BSs with
multiple streams for each smallcell BS, which is essentially different from
conventional hybrid precoding/combining schemes typically limited to
single-user MIMO with multiple streams or multi-user MIMO with single stream
for each user. Based on the proposed scheme, we further explore the fundamental
issues of developing mmWave massive MIMO for wireless backhaul, and the
associated challenges, insight, and prospect to enable the mmWave massive MIMO
based wireless backhaul for 5G UDN are discussed.Comment: This paper has been accepted by IEEE Wireless Communications
Magazine. This paper is related to 5G, ultra-dense network (UDN), millimeter
waves (mmWave) fronthaul/backhaul, massive MIMO, sparsity/low-rank property
of mmWave massive MIMO channels, sparse channel estimation, compressive
sensing (CS), hybrid digital/analog precoding/combining, and hybrid
beamforming. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=730653
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