2,878 research outputs found
Key Generation in Wireless Sensor Networks Based on Frequency-selective Channels - Design, Implementation, and Analysis
Key management in wireless sensor networks faces several new challenges. The
scale, resource limitations, and new threats such as node capture necessitate
the use of an on-line key generation by the nodes themselves. However, the cost
of such schemes is high since their secrecy is based on computational
complexity. Recently, several research contributions justified that the
wireless channel itself can be used to generate information-theoretic secure
keys. By exchanging sampling messages during movement, a bit string can be
derived that is only known to the involved entities. Yet, movement is not the
only possibility to generate randomness. The channel response is also strongly
dependent on the frequency of the transmitted signal. In our work, we introduce
a protocol for key generation based on the frequency-selectivity of channel
fading. The practical advantage of this approach is that we do not require node
movement. Thus, the frequent case of a sensor network with static motes is
supported. Furthermore, the error correction property of the protocol mitigates
the effects of measurement errors and other temporal effects, giving rise to an
agreement rate of over 97%. We show the applicability of our protocol by
implementing it on MICAz motes, and evaluate its robustness and secrecy through
experiments and analysis.Comment: Submitted to IEEE Transactions on Dependable and Secure Computin
A Comparison of CP-OFDM, PCC-OFDM and UFMC for 5G Uplink Communications
Polynomial-cancellation-coded orthogonal frequency division multiplexing
(PCC-OFDM) is a form of OFDM that has waveforms which are very well localized
in both the time and frequency domains and so it is ideally suited for use in
the 5G network. This paper analyzes the performance of PCC-OFDM in the uplink
of a multiuser system using orthogonal frequency division multiple access
(OFDMA) and compares it with conventional cyclic prefix OFDM (CP-OFDM), and
universal filtered multicarrier (UFMC). PCC-OFDM is shown to be much less
sensitive than either CP-OFDM or UFMC to time and frequency offsets. For a
given constellation size, PCC-OFDM in additive white Gaussian noise (AWGN)
requires 3dB lower signal-to-noise ratio (SNR) for a given bit-error-rate, and
the SNR advantage of PCC-OFDM increases rapidly when there are timing and/or
frequency offsets. For PCC-OFDM no frequency guard band is required between
different OFDMA users. PCC-OFDM is completely compatible with CP-OFDM and adds
negligible complexity and latency, as it uses a simple mapping of data onto
pairs of subcarriers at the transmitter, and a simple weighting-and-adding of
pairs of subcarriers at the receiver. The weighting and adding step, which has
been omitted in some of the literature, is shown to contribute substantially to
the SNR advantage of PCC-OFDM. A disadvantage of PCC-OFDM (without overlapping)
is the potential reduction in spectral efficiency because subcarriers are
modulated in pairs, but this reduction is more than regained because no guard
band or cyclic prefix is required and because, for a given channel, larger
constellations can be used
Secret Key Generation Based on AoA Estimation for Low SNR Conditions
In the context of physical layer security, a physical layer characteristic is
used as a common source of randomness to generate the secret key. Therefore an
accurate estimation of this characteristic is the core for reliable secret key
generation. Estimation of almost all the existing physical layer characteristic
suffer dramatically at low signal to noise (SNR) levels. In this paper, we
propose a novel secret key generation algorithm that is based on the estimated
angle of arrival (AoA) between the two legitimate nodes. Our algorithm has an
outstanding performance at very low SNR levels. Our algorithm can exploit
either the Azimuth AoA to generate the secret key or both the Azimuth and
Elevation angles to generate the secret key. Exploiting a second common source
of randomness adds an extra degree of freedom to the performance of our
algorithm. We compare the performance of our algorithm to the algorithm that
uses the most commonly used characteristics of the physical layer which are
channel amplitude and phase. We show that our algorithm has a very low bit
mismatch rate (BMR) at very low SNR when both channel amplitude and phase based
algorithm fail to achieve an acceptable BMR
Structural health monitoring of wind turbine blades: acoustic source localization using wireless sensor networks
Structural health monitoring (SHM) is important for reducing the maintenance and operation cost of safety-critical components and systems in offshore wind turbines. This paper proposes an in situ wireless SHM system based on an acoustic emission (AE) technique. By using this technique a number of challenges are introduced due to high sampling rate requirements, limitations in the communication bandwidth, memory space, and power resources. To overcome these challenges, this paper focused on two elements: (1) the use of an in situ wireless SHM technique in conjunction with the utilization of low sampling rates; (2) localization of acoustic sources which could emulate impact damage or audible cracks caused by different objects, such as tools, bird strikes, or strong hail, all of which represent abrupt AE events and could affect the structural health of a monitored wind turbine blade. The localization process is performed using features extracted from aliased AE signals based on a developed constraint localization model. To validate the performance of these elements, the proposed system was tested by testing the localization of the emulated AE sources acquired in the field
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