991 research outputs found
Distributed Detection over Fading MACs with Multiple Antennas at the Fusion Center
A distributed detection problem over fading Gaussian multiple-access channels
is considered. Sensors observe a phenomenon and transmit their observations to
a fusion center using the amplify and forward scheme. The fusion center has
multiple antennas with different channel models considered between the sensors
and the fusion center, and different cases of channel state information are
assumed at the sensors. The performance is evaluated in terms of the error
exponent for each of these cases, where the effect of multiple antennas at the
fusion center is studied. It is shown that for zero-mean channels between the
sensors and the fusion center when there is no channel information at the
sensors, arbitrarily large gains in the error exponent can be obtained with
sufficient increase in the number of antennas at the fusion center. In stark
contrast, when there is channel information at the sensors, the gain in error
exponent due to having multiple antennas at the fusion center is shown to be no
more than a factor of (8/pi) for Rayleigh fading channels between the sensors
and the fusion center, independent of the number of antennas at the fusion
center, or correlation among noise samples across sensors. Scaling laws for
such gains are also provided when both sensors and antennas are increased
simultaneously. Simple practical schemes and a numerical method using
semidefinite relaxation techniques are presented that utilize the limited
possible gains available. Simulations are used to establish the accuracy of the
results.Comment: 21 pages, 9 figures, submitted to the IEEE Transactions on Signal
Processin
On the DMT of TDD-SIMO Systems with Channel-Dependent Reverse Channel Training
This paper investigates the Diversity-Multiplexing gain Trade-off (DMT) of a
training based reciprocal Single Input Multiple Output (SIMO) system, with (i)
perfect Channel State Information (CSI) at the Receiver (CSIR) and noisy CSI at
the Transmitter (CSIT), and (ii) noisy CSIR and noisy CSIT. In both the cases,
the CSIT is acquired through Reverse Channel Training (RCT), i.e., by sending a
training sequence from the receiver to the transmitter. A channel-dependent
fixed-power training scheme is proposed for acquiring CSIT, along with a
forward-link data transmit power control scheme. With perfect CSIR, the
proposed scheme is shown to achieve a diversity order that is quadratically
increasing with the number of receive antennas. This is in contrast with
conventional orthogonal RCT schemes, where the diversity order is known to
saturate as the number of receive antennas is increased, for a given channel
coherence time. Moreover, the proposed scheme can achieve a larger DMT compared
to the orthogonal training scheme. With noisy CSIR and noisy CSIT, a three-way
training scheme is proposed and its DMT performance is analyzed. It is shown
that nearly the same diversity order is achievable as in the perfect CSIR case.
The time-overhead in the training schemes is explicitly accounted for in this
work, and the results show that the proposed channel-dependent RCT and data
power control schemes offer a significant improvement in terms of the DMT,
compared to channel-agnostic orthogonal RCT schemes. The outage performance of
the proposed scheme is illustrated through Monte-Carlo simulations.Comment: Accepted for publication in IEEE Transactions on Communication
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