495 research outputs found
Distributed Detection over Gaussian Multiple Access Channels with Constant Modulus Signaling
A distributed detection scheme where the sensors transmit with constant
modulus signals over a Gaussian multiple access channel is considered. The
deflection coefficient of the proposed scheme is shown to depend on the
characteristic function of the sensing noise and the error exponent for the
system is derived using large deviation theory. Optimization of the deflection
coefficient and error exponent are considered with respect to a transmission
phase parameter for a variety of sensing noise distributions including
impulsive ones. The proposed scheme is also favorably compared with existing
amplify-and-forward and detect-and-forward schemes. The effect of fading is
shown to be detrimental to the detection performance through a reduction in the
deflection coefficient depending on the fading statistics. Simulations
corroborate that the deflection coefficient and error exponent can be
effectively used to optimize the error probability for a wide variety of
sensing noise distributions.Comment: 30 pages, 12 figure
Type-Based Random Access for Distributed Detection Over Multiaccess Fading Channels
The problem of distributed detection in a sensor network over multiaccess fading channels is considered. A random-access transmission scheme referred to as the type-based random access (TBRA) is proposed and analyzed. Error exponents of TBRA under noncoherent detection are characterized with respect to the mean transmission rate and the channel-coherence index. For the zero-mean multiaccess fading channels, it is shown that there exists an optimal mean-transmission rate that maximizes the detection-error exponents. The optimal mean-transmission rate can be calculated numerically or estimated using the Gaussian approximation, and it gives a sensor-activation strategy that achieves an optimal allocation of transmission energy to spatial and temporal domains. Numerical examples and simulations are used to compare TBRA with the conventional centralized time-division multiple access (TDMA) scheme. It is shown that for the zero-mean multiaccess fading channels, TBRA gives substantial improvement in the low signal-to-noise ratio (SNR) regime whereas for the nonzero mean fading channels, TBRA performs better over a wide range of SNR
A Large Deviation Analysis of Detection Over Multi-Access Channels with Random Number of Sensors
We consider the problem of distributed detection over a multi-access channel. Assuming a random number of sensors transmitting their observations using type based multiple access, we derive the detection performance using large deviations principle as the mean number of sensors goes to infinity. We characterize the performance in terms of error exponents. We provide comparison with the case when the number of sensors is deterministic. We generalize this scheme to multiple collections, propose a minimum sum-rate detector and characterize its error exponents
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