2,616 research outputs found
Robust vector quantization for noisy channels
The paper briefly discusses techniques for making vector quantizers more tolerant to tranmsission errors. Two algorithms are presented for obtaining an efficient binary word assignment to the vector quantizer codewords without increasing the transmission rate. It is shown that about 4.5 dB gain over random assignment can be achieved with these algorithms. It is also proposed to reduce the effects of error propagation in vector-predictive quantizers by appropriately constraining the response of the predictive loop. The constrained system is shown to have about 4 dB of SNR gain over an unconstrained system in a noisy channel, with a small loss of clean-channel performance
Power Allocation for Distributed BLUE Estimation with Full and Limited Feedback of CSI
This paper investigates the problem of adaptive power allocation for
distributed best linear unbiased estimation (BLUE) of a random parameter at the
fusion center (FC) of a wireless sensor network (WSN). An optimal
power-allocation scheme is proposed that minimizes the -norm of the vector
of local transmit powers, given a maximum variance for the BLUE estimator. This
scheme results in the increased lifetime of the WSN compared to similar
approaches that are based on the minimization of the sum of the local transmit
powers. The limitation of the proposed optimal power-allocation scheme is that
it requires the feedback of the instantaneous channel state information (CSI)
from the FC to local sensors, which is not practical in most applications of
large-scale WSNs. In this paper, a limited-feedback strategy is proposed that
eliminates this requirement by designing an optimal codebook for the FC using
the generalized Lloyd algorithm with modified distortion metrics. Each sensor
amplifies its analog noisy observation using a quantized version of its optimal
amplification gain, which is received by the FC and used to estimate the
unknown parameter.Comment: 6 pages, 3 figures, to appear at the IEEE Military Communications
Conference (MILCOM) 201
Optimal block cosine transform image coding for noisy channels
The two dimensional block transform coding scheme based on the discrete cosine transform was studied extensively for image coding applications. While this scheme has proven to be efficient in the absence of channel errors, its performance degrades rapidly over noisy channels. A method is presented for the joint source channel coding optimization of a scheme based on the 2-D block cosine transform when the output of the encoder is to be transmitted via a memoryless design of the quantizers used for encoding the transform coefficients. This algorithm produces a set of locally optimum quantizers and the corresponding binary code assignment for the assumed transform coefficient statistics. To determine the optimum bit assignment among the transform coefficients, an algorithm was used based on the steepest descent method, which under certain convexity conditions on the performance of the channel optimized quantizers, yields the optimal bit allocation. Comprehensive simulation results for the performance of this locally optimum system over noisy channels were obtained and appropriate comparisons against a reference system designed for no channel error were rendered
Network Code Design for Orthogonal Two-hop Network with Broadcasting Relay: A Joint Source-Channel-Network Coding Approach
This paper addresses network code design for robust transmission of sources
over an orthogonal two-hop wireless network with a broadcasting relay. The
network consists of multiple sources and destinations in which each
destination, benefiting the relay signal, intends to decode a subset of the
sources. Two special instances of this network are orthogonal broadcast relay
channel and the orthogonal multiple access relay channel. The focus is on
complexity constrained scenarios, e.g., for wireless sensor networks, where
channel coding is practically imperfect. Taking a source-channel and network
coding approach, we design the network code (mapping) at the relay such that
the average reconstruction distortion at the destinations is minimized. To this
end, by decomposing the distortion into its components, an efficient design
algorithm is proposed. The resulting network code is nonlinear and
substantially outperforms the best performing linear network code. A motivating
formulation of a family of structured nonlinear network codes is also
presented. Numerical results and comparison with linear network coding at the
relay and the corresponding distortion-power bound demonstrate the
effectiveness of the proposed schemes and a promising research direction.Comment: 27 pages, 9 figures, Submited to IEEE Transaction on Communicatio
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