54 research outputs found
Simplified Multiuser Detection for SCMA with Sum-Product Algorithm
Sparse code multiple access (SCMA) is a novel non-orthogonal multiple access
technique, which fully exploits the shaping gain of multi-dimensional
codewords. However, the lack of simplified multiuser detection algorithm
prevents further implementation due to the inherently high computation
complexity. In this paper, general SCMA detector algorithms based on
Sum-product algorithm are elaborated. Then two improved algorithms are
proposed, which simplify the detection structure and curtail exponent
operations quantitatively in logarithm domain. Furthermore, to analyze these
detection algorithms fairly, we derive theoretical expression of the average
mutual information (AMI) of SCMA (SCMA-AMI), and employ a statistical method to
calculate SCMA-AMI based specific detection algorithm. Simulation results show
that the performance is almost as well as the based message passing algorithm
in terms of both BER and AMI while the complexity is significantly decreased,
compared to the traditional Max-Log approximation method
Non-adaptive pooling strategies for detection of rare faulty items
We study non-adaptive pooling strategies for detection of rare faulty items.
Given a binary sparse N-dimensional signal x, how to construct a sparse binary
MxN pooling matrix F such that the signal can be reconstructed from the
smallest possible number M of measurements y=Fx? We show that a very low number
of measurements is possible for random spatially coupled design of pools F. Our
design might find application in genetic screening or compressed genotyping. We
show that our results are robust with respect to the uncertainty in the matrix
F when some elements are mistaken.Comment: 5 page
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