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Improved encoding and decoding for non-adaptive threshold group testing (1901.02283v1)

Published 8 Jan 2019 in cs.IT and math.IT

Abstract: The goal of threshold group testing is to identify up to $d$ defective items among a population of $n$ items, where $d$ is usually much smaller than $n$. A test is positive if it has at least $u$ defective items and negative otherwise. Our objective is to identify defective items in sublinear time the number of items, e.g., $\mathrm{poly}(d, \ln{n}),$ by using the number of tests as low as possible. In this paper, we reduce the number of tests to $O \left( h \times \frac{d2 \ln2{n}}{\mathsf{W}2(d \ln{n})} \right)$ and the decoding time to $O \left( \mathrm{dec}_0 \times h \right),$ where $\mathrm{dec}_0 = O \left( \frac{d{3.57} \ln{6.26}{n}}{\mathsf{W}{6.26}(d \ln{n})} \right) + O \left( \frac{d6 \ln4{n}}{\mathsf{W}4(d \ln{n})} \right)$, $h = O\left( \frac{d_02 \ln{\frac{n}{d_0}}}{(1-p)2} \right)$ , $d_0 = \max{u, d - u }$, $p \in [0, 1),$ and $\mathsf{W}(x) = \Theta \left( \ln{x} - \ln{\ln{x}} \right).$ If the number of tests is increased to $O\left( h \times \frac{d2\ln3{n}}{\mathsf{W}2(d \ln{n})} \right),$ the decoding complexity is reduced to $O \left(\mathrm{dec}_1 \times h \right),$ where $\mathrm{dec}_1 = \max \left{ \frac{d2 \ln3{n}}{\mathsf{W}2(d \ln{n})}, \frac{ud \ln4{n}}{\mathsf{W}3(d \ln{n})} \right}.$ Moreover, our proposed scheme is capable of handling errors in test outcomes.

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