Sparse Combinatorial Group Testing
Abstract
In combinatorial group testing (CGT), the objective is to identify the set of at most defective items from a pool of items using as few tests as possible. The celebrated result for the CGT problem is that the number of tests can be made logarithmic in when . However, state-of-the-art GT codes require the items to be tested times and tests to include items (within log factors). In many applications, items can only participate in a limited number of tests and tests are constrained to include a limited number of items. In this paper, we study the "sparse" regime for the group testing problem where we restrict the number of tests each item can participate in by or the number of items each test can include by in both noiseless and noisy settings. These constraints lead to an unexplored regime where is a fractional power of . Our results characterize the number of tests as a function of and show, for example, that decreases drastically when is increased beyond a bare minimum. In particular, if , then we must have , i.e., individual testing is optimal. We show that if , this decreases suddenly to . The order-optimal construction is obtained via a modification of the Kautz-Singleton construction, which is known to be suboptimal for the classical GT problem. For more general case, when for , the modified K-S construction requires tests, which we prove to be near order-optimal. We show that our constructions have a favorable encoding and decoding complexity. We finally discuss an application of our results to the construction of energy-limited random access schemes for IoT networks, which provided the initial motivation for our work.
Keywords
Cite
@article{arxiv.1711.05403,
title = {Sparse Combinatorial Group Testing},
author = {Huseyin A. Inan and Peter Kairouz and Ayfer Ozgur},
journal= {arXiv preprint arXiv:1711.05403},
year = {2019}
}