Sparse Combinatorial Group Testing
Abstract
In combinatorial group testing (CGT), the objective is to identify the set of at most d defective items from a pool of n items using as few tests as possible. The celebrated result for the CGT problem is that the number of tests t can be made logarithmic in n when d=O(poly( n)). However, state-of-the-art GT codes require the items to be tested w=(d n) times and tests to include =(n/d) 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 w or the number of items each test can include by in both noiseless and noisy settings. These constraints lead to an unexplored regime where t is a fractional power of n. Our results characterize the number of tests t as a function of w () and show, for example, that t decreases drastically when w is increased beyond a bare minimum. In particular, if w≤ d, then we must have t=n, i.e., individual testing is optimal. We show that if w=d+1, this decreases suddenly to t=(dn). 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 w=ld+1 for l>1, the modified K-S construction requires t=(d n1l+1) 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.
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