{"ID":5935656,"CreatedAt":"2026-07-07T01:22:02.77346169Z","UpdatedAt":"2026-07-07T02:10:06.972658124Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.03499","arxiv_id":"2607.03499","title":"Scale-Free Beamforming using Swarm Arrays for Remote Sensing under Interference","abstract":"We consider a swarm array of autonomous relays that seek to cooperatively forward a desired signal to a fusion center with the maximum possible fidelity while canceling out a number of interferers. We present a distributed algorithm for computing the optimal zero-forcing beamforming weights at the relays without requiring prior channel knowledge. Crucially, our algorithm is {\\it scale-free} in the sense that the computational and bandwidth overheads are completely independent of the size of the array. We build on recent work that introduced the concept of a Collective Array that enables such {\\it scale-free} computation by imposing a constraint that the array must always function as a {\\it swarm} i.e. array elements can only ever communicate with external nodes collectively and never individually. While this is a very severe restriction, we show that it allows useful computations such as zero-forcing beamforming while being robust to noise and channel time-variations.","short_abstract":"We consider a swarm array of autonomous relays that seek to cooperatively forward a desired signal to a fusion center with the maximum possible fidelity while canceling out a number of interferers. We present a distributed algorithm for computing the optimal zero-forcing beamforming weights at the relays without requir...","url_abs":"https://arxiv.org/abs/2607.03499","url_pdf":"https://arxiv.org/pdf/2607.03499v1","authors":"[\"Bradley Hamilton\",\"Raghu Mudumbai\",\"Soura Dasgupta\",\"Benjamin Peiffer\"]","published":"2026-07-03T17:12:53Z","proceeding":"cs.DC","tasks":"[\"cs.DC\",\"cs.IT\",\"eess.SP\"]","methods":"[]","has_code":false}