Order-optimal Joint Transmission and Identification in Massive Multi-User MIMO via Group Testing
George Vershinin, Asaf Cohen, Omer Gurewitz

TL;DR
This paper introduces an order-optimal massive MU-MIMO scheme leveraging group testing principles to identify and decode active devices simultaneously without prior scheduling, significantly reducing overhead.
Contribution
It proposes a novel joint transmission and identification scheme using sparse coding and group testing, requiring minimal channel knowledge and achieving order-optimal performance.
Findings
Achieves simultaneous device identification and decoding without scheduling.
Requires O(K log N M) antennas, matching theoretical lower bounds.
Provides both sufficient conditions and converse bounds for minimal antennas.
Abstract
The number of wireless devices which are connected to a single Wireless Local Area Network continues to grow each year. As a result, the orchestration of so many devices becomes a daunting, resource--consuming task, especially when the resources available at the single access point are limited, and it is hard to anticipate which devices will request access at any given time. On the other hand, the number of antennas on both the devices and the access point grows as well, facilitating advanced joint scheduling and coding techniques. In this paper, we leverage the large number of antennas and suggest a massive multiple-user multiple-input-multiple-output (MU-MIMO) scheme using sparse coding based on Group Testing (GT) principles. The scheme allows for a small subset of devices to transmit simultaneously, without a preceding scheduling phase or coordination, thus reducing overhead and…
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Taxonomy
TopicsSARS-CoV-2 detection and testing · Advanced biosensing and bioanalysis techniques · Transplantation: Methods and Outcomes
