Joint Jammer Mitigation and Data Detection for Smart, Distributed, and Multi-Antenna Jammers


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Date

2023-10-23

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

Multi-antenna (MIMO) processing is a promising solution to the problem of jammer mitigation. Existing methods mitigate the jammer based on an estimate of its subspace (or receive statistics) acquired through a dedicated training phase. This strategy has two main drawbacks: (i) it reduces the communication rate since no data can be transmitted during the training phase and (ii) it can be evaded by smart or multi-antenna jammers that are quiet during the training phase or that dynamically change their subspace through time-varying beamforming. To address these drawbacks, we propose Joint jammer Mitigation and data Detection (JMD), a novel paradigm for MIMO jammer mitigation. The core idea is to estimate and remove the jammer interference subspace jointly with detecting the transmit data over multiple time slots. Doing so removes the need for a dedicated and rate-reducing training period while mitigating smart and dynamic multi-antenna jammers. We instantiate our paradigm with SANDMAN, a simple and practical algorithm for multi-user MIMO uplink JMD. Extensive simulations demonstrate the efficacy of JMD, and of SANDMAN in particular, for jammer mitigation.

Publication status

published

Editor

Book title

ICC 2023 - IEEE International Conference on Communications

Journal / series

Volume

Pages / Article No.

1364 - 1369

Publisher

IEEE

Event

IEEE International Conference on Communications (ICC 2023)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Training; Array signal processing; Simulation; Distributed databases; Receivers; Interference; Jamming

Organisational unit

09695 - Studer, Christoph / Studer, Christoph check_circle

Notes

Conference lecture held on May 29, 2023

Funding

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