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Nulling Steering Beamforming for Tx-Rx Isolation Optimization in Full-Duplex mMIMO

2024· article· en· W4408324766 on OpenAlex
Yuanzhe Gong, Tho Le‐Ngoc

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaHuawei Technologies
KeywordsBeamformingIsolation (microbiology)Computer scienceDuplex (building)Electronic engineeringEngineeringChemistryBiologyBioinformatics

Abstract

fetched live from OpenAlex

This paper proposes a nulling steering beamforming-based isolation optimization scheme to mitigate the Tx-Rx self-interference in full-duplex massive MIMO systems. By searching the optimal nulling angles in both the uplink and the downlink beamforming process, the simulation and experimental measurements demonstrate a considerable beam-level isolation improvement while maintaining the integrity of the original beamforming performance. Illustrative results with a 20 MHz modulated signal and the 8×8Tx/8×8Rx full-duplex array prototype in the anechoic chamber show an average Tx-Rx isolation improvement of 10.2 dB, resulting in an average Tx-Rx mutual coupling level of -75.7 dB. Within the 25 measured Tx/Rx beam pairs, the most substantial isolation improvement of 22.2 dB can be observed and the best beam-level isolation of 92.7 dB can be achieved.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.655
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.242
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations3
Published2024
Admission routes2
Has abstractyes

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