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Hybrid Block Diagonalization for Massive Multiuser MIMO Systems

2015· article· en· 382 citations· W1423052447 on OpenAlex· 10.1109/tcomm.2015.2502954

Why is this work in the frame?

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

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

Full frame distilled prediction

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.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Simulation or modelingConsensus signal: Simulation or modeling
Genre
Candidate signal: MethodsConsensus signal: none
Teacher disagreement score
0.974
Threshold uncertainty score
0.875
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

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

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.

Opus teacher head0.044
GPT teacher head0.274
Teacher spread
0.230 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

For a massive multiple-input multiple-output (MIMO) system, restricting the number of RF chains to far less than the number of antenna elements can significantly reduce the implementation cost compared to the full complexity RF chain configuration. In this paper, we consider the downlink communication of a massive multiuser MIMO (MU-MIMO) system and propose a low-complexity hybrid block diagonalization (Hy-BD) scheme to approach the capacity performance of the traditional BD processing method. We aim to harvest the large array gain through the phase-only RF precoding and combining and then digital BD processing is performed on the equivalent baseband channel. The proposed Hy-BD scheme is examined in both the large Rayleigh fading channels and millimeter wave (mmWave) channels. A performance analysis is further conducted for single-path channels and large number of transmit and receive antennas. Finally, simulation results demonstrate that our Hy-BD scheme, with a lower implementation and computational complexity, achieves a capacity performance that is close to (sometimes even higher than) that of the traditional high-dimensional BD processing.

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.

The record

Venue
IEEE Transactions on Communications
Topic
Advanced MIMO Systems Optimization
Field
Engineering
Canadian institutions
University of Victoria
Funders
Natural Sciences and Engineering Research Council of Canada
Keywords
PrecodingMIMOBasebandElectronic engineeringTelecommunications linkRayleigh fadingComputer scienceBlock (permutation group theory)Antenna (radio)FadingChannel (broadcasting)Multi-user MIMOTelecommunicationsEngineeringMathematicsBandwidth (computing)
Has abstract in OpenAlex
yes