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Record W2045761076 · doi:10.1109/glocom.2006.822

WLC35-6: Relay-Assisted Spatial Multiplexing in Wireless Fixed Relay Networks

2006· article· en· W2045761076 on OpenAlex

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.

Bibliographic record

VenueGlobecom · 2006
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsCarleton University
Fundersnot available
KeywordsRelaySpatial multiplexingComputer scienceMIMOMultiplexingComputer networkWirelessAntenna diversityDiversity gainDecoding methodsElectronic engineeringTelecommunicationsPower (physics)Channel (broadcasting)Engineering

Abstract

fetched live from OpenAlex

Fixed relays are expected to be a part of future infrastructure-based wireless networks. Besides coverage extension, such relays can form advanced architectures due to the flexibility in their power expenditure and physical size. This paper explores the potential benefits of multi-antenna relays for spatial multiplexing of independent data sources sending data to a common multi-antenna destination such as a base station or an access point. Overall, the system resembles a horizontally coded layered space-time architecture. In particular, we consider zero forcing decision feedback (ZF-DF) type MIMO receivers and study their outage performance under various (non-selective and selective) digital relaying protocols. For diversity relaying protocol, we propose two schemes, Joint ZF-DF and Parallel ZF-DF, for joint processing (combining and decoding) of the direct user signals and the signal from the relay. We show that with the proposed selective diversity relaying protocols and joint ZF-DF processing, the outage probability of the system can be decreased significantly.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.877
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.019
GPT teacher head0.246
Teacher spread0.227 · 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