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Record W2039501150 · doi:10.1049/iet-com.2013.1000

Performance analysis of relay‐multiplexing scheme in cellular systems employing massive multiple‐input multiple‐output antennas

2014· article· en· W2039501150 on OpenAlex
Assad Akhlaq, Ahmed Iyanda Sulyman, Hossam S. Hassanein, Abdulhameed Alsanie, Saleh A. Alshebeili

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

VenueIET Communications · 2014
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsQueen's University
FundersKing Saud University
KeywordsComputer scienceRelayMultiplexingScheme (mathematics)Electronic engineeringTelecommunicationsMathematicsPhysicsEngineering

Abstract

fetched live from OpenAlex

This study presents the symbol error probability (SEP) analysis of relay‐multiplexing scheme in relay‐assisted cellular systems such as the IEEE 802.16j and upcoming fifth generation (5G) systems. The availability of multiple relay paths in these systems motivates two relay configurations: (i) relay diversity and (ii) relay multiplexing. Available works in the literature have focused on the relay diversity methods. In this study, we explore the relay‐multiplexing alternative whereby relay stations (RSs) act as independent data pipes for transmitting multiple independent data streams from the base station (BS) to the mobile station (MS). We examine the case when the BS is equipped with massive multiple‐input multiple‐output (MIMO) antennas, transmitting independent data streams to several MS simultaneously via different relay paths. We derive analytical expressions for the SEP performance of the proposed scheme, and also complement the analysis with simulations. The results show that parallel relaying of independent data streams via different RSs has acceptable SEP performance while boosting the capacity of the system linearly with the number of parallel RSs available in the system. The results also show that when this relaying approach is combined with the emerging massive MIMO techniques, a tremendous boost in data rate 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0040.002
Research integrity0.0000.001
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 head0.063
GPT teacher head0.282
Teacher spread0.219 · 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