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Performance Analysis of LTE Systems with Artificial Intelligence-Assisted Interpretation Cover

Performance Analysis of LTE Systems with Artificial Intelligence-Assisted Interpretation

Open Access
|Jun 2026

Figures & Tables

Figure no. 1:

Three-layer MVC-inspired architecture of the proposed LTE simulalion platform. Solid arrows indicate primary data flow between layers (Source: Author’s own conception)

Figure no. 2:

Three-stage computation pipeline of the LTE simulation engine (Source: Author’s own conception)

Figure no. 3:

Two-stage AI interpretation and validation pipeline: Stage 4 generates a structured academic report via Claude Sonnet 4; Stage 5 independently verifies all eight IEEE metrics against NumPy-computed reference values (Source: Author’s own conception)

Figure no.4:

Simulated BLER vs. SNR (up) and spectral efficiency vs. SNR (down) for the MIMO 2×2, 16-QAM, EVA reference configuration. Dashed horizontal line at BLER = 10% indicates the 3GPP operational threshold. Dashed blue curve represents the Shannon capacity bound (Source: LTE Simulator)

Figure no. 5:

BLER vs. SNR comparison for SISO, SIMO 1×2, MISO 2×1, and MIMO 2×2 under fixed 16-QAM, EVA, 70 Hz Doppler conditions (Source: LTE Simulator)

Figure no. 6:

Spectral efficiency vs. SNR for the four antenna configurations. MISO and MIMO 2×2 achieve 8.0 bps/Hz peak through simultaneous two-stream spatial multiplexing (Source: LTE Simulator)

Figure no. 7:

Independent validation dashboard for the MIMO 2×2, 16-QAM, EVA reference configuration, showing per-metric VALID/INVALID status, absolute deviations, and overall accuracy score (Source: LTE Simulator)

Figure no. 8:

Side-by-side comparison of independently computed metric values (left column) versus AI-reported values extracted via regular expression pattern matching (right column), for the SNR @ 10% BLER metric (Source: LTE Simulator)

AI validation results for MIMO 2x2, 16-QAM, EVA reference configuration

MetricAI ReportedNumPy ComputedDeviationStatus
SNR @ 10% BLER8.04 dB8.0442 dB0.05%VALID
SNR @ 1% BLER12.00 dB12.00 dB0.00%VALID
Peak Throughput7.9999 bps/Hz7.9999 bps/Hz0.00%VALID
Mean Throughput4.55 bps/Hz4.5485 bps/Hz0.00%VALID
Knee SNR5.94 dB5.94 dB0.02%VALID
Good SNR Min8.04 dB12.00 dB33.0%INVALID
Peak SNR14.00 dB14.00 dB0.00%VALID
Shannon Efficiency60.08%60.08%<0.01%VALID

Experimental scenario parameters

ParameterScenario IScenario IIScenario III
Variable factorMIMO mode (SISO → MIMO 2×2)Channel model (EPA / EVA / ETU)Modulation scheme (QPSK / 16-QAM / 64-QAM)
MIMO modeSISO · SIMO 1×2 · MISO 2×1 · MIMO 2×2MIMO 2×2 (fixed)MIMO 2×2 (fixed)
Modulation16-QAM (fixed)16-QAM (fixed)QPSK · 16-QAM · 64-QAM
Channel codingTurbo (fixed)Turbo (EPA, EVA) · LDPC (ETU)Turbo (fixed)
Channel modelEVA (fixed)EPA · EVA · ETUEVA (fixed)
Doppler frequency70 Hz (fixed)5 Hz · 70 Hz · 300 Hz70 Hz (fixed)
HARQ retransmissions0 (fixed)1 (EPA) · 0 (EVA, ETU)0 (fixed)
Antenna correlation ρ0.3 (fixed)0.3 (fixed)0.3 (fixed)
CSI feedback delay1.0 ms (fixed)1.0 ms (fixed)1.0 ms (fixed)
SNR range−5 → 25 dB−5→25 / −10→20 / 0→30 dB−5 → 25 dB
SNR step2 dB2 dB2 dB
Standard3GPP TS 36.104 (3GPP, 2016)3GPP TS 36.104 (3GPP, 2016)3GPP TS 36.104 (3GPP, 2016)
DOI: https://doi.org/10.2478/bsaft-2026-0006 | Journal eISSN: 3100-5098 | Journal ISSN: 3100-508X
Language: English
Page range: 75 - 86
Submitted on: Mar 23, 2026
Accepted on: May 4, 2026
Published on: Jun 24, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2026 Anisia-Teodora FUGARU, Mădălina CURTA, Anamaria SÂRBU, published by Nicolae Balcescu Land Forces Academy
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.