Interference-Calibrated Algebraically Projected Antenna Selection with Certified Graph Learning for Massive MIMO Under Realistic Multi-Cell Impairments
Antenna selection is investigated as a means of reducing radio-frequency (RF) chain power in massive multiple-input multiple-output (MIMO) base stations under realistic channel state information (CSI) impairments. The study is motivated by the mismatch between conventional selection objectives and multi-cell operation with estimation error, pilot contamination, spatial correlation and inter-cell interference. APCS-Boost-R is introduced as the primary contribution. An interference-whitened D-optimal seed is combined with projected rank-one exchanges and a calibrated surrogate that incorporates a user-side interference-plus-noise report and a closed-form estimation-error correction. APCS-Boost-RG is retained as an optional graph neural network (GNN) refinement in which residual exchanges are ranked after the algebraic solution has been formed, while feasibility and non-degradation of the calibrated surrogate are verified deterministically. In a three-cell urban macro configuration derived from Third Generation Partnership Project (3GPP) TR 38.901 with 64 antennas, 16 active RF chains and eight users per cell, APCS-Boost-R achieves 19.364 bit/s/Hz over 200 paired realizations. Improvements of 2.58 percent over APCS-Boost, 6.76 percent over greedy search and 10.16 percent over a genetic algorithm are obtained. APCS-Boost-RG adds 0.019 bit/s/Hz but is treated as an optional refinement because it requires a second-stage neighborhood evaluation and offline model maintenance. In the archived common timing record, APCS-Boost-R requires 20.376 ms per three-cell realization, compared with 12.728 ms for APCS-Boost, 57.775 ms for norm-initialized greedy search and 41.302 ms for the genetic algorithm, while APCS-Boost-RG requires 24.0 ms versus 20.4 ms for APCS-Boost-R in the separate archived learned-stage record. Separate reconstructions on the documented reproducibility host require 55.3±14.5 ms for APCS-Boost-R and 592.2±181.9 ms for a complete APCS-Boost-RG rebuild. Additional paired examinations confirm robustness across stronger search budgets, report imperfections, regularized precoding, coordination, near-field sensitivity, hardware perturbations, and configurations ranging from 32 to 128 antennas and one to seven cells.
A unified RIS-RSMA optimization framework for asynchronous downlink CF-MIMO and targeted comparisons using WMMSE and regularized zero-forcing private precoders, together with the common-power allocation results, support the need for joint common/private precoder design.
Ghadir Dogim, Ahmed E. El-Mahdy, Falko Dressler· IEEE Open Journal of the Com...· 0 citations
A time-evolving RCE model is developed that characterizes the joint effects of residual phase mismatches, residual carrier frequency offsets, and oscillator phase noise, and a Gauss--Legendre quadrature-based weighted minimum mean square error (WMMSE) optimization framework is developed.
Mingjun Sun, Xi-Dong Mu, Shaochuan Wu et al.· 0 citations
Digital Twin User pre-Screening (DiTUS), a digital-twin (DT)-aided framework that identifies promising users before instantaneous CSI acquisition, demonstrating that DT-based prescreening preserves substantial multiuser-diversity gains by identifying strong, spatially compatible users before acquiring effective-channel...
Namhyun Kim, Mahmoud Saad Abouamer, Jeonghun Park et al.· 0 citations
DEBKA is developed, a training-free optimizer that assigns different search roles to two complementary mechanisms: a BKA-inspired Cauchy-Gaussian attack for local refinement and adaptive DE/current-to-pbest migration for population-difference exploration, and results support the contribution of the coupled search and c...
Wen-Jian Zhang, Ping Li· Discover Internet of Things· 0 citations
Cell-free massive multiple-input multiple-output (CF-mMIMO) is a promising architecture for future wireless networks, yet its practical deployment is severely hindered by hardware impairments and time-varying channel conditions. To address these challenges, we investigate downlink transmission in a rate-splitting multi...
Le-Chen Li, Yao Zhang, Wenchao Xia et al.· 2026 IEEE/CIC International...· 0 citations
Cell-Free massive multiple-input multiple-output (CF-mMIMO) is a key technology for 6G networks, enabling efficient downlink beamforming by exploiting the channel reciprocity under time-division duplex (TDD) operation. However, mismatched radio-frequency (RF) gains in transceiver chains render the composite channel non...
Shi-Yuan Li, Shu Xu, Su-Ting Chen et al.· IEEE Transactions on Wireles...· 0 citations
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