Rate-splitting multiple access (RSMA) is a promising technique for massive MIMO systems, while hybrid precoding provides an effective means to balance transmission performance and energy consumption. However, existing studies mainly focus on fully-connected architectures, while hybrid precoding design for massive MIMO-RSMA systems with energy-efficient partially-connected architecture remains unexplored in the literature. To fill in this research gap, we propose an adaptive cross-entropy (ACE)-based hybrid precoding scheme. The analog precoder is designed using a probabilistic search over discrete phases, iteratively sampling and updating selection probabilities. Then, the weighted minimum mean-squared error (WMMSE) algorithm is employed to jointly optimize the digital precoder and the common rate allocation. Simulation results demonstrate that the proposed scheme maintains competitive MMF performance while achieving superior energy efficiency.
This paper presents a low-complexity precoded MIMO-OFDM system for achieving improved spectral efficiency (SE) via intentionally compressing information symbols among subcarriers. Particularly, the proposed scheme leverages the powerful random multiplexing mechanism for precoding, and adopts the linear-complexity orthogonal approximate message passing (OAMP) estimator for symbol detection, where the compatibility with the existing fifth generation (5G) architectures is fully preserved. We further provide the theoretical analysis based on the replica-symmetric (RS) formula. This analysis confirms the advantages of the proposed system with respect to the adopted compression ratios, where an interesting phase transition behavior is verified. Numerical results coincide with our analysis and demonstrate significant improvements in terms of achievable rates and bit error rate (BER) compared to conventional MIMO-OFDM counterpart, making the proposed scheme a promising solution to 6G and beyond wireless networks.
Current wireless systems combat inter-symbol interference (ISI) by diagonalizing or sparsifying the channel matrix, yet they remain vulnerable to selective fading. To address this, we propose a universal random precoding (RP) transmission framework based on the universality class. RP leverages random transforms to statistically exploit all subchannels and construct an equivalent channel belonging to the universality class, thereby enhancing diversity gain while maintaining backward compatibility with existing waveforms. Low-complexity implementations include the randomly permuted fast transform (FT-RP) and the interleaved block-sparse fast transform (IBSFT-RP). A cross-domain OAMP/MAMP (CD-OAMP/MAMP) detector is designed for RP systems, which is replica maximum \textit{a posteriori} (MAP)-optimal according to state evolution (SE). Simulation results on MIMO systems demonstrate that RP with CD-OAMP/MAMP achieves near-RM performance with much lower complexity, with additional benefits of flexible compression ratios for spectral efficiency.
Jiazhen Dong, Lei Liu, Xiaojun Yuan et al.· 0 citations
Massive Multiple-Input Multiple-Output (MIMO) is a key enabling technology for fifth-generation (5G) and beyond wireless communication systems because of its ability to greatly enhance both spectral efficiency (SE) and energy efficiency (EE). However, maximizing these two performance metrics simultaneously remains a challenging multi-objective optimization problem due to the conflicting effects of the transmit power, antenna deployment, and circuit power consumption. This paper investigates the EE–SE trade-off in a downlink Massive MIMO system with Minimum Mean Square Error (MMSE) channel estimation (CE) and different linear combining and precoding techniques. A power optimization framework based on transmit power allocation and antenna configuration is analyzed to identify operating points that maximize EE while maintaining high SE. Performance analysis of the number of base station (BS) antennas in MIMO systems, user equipment density, transmit power, and inter-cell interference on system performance is evaluated through numerical simulations. The results demonstrate that appropriately selecting the number of transmit antennas and optimizing the transmit power significantly improve the EE–SE trade-off. Furthermore, although increasing the number of antennas enhances SE, EE exhibits a non-monotonic behavior because of the additional circuit power required by the radio-frequency hardware. The findings confirm that MMSE-based CE provides higher spectral efficiency than the MR, ZF, RZF, and S-MMSE schemes, albeit at increased computational complexity, offering useful design guidelines for energy-efficient Massive MIMO networks.
Unknown authors· Journal of Low Power Electro...· 0 citations
This letter proposes a new beamforming technique, Adaptive Regularized OLP (AR-OLP), by jointly optimizing transmit beamforming and IRS phase shifts to enhance spectral efficiency in downlink wireless communications. We provide a comparative analysis of AR-OLP with two key precoding algorithms: Optimal Linear Precoding (OLP) and Regularized Zero-forcing (RZF) to evaluate their performance under varying network parameters, including the number of transmit antennas, users, and IRS passive elements. Simulation results demonstrate that the proposed AR-OLP algorithm consistently achieves higher average sum rates per user compared to conventional OLP and RZF methods. The performance gains grow with increasing antenna count and IRS size, showing robust interference management and effective resource utilization across different transmit powers. These findings highlight the potential of adaptive hybrid precoding in IRS-aided MISO multiuser systems for next-generation wireless networks.
A unified comparative analysis of three widely used spatially correlated centralized scattering channel models in a multi-cell massive MIMO system suggests that M-MMSE is preferable in strongly correlated environments, while lower-complexity schemes such as RZF provide a favorable trade-off in scenarios with milder spatial correlation.
Waleed A. Ali, M. M. Zayed· Wireless networks· 0 citations
An autoencoder-based solution to compress CSI at the UE side and reconstruct it at BS and outperforms the conventional CSI feedback scheme by approximately 21% in terms of throughput is proposed.
A. F. Chabi, João Vitor, D. S. Campos et al.· 0 citations
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