2026· passer of basic and applied sciences· 0 citations· 22 references
TL;DR
The results demonstrated that integrating C-NOMA with caching and m-MIMO leads to better performance in sum rate, latency reduction, and throughput for different file sizes, different networks traffic, different users and stations numbers and different power allocation levels.
Abstract
The demand for data and the spectrum utilization together with interference issues and energy use requirements and sustainability objectives and reduced latency needs have become the main driving forces behind developing 6G mobile networks. High-definition videos along with augmented reality and virtual reality and connected devices in the Internet of Things (IoT) are main factors behind the network growth. This research aims to examine the strategic combination of C-NOMA cooperative access and massive MIMO antennas with caching data entities to boost the operational qualities of these networks. The combined system seeks to manage escalating data volumes better. This research proposed a combination of C-NOMA with massive MIMO along with caching functions to boost 6G network operations in dynamic form. NYSIM along with MATLAB simulations are used to evaluate the performance of this system against different setups that implement massive MIMO technology in 6G communication networks. The results demonstrated that integrating C-NOMA with caching and m-MIMO leads to better performance in sum rate, latency reduction, and throughput for different file sizes, different networks traffic, different users and stations numbers and different power allocation levels. The results also show improvement gained in sum rate, throughput, latency reduction when compared with other recent studies too. Finally, integration results lead to higher-level performance improvement in the 6G mobile networks.
The review finds that Massive MIMO improves spectrum efficiency, system capacity, and link reliability through large antenna arrays, beamforming, and spatial multiplexing, while NOMA increases access density and edge-user fairness through power-domain multiplexing and successive interference cancellation.
Yijiao Liu· Applied and Computational En...· 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
The development of 6G wireless networks will meet a multitude of communication requirements including ultra-high data rates, extensive connectivity, low latency and intelligent network management. For these goals, the use of advanced technologies to improve spectrum utilization, computing efficiency and network scalability will be required. The current review covers three technologies that are expected to be prevalent in the future of 6G networks: intelligent multiple access, edge intelligence and advanced antenna systems. In this paper, we cover advancements in intelligent multiple access technologies to enhance spectrum efficiency and user connectivity, and the role played by edge intelligence in developing distributed artificial intelligence, real-time decision making, and latency-aware resource management. Moreover, we review advanced antenna technologies - massive Multiple Input Multiple Output (MIMO), cell-free architectures and reconfigurable intelligent surfaces - and discuss their potential to enhance coverage, capacity and energy efficiency. In addition, we also compare recent work and discuss some of the research gaps in the field and the future research directions in smart and sustainable 6G communication technologies. The findings illustrated that the integration of intelligent multiple access technologies, edge intelligence and advanced antenna technologies would be critical for reliable and scalable wireless networks that would be able to support next generation applications such as extended reality, autonomous systems and large-scale IoT systems.
Mustafa Mohammed Jasim, Firas Mohammed Adress, A. Fadhil· Central Asian Journal of The...· 0 citations
Numerical simulations demonstrate that proactive caching based on clustered-BSVM outperforms existing methods in terms of CHR and USR, while the branch-and-bound method effectively resolves the content delivery problem, minimizing system latency.
Ayaz Ahmad, Fawad Ahmad, Muhammad Suleman Khan et al.· PeerJ Computer Science· 0 citations
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