Mimo Network(咪莫网络)研究综述
Mimo Network 咪莫网络 - In the case of Underwater IoT (UIoT) where the strength of electromagnetic waves rapidly falls off, the MIMO network can be effectively implemented by substitute of acoustic OFDM instead of the normal one. [1] For the MIMO network, our scheme achieves 80. [2] While prior work indicates that mMIMO networks employing time division duplexing have a significant capacity growth potential, deploying mMIMO in frequency division duplexing (FDD) networks remains problematic. [3] We address this problem in a two-hop, MIMO network, accounting for practical operational conditions in which the source is unaware of the symbols that the relay is transmitting. [4] The cellular mMIMO networks can provide high data rate for users, however their performance is not satisfied for the cell-edge users and shadowed users. [5] Finally, we propose a distributed link scheduling algorithm based on MSIC to eliminate the interference between competing links in the MIMO network. [6] The links between these two clusters results in V-MIMO network. [7] To fill this gap, in this paper we conduct a comparative analysis of several most viable advanced jamming schemes in the widely-used MIMO networks. [8] This method was applied to MIMO networks that operate over Rayleigh fading channels with different antenna nodes. [9] Multi-user (MU) MIMO network with transmit antennas $$T_x$$Tx at base station can schedule as many single antenna users in one time slot. [10] In this study, a CSI feedback scheme using random scalar quantization (RSQ) for MU-MIMO networks is proposed. [11] In this paper, we consider a massive MU-MIMO network and investigate the performance of phased-Zero-Forcing (PZF) precoding, to exploit the capacity performance of the conventional baseband Zero-Forcing scheme in downlink communication. [12] Such that MIMO networks give output exactly matching with the information sent by the transmitter. [13] However, in practice MU-MIMO networks are far from their full potential due to the poor scalability problem, including high computational complexity at PHY layer and large-overhead channel contention at MAC layer. [14] This paper aims at highlighting the different trade-offs affecting various performance metrics in CF-M-MIMO networks. [15] We propose a linear precoding scheme that relaxes such infeasibility in overloaded MU-MIMO networks. [16]在电磁波强度迅速下降的水下物联网（UIoT）的情况下，MIMO网络可以用声学OFDM代替普通的OFDM来有效地实现。 [1] 对于 MIMO 网络，我们的方案达到了 80。 [2] 虽然先前的工作表明采用时分双工的 mMIMO 网络具有显着的容量增长潜力，但在频分双工 (FDD) 网络中部署 mMIMO 仍然存在问题。 [3] 我们在两跳 MIMO 网络中解决了这个问题，考虑了源不知道中继正在传输的符号的实际操作条件。 [4] 蜂窝mMIMO网络可以为用户提供高数据速率，但其性能对于小区边缘用户和影子用户来说并不满意。 [5] 最后，我们提出了一种基于 MSIC 的分布式链路调度算法，以消除 MIMO 网络中竞争链路之间的干扰。 [6] 这两个集群之间的链接导致了 V-MIMO 网络。 [7] 为了填补这一空白，在本文中，我们对广泛使用的 MIMO 网络中几种最可行的高级干扰方案进行了比较分析。 [8] 该方法应用于在具有不同天线节点的瑞利衰落信道上运行的 MIMO 网络。 [9] 在基站具有发射天线$$T_x$$Tx 的多用户（MU）MIMO 网络可以在一个时隙中调度尽可能多的单天线用户。 [10] 在这项研究中，提出了一种针对 MU-MIMO 网络使用随机标量量化 (RSQ) 的 CSI 反馈方案。 [11] 在本文中，我们考虑了一个大规模的 MU-MIMO 网络，并研究了相位迫零 (PZF) 预编码的性能，以利用传统基带迫零方案在下行链路通信中的容量性能。 [12] 这样 MIMO 网络提供的输出与发射机发送的信息完全匹配。 [13] 然而，在实践中，由于可扩展性差的问题，包括 PHY 层的高计算复杂度和 MAC 层的大开销信道竞争，MU-MIMO 网络在实践中远未发挥其全部潜力。 [14] 本文旨在强调影响 CF-M-MIMO 网络中各种性能指标的不同权衡。 [15] 我们提出了一种线性预编码方案，可以缓解过载 MU-MIMO 网络中的这种不可行性。 [16]
cell free massive
In this paper, a resource allocation problem is studied for downlink cell-free massive MIMO networks, where each access point (AP) serves a cluster of user equipment (UE). [1] Our numerical results reveal that a cell-free massive MIMO architecture may provide better performance than a traditional multicell massive MIMO network deployment. [2] We present a modification of conjugate beamforming for the forward link of cell-free massive MIMO networks. [3] This paper focuses on the use of a deep learning approach to perform sum-rate-max and max-min power allocation in the uplink of a cell-free massive MIMO network. [4]在本文中，研究了下行链路无蜂窝大规模 MIMO 网络的资源分配问题，其中每个接入点 (AP) 服务于一组用户设备 (UE)。 [1] 我们的数值结果表明，无蜂窝大规模 MIMO 架构可以提供比传统多蜂窝大规模 MIMO 网络部署更好的性能。 [2] nan [3] nan [4]
Massive Mimo Network 庞大的 Mimo 网络
Cell-Free massive MIMO networks are recognized as possible solution in the future wireless communication. [1] This power control algorithm leads to scalable CF Massive MIMO networks in which the amount of computations conducted by each access point (AP) does not depend on the number of network APs. [2] In this paper, a SWIPT-enhanced cell-free massive MIMO network is proposed. [3] To promote energy conservation and improve utilization of system resources, we propose a joint antenna selection and power allocation (JASPA) strategy for CCFD massive MIMO networks. [4] In this paper, we design a deep learning framework for the power allocation problems in massive MIMO networks. [5] Useful insights into the optimal multi-beam multi-hop routing design are also drawn under different setups of the multi-IRS aided massive MIMO network. [6] A large-scale clustered massive MIMO network is proposed for improving the spectral efficiency of the next-generation wireless infrastructure by maximizing its sum-rate. [7] In a frequency division duplex (FDD) multiuser massive MIMO network, each user needs to compress and feedback its downlink CSI to the BS. [8] The major challenges in massive MIMO networks are to increase the system throughput and capacity with low complexity and reliability of the wireless communication system. [9] This study investigates the impact of channel correlation on a prototyped massive MIMO network with the objective to identify an antenna array geometry which has reduced mutual coupling and channel correlation. [10] The RIS is deployed to help conventional massive MIMO networks serve the users in the dead zone. [11] Although many precoding techniques are essentially proposed for a small-scale MIMO, they have been exploited in massive MIMO networks. [12] Cell-free massive multiple-input--multiple-output (MIMO) (CF-mMIMO) is a distributed massive MIMO network architecture, which leads to a better ability to resist shadow fading than centralized massive MIMO. [13] In this chapter, planning and performance evaluation for massive MIMO network has been conducted for rural areas in Tanzania. [14] We also provide design guidelines and requirements for massive MIMO network deployment and proper acceptance of Key Performance Indicators (KPIs) collection and comparisons criteria. [15] To alleviate the limitation of orthogonal resource and further enhance network capacity, non-orthogonal multiple access is applied to the CF massive MIMO network in both channel training and uplink transmission phases. [16] A good match to Terahertz communication is cell-free massive MIMO network architecture, where the antenna beams are located irregularly, coordination among base stations is required to improve the throughput. [17] We consider the uplink of a Massive MIMO network with $L$ cells, each comprising a BS with $M$ antennas and $K$ single-antenna user equipments. [18] The Massive MIMO network has a much potential to manage the speedy growth of cellular data traffic. [19] This work considers the uplink of a Massive MIMO network wherein the base stations (BSs) are randomly deployed according to a homogenous Poisson point process of intensity $\lambda$. [20] In this paper, we analyze the performance of the uplink (UL) of a massive MIMO network considering an asymptotically large number of antennas at base stations (BSs). [21] In this paper, a resource allocation problem is studied for downlink cell-free massive MIMO networks, where each access point (AP) serves a cluster of user equipment (UE). [22] Our numerical results reveal that a cell-free massive MIMO architecture may provide better performance than a traditional multicell massive MIMO network deployment. [23] The results demonstrate that ARDI is capable of accurately reconstructing full downlink channels when the signal-to-noise ratio is higher than 15dB, thereby expanding the channel capacity of Massive MIMO networks. [24] This paper considers a Massive MIMO network withCell-Free 大规模 MIMO 网络被认为是未来无线通信中可能的解决方案。 [1] 这种功率控制算法导致了可扩展的 CF Massive MIMO 网络，其中每个接入点 (AP) 执行的计算量不依赖于网络 AP 的数量。 [2] 在本文中，提出了一种 SWIPT 增强的无蜂窝大规模 MIMO 网络。 [3] 为了促进节能和提高系统资源的利用率，我们提出了一种用于 CCFD 大规模 MIMO 网络的联合天线选择和功率分配 (JASPA) 策略。 [4] 在本文中，我们为大规模 MIMO 网络中的功率分配问题设计了一个深度学习框架。 [5] 在多 IRS 辅助的大规模 MIMO 网络的不同设置下，还得出了对最佳多波束多跳路由设计的有用见解。 [6] 为了提高下一代无线基础设施的频谱效率，提出了一种大规模集群的大规模 MIMO 网络，通过最大化其和速率来提高其频谱效率。 [7] 在频分双工（FDD）多用户大规模MIMO网络中，每个用户都需要对其下行链路CSI进行压缩并反馈给BS。 [8] 大规模 MIMO 网络的主要挑战是提高系统吞吐量和容量，同时降低无线通信系统的复杂性和可靠性。 [9] 本研究调查了信道相关性对原型大规模 MIMO 网络的影响，目的是确定降低互耦合和信道相关性的天线阵列几何结构。 [10] RIS 的部署是为了帮助传统的大规模 MIMO 网络为死区的用户提供服务。 [11] 尽管许多预编码技术本质上是针对小规模 MIMO 提出的，但它们已在大规模 MIMO 网络中得到应用。 [12] 无单元大规模多输入多输出（MIMO）（CF-mMIMO）是一种分布式大规模MIMO网络架构，与集中式大规模MIMO相比，具有更好的抗阴影衰落能力。 [13] 在本章中，对坦桑尼亚农村地区的大规模 MIMO 网络进行了规划和性能评估。 [14] 我们还为大规模 MIMO 网络部署和正确接受关键性能指标 (KPI) 收集和比较标准提供设计指南和要求。 [15] 为了缓解正交资源的限制，进一步提高网络容量，非正交多址接入在信道训练和上行传输阶段都应用于CF大规模MIMO网络。 [16] 与太赫兹通信的一个很好的匹配是无蜂窝大规模 MIMO 网络架构，其中天线波束的位置不规则，需要基站之间的协调以提高吞吐量。 [17] 我们考虑具有 $L$ 个小区的 Massive MIMO 网络的上行链路，每个小区包括一个具有 $M$ 个天线和 $K$ 个单天线用户设备的 BS。 [18] 大规模 MIMO 网络在管理蜂窝数据流量的快速增长方面具有很大潜力。 [19] nan [20] nan [21] 在本文中，研究了下行链路无蜂窝大规模 MIMO 网络的资源分配问题，其中每个接入点 (AP) 服务于一组用户设备 (UE)。 [22] 我们的数值结果表明，无蜂窝大规模 MIMO 架构可以提供比传统多蜂窝大规模 MIMO 网络部署更好的性能。 [23] nan [24] nan [25] nan [26] nan [27] nan [28] 大规模 MIMO 网络部署预计将成为即将到来的 5G 通信系统的一个关键特征。 [29] nan [30] nan [31] nan [32] nan [33] nan [34] nan [35] nan [36] nan [37] nan [38] nan [39] nan [40] nan [41] nan [42] nan [43] nan [44] nan [45] nan [46] nan [47] nan [48] nan [49]
User Mimo Network
A multi-user MIMO network system with channel fading effect introduces a multiple number of challenges such as pilot contamination, collision, model complexity, resource allocation and etc. [1] This article investigates the using of this new SM technique in Multi-user MIMO networks, denoted here as MU-QSM. [2] The IoT $K$ -User MIMO networks described improve upon prior multi-user capacity results through the application of a new beamformer modality. [3]具有信道衰落效应的多用户 MIMO 网络系统引入了导频污染、冲突、模型复杂度、资源分配等诸多挑战。 [1] 本文研究了这种新的 SM 技术在多用户 MIMO 网络中的使用，这里表示为 MU-QSM。 [2] nan [3]
Scale Mimo Network
To minimize the total power consumption, we further propose an improved coalition game approach to effectively optimize MU clustering for the large-scale MIMO networks, in which the size of a cluster is flexible. [1] In this paper, we study the performance of large-scale MIMO network where the base station has a large number of antennas and performs semi-blind channel estimation. [2]为了最小化总功耗，我们进一步提出了一种改进的联盟博弈方法，以有效优化大规模 MIMO 网络的 MU 聚类，其中集群的大小是灵活的。 [1] 在本文中，我们研究了基站具有大量天线并执行半盲信道估计的大规模 MIMO 网络的性能。 [2]
mimo network deployment
We also provide design guidelines and requirements for massive MIMO network deployment and proper acceptance of Key Performance Indicators (KPIs) collection and comparisons criteria. [1] Our numerical results reveal that a cell-free massive MIMO architecture may provide better performance than a traditional multicell massive MIMO network deployment. [2] Massive MIMO network deployments are expected to be a key feature of the upcoming 5G communication systems. [3]我们还为大规模 MIMO 网络部署和正确接受关键性能指标 (KPI) 收集和比较标准提供设计指南和要求。 [1] 我们的数值结果表明，无蜂窝大规模 MIMO 架构可以提供比传统多蜂窝大规模 MIMO 网络部署更好的性能。 [2] 大规模 MIMO 网络部署预计将成为即将到来的 5G 通信系统的一个关键特征。 [3]
mimo network system
It is built on the concept of integrating and interfacing optimized MIMO network systems with primary focus on achieving high spectral efficiency, link reliability, and optimum power operation. [1] A multi-user MIMO network system with channel fading effect introduces a multiple number of challenges such as pilot contamination, collision, model complexity, resource allocation and etc. [2]它建立在集成和连接优化的 MIMO 网络系统的概念之上，主要关注实现高频谱效率、链路可靠性和最佳功率操作。 [1] 具有信道衰落效应的多用户 MIMO 网络系统引入了导频污染、冲突、模型复杂度、资源分配等诸多挑战。 [2]
mimo network architecture Mimo 网络架构
Cell-free massive multiple-input--multiple-output (MIMO) (CF-mMIMO) is a distributed massive MIMO network architecture, which leads to a better ability to resist shadow fading than centralized massive MIMO. [1] A good match to Terahertz communication is cell-free massive MIMO network architecture, where the antenna beams are located irregularly, coordination among base stations is required to improve the throughput. [2]无单元大规模多输入多输出（MIMO）（CF-mMIMO）是一种分布式大规模MIMO网络架构，与集中式大规模MIMO相比，具有更好的抗阴影衰落能力。 [1] 与太赫兹通信的一个很好的匹配是无蜂窝大规模 MIMO 网络架构，其中天线波束的位置不规则，需要基站之间的协调以提高吞吐量。 [2]