基于毫米波大规模MIMO的混合RZF预编码算法

针对毫米波大规模MIMO系统采用全数字预编码时,系统所需射频链路数量较大而导致实现成本和能耗较高的问题,提出了一种在基站端和用户端分别采用混合预编码和模拟合并的方案.在充分考虑信道特性的基础上,根据收发两端的天线阵列响应矢量分别设计模拟预编码矩阵和模拟合并矩阵,然后根据生成的有效信道矩阵,在基带部分设计低维的数字预编码,从而消除系统中噪声和用户间干扰的影响.仿真结果表明,在有效减少系统所需射频链路数量的基础上,所提混合预编码方案能够接近传统全数字预编码方案的性能.     

改进的IRS辅助毫米波MIMO级联信道估计

为改善智能反射表面（Intelligent reflective surface,IRS）辅助的毫米波多输入多输出（Multiple-input multiple-output,MIMO）级联信道的估计精度和收敛速度,基于平行因子（Parallel factor,PARAFAC）分解模型,把常规的双线性交替最小二乘（Bilinear alternating least squares,BALS）算法改进为带松弛因子的ω-BALS算法和正则化的T-BALS,加快了收敛速度和算法稳定性。当基站、IRS元件或用户侧的阵列天线数目较大时,提出改进的奇异值（Singular value decomposition,svd）-BALS算法。该算法通过奇异值分解压缩张量,再利用低维度的核心张量来重构模式n矩阵。仿真结果表明,该算法的归一化均方误差性能有所提高,并且加快了收敛速度。     

Wideband high aperture efficiency antennas with beam switching for mmWave 5G base stations

A compact metamaterial inspired sub‐wavelength unit cells are integrated into wideband Vivaldi antenna. A high gain Vivaldi antenna with 50% impedance bandwidth is proposed. The dimensions of the antenna are 1.55 λ₀ × 3.2 λ₀ at 28 GHz. Gain enhancement of 3‐dB achieved by placing metamaterial unit cells in the aperture of the antenna. These unit cells aid in phase correction of the antenna. The 1‐dB gain bandwidth of antenna is 42% with a peak gain of 12.5 dBi indicating high pattern integrity. Corrugations of varying length are introduced in the ground plane to improve front‐to‐back ratio without altering the input impedance bandwidth. The aperture efficiency of the metamaterial loaded Vivaldi antenna is 78% at 28 GHz. The proposed element is used in a stacked module to achieve wide angular coverage of 120°.     

基于改进离散布谷鸟搜索算法的毫米波大规模MIMO系统波束选择

在毫米波大规模MIMO系统中采用全数字编码需要大量的射频链路,从而导致能量损耗过高。针对这一问题提出一种基于离散布谷鸟搜索算法(Discrete cuckoo search, DCS)的波束选择方案,减少所需射频链路数而不会造成明显的性能损失。首先分析毫米波大规模MIMO系统的波束选择模型,引用DCS算法来求解模型;然后针对布谷鸟算法Levy飞行离散化结果中出现的非正常编码,采用启发式贪婪算法进行修复;将遗传算法中的复制引入DCS算法中,复制全局最优的鸟巢来替换其中被发现的鸟巢,加快算法收敛速度。仿真结果表明,所提基于改进DCS算法的波束选择方案相比几种已有的方案可以获得更优的和速率性能。     

基于两步噪声学习网络的波束域毫米波大规模MIMO信道估计

针对波束域毫米波大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)系统,构建了一种新型两步噪声学习网络（Two-step Noise Learning Network,TNLNet）。基本原理是在接收信号反复经过卷积层和池化层提取噪声特征的基础上,利用波束域毫米波大规模MIMO信道矩阵稀疏性所引起的相邻元素相近的特点,采用下采样将信道矩阵重构成4个子矩阵,提高训练测试效率。该算法具有以比全卷积去噪近似消息传递(Fully Convolutional Denoising Approximate Message Passing,FCDAMP)算法和学习去噪的近似消息传递(Learned Denoising-based Approximate Message Passing,LDAMP)算法更低的复杂度,取得了比最小二乘算法、最小均方误差算法、FCDAMP和LDAMP更优的归一化均方误差（Normalized Mean Squared Error,NMSE）性能;与快速灵活去噪卷积神经网络(Fast and Flexible Denoising convolutional neural Network,FFDNet)相比虽然复杂度略高,但具有更优的NMSE性能,且在单一训练模型中获得了比FFDNet更宽的信噪比适用范围,增强了实用性。     

5G/B5G毫米波网络TCP传输性能分析

5G/B5G移动通信系统的高带宽、高可靠性和低延迟的通信需求需要更多新技术的支持.毫米波由于其丰富的频谱资源和极高的带宽容量而成为5G/B5G移动通信系统的研究热点之一.不同于以往由有线网络主导的互联网架构,如今的移动互联网已经成为无线接入网和高速核心网的融合.但是目前对毫米波端到端通信传输性能的研究工作还相对较少,而且多采用仿真实验.本文利用真实网络设备,通过开展真实网络环境下的实验,对毫米波链路基本传输性能和5G/B5G毫米波网络端到端通信系统中TCP传输性能进行测量分析,研究5G/B5G毫米波网络传输过程中的链路瓶颈,为设计毫米波端到端网络传输协议,提高网络传输吞吐率奠定基础.     

无人机协助的多用户MIMO毫米波网络混合预编码方案

针对无人机(UAV)协助的毫米波网络下行链路多用户通信场景,设计一种混合预编码方案.在发射端和接收端分别使用混合预编码器和模拟合并器,并将多元联合优化问题分解为子问题进行求解.构建UAV与地面用户的三维位置模型,利用带外位置信息对波束导向向量进行优化,进而通过码本生成模拟预编码器和模拟合并器.以最小化接收数据和发送数据...     

基于改进智能水滴的正交匹配追踪混合预编码算法

针对毫米波大规模多输入多输出(mmWave Massive MIMO)系统硬件成本高、系统开销大等问题,提出一种基于改进智能水滴的正交匹配追踪(IWD-OMP)混合预编码算法.首先,基于正交匹配追踪(OMP)算法求解预编码矩阵;其次,采用改进的智能水滴(IWD)算法求解矩阵中全局最优的索引向量;最后,通过此方法求解的矩...     

A Compact 28 GHz Millimeter Wave Antenna for Future Wireless Communication

This article presents a novel modified chuck wagon dinner bell shaped millimeter wave (mm-wave) antenna at 28 GHz. The proposed design has ultra-thin Rogers 5880 substrate with relative permittivity of 2.2. The design consists of T shaped resonating elements and two open ended side stubs. The desired 28 GHz frequency response is achieved by careful parametric modeling of the proposed structure. The maximum achieved single element gain at the desired resonance frequency is 3.45 dBi. The efficiency of the proposed design over the operating band is more than 88%. The impedance bandwidth achieved for −10 dB reference value is nearly 2.9 GHz. The proposed antenna is transformed into four element linear array which increases the gain up to 10.5 dBi. The fabricated prototype is tested for the measured results. It is observed that measured results closely match the simulated results. By considering its simple structure and focused radiation patterns, the proposed design is well suited for IoT (Internet of Things), mmWave microwave sensing, 5G and future RF (Radio Frequency) front-ends.     

Double Deep Q-Network Method for Energy Efficiency and Throughput in a UAV-Assisted Terrestrial Network

Increasing the coverage and capacity of cellular networks by deploying additional base stations is one of the fundamental objectives of fifth-generation (5G) networks. However, it leads to performance degradation and huge spectral consumption due to the massive densification of connected devices and simultaneous access demand. To meet these access conditions and improve Quality of Service, resource allocation (RA) should be carefully optimized. Traditionally, RA problems are nonconvex optimizations, which are performed using heuristic methods, such as genetic algorithm, particle swarm optimization, and simulated annealing. However, the application of these approaches remains computationally expensive and unattractive for dense cellular networks. Therefore, artificial intelligence algorithms are used to improve traditional RA mechanisms. Deep learning is a promising tool for addressing resource management problems in wireless communication. In this study, we investigate a double deep Q-network-based RA framework that maximizes energy efficiency (EE) and total network throughput in unmanned aerial vehicle (UAV)-assisted terrestrial networks. Specifically, the system is studied under the constraints of interference. However, the optimization problem is formulated as a mixed integer nonlinear program. Within this framework, we evaluated the effect of height and the number of UAVs on EE and throughput. Then, in accordance with the experimental results, we compare the proposed algorithm with several artificial intelligence methods. Simulation results indicate that the proposed approach can increase EE with a considerable throughput.