Multipath multihop mmWave backhaul in ultra-dense small-cell network

Ultra-Dense Network (UDN) is considered to be the key enabler for realizing capacity goals set by 5G. The major concern in UDN deployment is the backhaul network, which should be scalable, cost-effective, and have sufficient capacity to support massive small cell traffic. Otherwise, the backhaul can become the bottleneck of the network. In this paper, we propose a wireless backhaul solution for UDN deployment by considering MultiPath-MultiHop (MPMH) backhaul architecture in mmWave frequency band. In addition, we propose a distributed routing scheme to forward the backhaul traffic over the multihop network. Backhaul capacity and line-of-sight probability of the proposed backhaul architecture for various picocell densities were compared with direct, multiple-association, and multihop backhaul schemes under interference limited scenarios in outdoor and indoor small cell deployments. The simulation results indicate that the MPMH mmWave backhaul is the most cost-effective and scalable solution for UDN deployment.     

一种低信噪比下基于深度学习的DoA估计方法

针对低信噪比下毫米波系统多径方位估计问题,提出了一种基于深度学习的多径波达方向估计方法。该方法通过构建协方差矩阵与多径角度间的映射模型来实现：首先利用接收信号,构建抽样协方差矩阵;然后,通过基于深度残差收缩网络的多标签分类模型,实现视距传输路径角度估计;最后,利用基于卷积神经网络的回归模型,实现非视距传输路径的角度估计。仿真结果表明,与传统方法相比,所提方法能够显著降低均方根误差,并且在低信噪比下可以取得较低的角度估计误差;在不同场景下,所提方法具有良好的适用性。     

Time‐Slotted Scheduling Schemes for Multi‐hop Concurrent Transmission in WPANs with Directional Antenna

To achieve high‐speed (giga‐bit) connectivity for short‐range wireless multimedia applications, the millimeter‐wave (mmWave) wireless personal area networks with directional antennas are gaining increased interest. Due to the use of directional antennas and mmWave communications, the probability of non‐interfering transmissions increases in a localized region. Network throughput can be increased immensely by the concurrent time allocation of non‐interfering transmissions. The problem of finding optimum time allocation for concurrent transmissions is an NP‐hard problem. In this paper, we propose two enhanced versions of previously proposed multi‐hop concurrent transmission (MHCT) schemes. To increase network capacity, the proposed schemes efficiently make use of the free holes in the time‐allocation map of the MHCT scheme; thus, making it more compact.     

毫米波MIMO系统中基于正交码本的模数混合预编码算法

由于毫米波混频器件的高成本和高功耗,传统MIMO系统的数字预编码技术面临硬件复杂度过高的缺点,因而模数混合预编码吸引了学术界和工业界的广泛关注.基于此,提出了一种基于正交码本的模数混合预编码算法,该算法利用模拟波束成形码本的正交性,并行地设计各个射频链路的波束成形向量,显著降低了传统混合预编码设计中正交匹配追踪算法的计算复杂度,从而降低了硬件实现的复杂度.     

A robust beam tracking scheme for millimeter wave HetNets

Millimeter Wave (mmWave) communication has been widely acknowledged as an attractive solution to address high-speed transmission of massive data in 5G and beyond 5G systems due to the promising spectrum availability. However, mmWave signals are highly susceptible to blockage and may suffer from rapidly changing channels. Thus, directional/beam tracking becomes imperative yet essential for robust mmWave communications. To address this challenge, we propose a robust beam tracking scheme for mmWave Heterogeneous Networks (HetNets) with multi-connectivity. Different from most existing schemes, the proposed beam tracking scheme is effective for outage events. We first discuss the μWave-assisted beam tracking procedure with and without candidate beams, and then analyze the inherent correlation between mmWave link quality and the operating beamwidth and occlusion range to derive the optimal beamwidth. Theoretical and numerical results show that the proposed beam tracking scheme can improve the robustness of mmWave communications while guaranteeing the rate performance.     

基于射线跟踪的车联网毫米波信道准平稳区间研究

针对28 GHz车联网中车对基础设施（Vehicle-to-Infrastructure，V2I）毫米波信道，开展了准平稳区间的研究.首先，分析了信道准平稳区间的理论基础和计算方法.其次，利用功率相关（Correlation of Power，CP）算法和谱散度（Spectral Divergence，SD）算法进行准平稳区间的计算.结果表明，CP算法复杂度低且精度较高，更适合用于计算V2I通信场景下的准平稳区间.最后，利用CP算法计算出的准平稳区间作为新的采样间隔，从而减少了射线跟踪仿真器的采样点数.通过原始采样和减少采样点后的信道特性的比较，在合理的门限值下，利用信道准平稳区间的方法加速了射线跟踪仿真器，并且不会造成信道参数的失真.另外，对于信道特性的分析结果也对车联网在毫米波频段的仿真和设计具有重要意义.     

Joint hybrid beamforming and power splitting design in millimeter-wave simultaneous wireless information and power transfer system

A joint hybrid beamforming and power splitting(JHBPS) design problem for simultaneous wireless information and power transfer(SWIPT) in millimeter-wave(mmWave) system is studied.The considered scenario is a multi-antenna base station(BS) transfers information and energy simultaneously to multiple single-antenna receivers.BS adopts hybrid digital and analog beamforming architecture to reduce hardware costs.Receivers separate acquired signals with power splitters either for information decoding(ID) or energy harvesting(EH).The aim is minimizing total transmission power by joint design of hybrid beamforming and PS under ID and EH requirements.It is difficult to obtain the optimal hybrid beamformer directly since the analog beamformer and digital beamformer are multiplied.Therefore,a two-stage algorithm is proposed to solve the problem.In the first stage,the optimal beamformer and PS ratios are obtained by solving the joint transmission beamforming and PS design problem.In the second stage,the optimal beamformer is approximated with the product of analog beamformer and digital beamformer.The superiority of proposed algorithm over the existing algorithms is demonstrated through simulations.Moreover,the effectiveness of approximation algorithm is testified.     

Energy-efficient hybrid beamforming for millimeter-wave-based massive multiple-input multiple-output system

The advanced wireless communication system requires abridged energy consumption, enhanced data rate, and good signal coverage. The massive MIMO technology for 5G systems has been developed to accommodate several users simultaneously with superior throughput. The claim for high data rate wireless communication services is expanding quickly as time goes. Thus, the key difficulty is that as the number of users grows, the number of phase shifters grows as well, causing the system to consume more power; as a result, the system's energy efficiency decreases. Hybrid beamforming has recently emerged as an attractive technique for millimeter-wave (mmWave) communication systems. The analog beamformer in the RF domain and digital beamformer in the baseband are coupled through a minimal number of RF chains in hybrid beamforming architecture. Hybrid beamforming utilizes fewer RF (radio frequency) chains than the total number of antennas to have a lower energy consumption design. The hybrid beamforming for a mmWave-based massive MIMO system through different phase shifter selection mechanisms is proposed to achieve the highest energy efficiency for mmWave communications systems. The fully connected with phase shifter selection, sub-connected with phase shifter selection (SPSS), and fully connected and sub-connected with phase shifter selection with halved and doubled switches are considered for this research. The simulation results show the SPSS with halved switch outperforms on energy efficiency.     

一种面向B5G初始接入过程的增强型波束管理机制设计

波束管理是毫米波通信的重要研究内容,5G NR（New Radio）协议中已完整设计了用户在初始接入和连接状态下与基站确定最佳通信波束的流程,然而B5G(Beyond Fifth Generation)场景将使用52.6 GHz以上甚至更高的通信频率,需要更大规模的天线单元对抗路损,导致波束管理在初始接入过程中的信令开销和时延急剧增加。为此,在5G NR协议现有框架的基础上,针对52.6 GHz以上的高频段重新设计了一种专用于波束扫描的信号块（Beam Sweeping Block,BSB）,并提出一种两阶段增强型波束管理机制,用于在初始接入过程中快速确定用户和基站的最佳通信波束,进而完成同步和小区搜索。仿真结果表明,相对于NR中现有的波束管理机制,所提出的增强型波束管理方案可在保证接入性能的前提下,大幅降低初始接入时延。     

Millimeter-Wave Concurrent Beamforming: A Multi-Player Multi-Armed Bandit Approach

The communication in the Millimeter-wave (mmWave) band, i.e., 30~300 GHz, is characterized by short-range transmissions and the use of antenna beamforming (BF). Thus, multiple mmWave access points (APs) should be installed to fully cover a target environment with gigabits per second (Gbps) connectivity. However, inter-beam interference prevents maximizing the sum rates of the established concurrent links. In this paper, a reinforcement learning (RL) approach is proposed for enabling mmWave concurrent transmissions by finding out beam directions that maximize the long-term average sum rates of the concurrent links. Specifically, the problem is formulated as a multiplayer multiarmed bandit (MAB), where mmWave APs act as the players aiming to maximize their achievable rewards, i.e., data rates, and the arms to play are the available beam directions. In this setup, a selfish concurrent multiplayer MAB strategy is advocated. Four different MAB algorithms, namely, ϵ-greedy, upper confidence bound (UCB), Thompson sampling (TS), and exponential weight algorithm for exploration and exploitation (EXP3) are examined by employing them in each AP to selfishly enhance its beam selection based only on its previous observations. After a few rounds of interactions, mmWave APs learn how to select concurrent beams that enhance the overall system performance. The proposed MAB based mmWave concurrent BF shows comparable performance to the optimal solution.