Beam Tracking Particle Filter for Hybrid Beamforming and Precoding Systems

Because millimeter wave (mmWave) systems can span notably wide spectral bands, mmWave systems are expected to dominate fifth-generation (5G) communication systems. Due to the short wave-length of mmWave radiation, multiple-input multiple-output (MIMO) systems can use massive antennas and precoding technology to overcome signal attenuation in mmWave channels. However, the cost and power consumption of radio frequency (RF) chains would increase substantially with the number of antennas. Hence, hybrid beamforming was proposed to reduce the number of RF chains in massive MIMO systems. Hybrid beamforming involves RF beamforming matrix construction and baseband precoding matrix derivation. This study focused on the design and implementation of an algorithm for the RF beamforming matrix construction for mobile environments. Accordingly, this study presents a mixture particle filter that exploits the temporal continuity of beam clusters in a mobile mmWave channel to reduce the computational complexity of RF beamforming matrix construction. Moreover, this beam-tracking particle filter is based on parallel processing architecture to support the tracking of multiple beam clusters in the mmWave channel. Finally, the beam-tracking particle filter was implemented on a field-programmable gate array platform and was verified in a hybrid beamforming system for mmWave MIMO systems. The particle filter processor achieved a maximal throughput of 9.198k matrices/s with a clock rate of 192 MHz, which could support a speed of up to 88.5 km/h for mobile users.

     

Channel estimation for multi-panel millimeter waveMIMO based on joint compressed sensing

Channel state information (CSI) is essential for downlink transmission in millimeter wave( mmWave) multipleinput multiple output (MIMO) systems. Multi-panel antenna array is exploited in mmWave MIMO system due to itssuperior performance. Two channel estimation algorithms are proposed in this paper, named as generalized jointorthogonal matching pursuit (G-JOMP) and optimized joint orthogonal matching pursuit (O-JOMP) for multi-panelmmWave MIMO system based on the compressed sensing (CS) theory. G-JOMP exploits common sparsity structureamong channel response between antenna panels of base station ( BS) and users to reduce the computationalcomplexity in channel estimation. O-JOMP algorithm is then developed to further improve the accuracy of channelestimation by optimal panel selection based on the power of the received signal. Simulation results show that theperformance of the proposed algorithms is better than that of the conventional orthogonal matching pursuit (OMP)based algorithm in multi-panel mmWave MIMO system.     

Robust hybrid beamforming design for millimeter-wave massive MIMO systems

Hybrid analog-digital beamforming is recognized as a promising solution for a practical implementation of massive multiple-input multiple-output(MIMO) systems based on millimeter-wave(mmWave) technology. In view of the overwhelming hardware cost and excessive power consumption and the imperfection of the channel state information(CSI), a robust hybrid beamforming design is proposed for the mmWave massive MIMO systems, where the robustness is defined with respect to imperfect knowledge or error of the CSI at the transmitter due to limited feedback and/or imperfect channel estimation. Assuming the errors of the CSI are bounded, the optimal hybrid beamforming design with robustness is formulated to a mean squared error(MSE) minimization problem. An iterative semidefinite programming(SDP) based algorithm is proposed to obtain the beamforming matrices. Simulation results show that the proposed robust design can provide more than 4 dB performance gain compared to that of non-robust design.     

Intelligent channel estimation in millimeter wave massive MIMO communication system using hybrid deep learning with heuristic improvement

The major goal of millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems is to get effective channel state information (CSI). Most of the recent works use nuclear norm theory for recovering the low-rank scheme of channels. Some suboptimal solutions to the rank minimization problem can occur while addressing the nuclear norm-based convex problem, which degrades the accuracy of channel estimation. Some works recover the channel with the assumption of the mmWave channel using an over-complete dictionary. On the other hand, the accuracy of available CSI may openly influence the efficiency of mmWave communications. The main intention of this paper is to develop an enhanced channel estimation model with an optimized hybrid deep learning model. Here, the integration of deep neural network (DNN) and long short-term memory (LSTM) form the hybrid deep learning model termed optimized D-LSTM, which is modified by the opposition searched exploration-based Harris hawks optimization (OE-HHO). The input to the proposed hybrid deep learning is taken as the correlation among the received signal vectors and the measurement matrix for predicting the beam space channel amplitude. Finally, the successful channel estimation is observed by deep hybrid learning by the experimental outcomes, which also demonstrate that the proposed channel estimation model overwhelms the conventional models in terms of Normalized Mean-Squared Error (NMSE) and spectral efficiency. The experimental results show that the designed OE-HHO method obtains 9.2%, 8.9%, 8.65%, and 0.47% progressed than DA, DHOA, GWO, and HHO, respectively. Therefore, higher efficiency is observed by OE-HHO based mmWave MIMO communication system.     

基于GSIC的上行链路毫米波大规模MIMO-NOMA系统低功耗传输方法

非正交多址接入（non-orthogonal multiple access,NOMA）和毫米波大规模多输入多输出（multiple-input multiple-output,MIMO）的结合能够支持未来无线通信网络的巨流量大连接需求。研究了上行链路毫米波大规模MIMO-NOMA系统中的功率最小化问题，提出了基于群体串行干扰消除（group-levelsuccessiveinterference cancellation,GSIC）的混合波束成形毫米波MIMO-NOMA上行传输系统新架构。具体来说，根据信道增益对用户进行群体划分，不同群体用户由NOMA服务，群体内用户采用空分多址区分。通过给不同群体设计模拟波束成形矩阵，对数字波束成形和功率控制进行联合优化，提出了一种并行迭代算法来解决优化问题。仿真结果表明，所提出的新架构在总功率方面优于传统的基于分簇和用户级串行干扰消除的毫米波大规模MIMO-NOMA。     

Hybrid beamforming with discrete phase shifters for millimeter wave backhaul networks

Hybrid beamforming (HBF) technology becomes one of the key technologies in the millimeter wave (mmWave) mobile backhaul systems, for its lower complexity and low power consumption compared to full digital beamforming (DBF). Two structures of HBF exist in the mmWave mobile backhaul system, namely, the fully connected structures (FCS) and partially connected structures (PCS). However, the existing methods cannot be applied to both structures. Moreover, the ideal phase shifter is considered in some current HBF methods, which is not realistic. In this paper, a HBF algorithm for both structures based on the discrete phase shifters is proposed in the mmWave mobile backhaul systems. By using the principle of alternating minimization, the optimization problem of HBF is decomposed into a DBF optimization problem and an analog beamforming (ABF) optimization problem. Then the least square (LS) method is enabled to solve the optimization model of DBF. In addition, the achievable data rate for both structures with closed-form expression which can be used to convert the optimization model into a single-stream beamforming optimization model with per antenna power constraint is derived. Therefore, the ABF is easily solved. Simulation results show that the performance of the proposed HBF method can approach the full DBF by using a lower resolution phase shifter.     

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.     

A novel threshold based compressed channel sensing in OFDM system

High speed data transmission for wireless communication in orthogonal frequency division multiplexing (OFDM) system requires effective channel state information (CSI). CSI should be precisely estimated with low consumption of spectral resources and acceptable computational cost. To realize this goal, an effective compressed sensing (CS) based channel estimation scheme is proposed for sparse channels with large delay spreads, without prior knowledge of channel statistics and noise standard deviation. By fully considering the rank of the measurement matrix, a novel algorithm based on orthogonal matching pursuit (OMP) and least squares (LS) methods with a new threshold is proposed for effective channel estimation. Simulation results show that with fewer number of pilots, the proposed method outperforms the compared existing channel estimation methods in a comprehensive way and approaches the optimal channel estimation performance.     

Signal Processing by Generalized Receiver in?DS-CDMA Wireless Communication Systems with?Frequency-Selective Channels

The generalized receiver (GR) based on a generalized approach to signal processing (GASP) in noise is investigated in a direct-sequence code-division multiple access (DS-CDMA) wireless communication system with frequency-selective channels. We consider four avenues: linear equalization with finite impulse response (FIR) beamforming filters; channel estimation and spatially correlation; optimal combining; and partial cancellation. We investigate the GR with simple linear equalization and FIR beamforming filters. Numerical results and simulation show that the GR with FIR beamforming filters surpasses in performance the optimum infinite impulse response beamforming filters with conventional receivers, and can closely approach the performance of GR with infinite impulse response beamforming filters. Channel estimation errors are taken into consideration so that DS-CDMA wireless communication system performance will not be degraded under practical channel estimation. GR takes an estimation error of a maximum likelihood (ML) multiple-input multiple-output (MIMO) channel estimation and GR spatially correlation into account in computation of minimum mean square error (MMSE) and log-likelihood ratio (LLR) of each coded bit. The symbol error rate (SER) performance of DS-CDMA employing GR with a quadrature sub-branch hybrid selection/maximal-ratio combining (HS/MRC) scheme for 1-D modulations in Rayleigh fading is obtained and compared with that of conventional HS/MRC receivers. Procedure of selecting a partial cancelation factor (PCF) for the first stage of a hard-decision partial parallel interference cancellation (PPIC) of the GR employed in DS-CDMA wireless communication system is proposed. A range of optimal PCFs is derived based on the Price’s theorem. Computer simulation results show superiority in bit error rate (BER) performance that is very close to that potentially achieved and surpasses the BER performance of the real PCF for DS-CDMA systems discussed in literature.     

MIMO-OFDM快衰落信道的稀疏自适应感知估计

在多输入多输出（MIMO）-正交频分复用（OFDM） 系统中,怎样在较高频谱利用率的情况下对快时变信道进行较为准确的估计是一个具有挑战性的课题。该文在利用压缩感知理论可提高系统频谱利用率的基础上,提出了一种适合于快时变环境下MIMO-OFDM 系统的稀疏自适应信道估计方法。该方法不再受到奈奎斯特采样频率条件约束,避免了传统导频辅助信道估计方法频谱利用率低的缺点。该文方法通过构建多天线群时频结构特征稀疏基,利用多天线间和群时变OFDM符号内信道冲激响应具有更强稀疏性的特点,对MIMO-OFDM快衰落信道进行稀疏变换。由于实际MIMO-OFDM快衰落信道往往处于频率选择性、时变性和多种干扰并存的复杂环境,受到干扰的信道参数对系统而言是未知,采用该方法克服了现有基于压缩感知理论的信道估计方法需要预先知道信道冲激响应稀疏度才能重构信道参数的不足,在信道稀疏度未知道的情况下,运用稀疏自适应的方法来对不同时频结构特征的信道参数进行估计。仿真结果表明所提估计方法具有对快时变信道参数估计的鲁棒性和较高频谱利用率,且均方误差小。      

AoA-Based Channel Estimation for Massive MIMO OFDM Communication Systems on High Speed Rails

Channel estimation is a well-known challenge for wireless orthogonal frequency division multiplexing(OFDM)communication systems with massive antennas on high speed rails(HSRs).This paper investigates this problem and design two practicable uplink and downlink channel estimators for orthogonal frequency division multiplexing(OFDM)communication systems with massive antenna arrays at base station on HSRs.Specifically,we first use pilots to estimate the initial angle of arrival(AoA)and channel gain information of each uplink path through discrete Fourier transform(DFT),and then refine the estimates via the angle rotation technique and suggested pilot design.Based on the uplink angel estimation,we design a new downlink channel estimator for frequency division duplexing(FDD)systems.Additionally,we derive the Cramér-Rao lower bounds(CRLBs)of the AoA and channel gain estimates.Finally,numerical results are provided to corroborate our proposed studies.     

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.     

Space‐time block coding in millimeter wave large‐scale MIMO‐NOMA transmission scheme

In this paper, we introduce a new wireless system architecture using space‐time block coding schemes (STBC) and non‐orthogonal multiple access (NOMA) in millimeter wave (mmWave) large‐scale MIMO systems. The proposed STBC mmWave large‐scale MIMO‐NOMA system utilizes two MIMO subarrays, transmitting data over two channel vectors to mobile users. To reduce the communication overhead and latency in the system, we utilize random beamforming with optimal coefficients at the base station and random‐near random‐far user pairing in implementing the NOMA scheme. Our results show that the proposed STBC mmWave large‐scale MIMO‐NOMA technique significantly outperforms the previous counterparts.     

Diversity gain for cdma systems equipped with antenna arrays

If the angular spread is not zero, the diversity gain can be achieved in the antenna-array reception. In order to achieve the diversity gain, we propose a beamforming method that utilizes two beamforming weight vectors and apply this beamforming technique to code-division multiple-access (CDMA) systems equipped with antenna arrays under a time-varying multipath-fading channel environment. In the proposed beamforming method, the channel vector has been estimated using two basis vectors that span the signal subspace. Since the proposed beamforming method utilizes two-dimensional (2D) signal subspace, it provides better performance than the conventional beamforming method, which utilizes one-dimensional signal subspace. Through simulation results, we can see that the performance is improved as the angular spread gets larger.     

28 GHz室内毫米波信道路径损耗模型研究

毫米波信道建模是第五代（the 5th Generation,5G）移动通信系统的关键技术,而路径损耗是表征毫米波信道传播大尺度衰落影响的重要参数.为了更好地理解毫米波信道的传播特性,应进行广泛的信道测量与建模.因此,对28 GHz室内环境进行了信道测量,并给出了相应的毫米波信道路径损耗模型,同时基于入射及反弹射线法/镜像法仿真分析了路径损耗传播特性.研究结果表明:实测结果与仿真结果一致性吻合良好,从而验证了入射及反弹射线法/镜像法的正确性;自由空间邻近（Close-In,CI）参考距离路径损耗模型表达式更简洁,鲁棒性更强.最后,本文给出了一种普遍适用的用来表征室内视距（Line-of-Sight,LOS）与非视距（Non-Line-of-Sight,NLOS）环境28 GHz与60 GHz毫米波信道的路径损耗模型.     

Joint binary image deconvolution and blur identification in the context of two-dimensional storage channels

We consider blurring of binary images and corruption by ambient noise occuring on two-dimensional storage channels. Since coding is generally used in such systems, the deconvolution problem can be treated jointly with decoding. Several methods have been proposed in the literature under the name of turbo equalization to mitigate the degradation introduced by such channels. However, the problem of blur identification has rarely been addressed previously. In this paper, we propose a technique for estimating the 2D channel coefficients, along with the variance of the ambient noise. The proposed estimation algorithm is adaptive and performed jointly with turbo equalization, so as to limit the number of known pilot symbols needed to bootstrap the channel estimator. Interestingly, we found that the computational complexity of the proposed joint channel estimation and turbo equalization method depends heavily on the sensitivity of existing turbo equalization methods to 2D channel parameter mismatch.     

CRLB for DOA Estimation in Gaussian and Non-Gaussian Mixed Environments

The determination of Cramer-Rao lower bound (CRLB) as an optimality criterion for the problem of Direction-of-arrival (DOA) estimation is a very important issue. Several CRLBs on DOA estimation have been derived for Gaussian noise. However, a practical channel is affected by not only Gaussian background noise but also non-Gaussian noise such as impulsive interference. This paper derives the deterministic CRLB for Gaussian and non-Gaussian mixed environments. Since non-parametric kernel method is used to build the probability density function (PDF) of non-Gaussian noise, the CRLB derived is suitable for various noise distributions with or without symmetric PDF. The relationship between the CRLB for Gaussian noise and the proposed CRLB is also investigated. Theoretical analysis shows that the proposed CRLB provides a unified representation for both the cases of Gaussian and mixed environments. Computer simulations are included to verify the derived CRLB in different noise environments.     

5G毫米波信道估计研究综述

信道估计是大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)毫米波(Millimeter Wave,mmWave)系统关键技术之一.梳理了近几年大规模MIMO毫米波的信道估计策略,重点从压缩感知(Compressive Sensing,CS)、参数估计和深度学习三个方面进行了描...     

A Technique for Frequency Synchronization in Multi-Band OFDM in Realistic UWB Channel

This paper presents a highly accurate frequency offset estimation algorithm for multi-band orthogonal frequency division multiplexing (MB-OFDM) systems effective for realistic ultra-wideband (UWB) environment. The proposed algorithm derives its estimates based on phase differences in the received subcarrier signals of several successive OFDM symbols in the preamble. We consider different carrier frequency offsets and different channel responses in different bands to keep the analysis and simulation compatible for practical multi-band UWB scenario. Performance of the proposed algorithm is studied by means of bit error rate (BER) performance of MB-OFDM system. In order to compare the variance of the synchronizer to that of the theoretical optimum, we derive the Cramer–Rao lower bound (CRLB) of the estimation error variance and compare it with the simulated error variance both in additive white Gaussian noise and UWB channel model (CM) environments, CM1–CM4. Next, we modify the estimation algorithm by proposing a multi-band averaging frequency offset synchronization (MBAFS) scheme. We establish superior BER performance with MBAFS compared to our first scheme. We calculate modified CRLB for MBAFS and compare it with simulation results for CM1–CM4. Both analysis and simulation show that MBAFS algorithm can estimate the carrier frequency offset effectively and precisely in UWB fading channels for MB-OFDM applications. We also analyze the computational complexity of both the proposed algorithms in order to verify their feasibility of implementation in practical UWB receiver design.     

面向6G的毫米波多频段多天线信道测量系统构建及实测验证

毫米波是5G和6G无线通信系统的关键技术.设计满足6G多频段、多天线、高动态范围需求的信道测量系统是6G无线信道研究面临的首要挑战.针对这一需求,本文构建了一种毫米波多频段多天线信道测量系统,可以覆盖24.25～28.5 GHz、31.8～33.4 GHz、37～42.5 GHz等毫米波频段,支持最高16×16天线配置.首先介绍该信道测量系统的架构与性能指标,提出多通道并行校准方案以及测量数据处理算法;其次,基于该信道测量系统开展26 GHz室内外场景的信道测量实验,分析路径损耗、时延扩展以及奇异值扩展等信道统计特性.通过对实测结果分析,验证了该信道探测器用于毫米波段测量的有效性.