A review of codebooks for CSI feedback in 5G new radio and beyond

Codebooks have been indispensable for wireless communication standard since the first release of the Long-Term Evolution in 2009. They offer an efficient way to acquire the channel state information (CSI) for multiple antenna systems. Nowadays, a codebook is not limited to a set of pre-defined precoders, it refers to a CSI feedback framework, which is more and more sophisticated. In this paper, we review the codebooks in 5G New Radio (NR) standards. The codebook timeline and the evolution trend are shown. Each codebook is elaborated with its motivation, the corresponding feedback mechanism, and the format of the precoding matrix indicator. Some insights are given to help grasp the underlying reasons and intuitions of these codebooks. Finally, we point out some unresolved challenges of the codebooks for future evolution of the standards. In general, this paper provides a comprehensive review of the codebooks in 5G NR and aims to help researchers understand the CSI feedback schemes from a standard and industrial perspective.Comment: 11pages, 7 figures, 1 table, magzine revie

Eigenvector prediction-based precoding for massive MIMO with mobility

Eigenvector decomposition (EVD) is an inevitable operation to obtain the precoders in practical massive multiple-input multiple-output (MIMO) systems. Due to the large antenna size and at finite computation resources at the base station (BS), the overwhelming computation complexity of EVD is one of the key limiting factors of the system performance. To address this problem, we propose an eigenvector prediction (EGVP) method by interpolating the precoding matrix with predicted eigenvectors. The basic idea is to exploit a few historical precoders to interpolate the rest of them without EVD of the channel state information (CSI). We transform the nonlinear EVD into a linear prediction problem and prove that the prediction of the eigenvectors can be achieved with a complex exponential model. Furthermore, a channel prediction method called fast matrix pencil prediction (FMPP) is proposed to cope with the CSI delay when applying the EGVP method in mobility environments. The asymptotic analysis demonstrates how many samples are needed to achieve asymptotically error-free eigenvector predictions and channel predictions. Finally, the simulation results demonstrate the spectral efficiency improvement of our scheme over the benchmarks and the robustness to different mobility scenarios.Comment: 13pages, 7 figures, 1 table, journa

A Multi-Dimensional Matrix Pencil-Based Channel Prediction Method for Massive MIMO with Mobility

This paper addresses the mobility problem in massive multiple-input multiple-output systems, which leads to significant performance losses in the practical deployment of the fifth generation mobile communication networks. We propose a novel channel prediction method based on multi-dimensional matrix pencil (MDMP), which estimates the path parameters by exploiting the angular-frequency-domain and angular-time-domain structures of the wideband channel. The MDMP method also entails a novel path pairing scheme to pair the delay and Doppler, based on the super-resolution property of the angle estimation. Our method is able to deal with the realistic constraint of time-varying path delays introduced by user movements, which has not been considered so far in the literature. We prove theoretically that in the scenario with time-varying path delays, the prediction error converges to zero with the increasing number of the base station (BS) antennas, providing that only two arbitrary channel samples are known. We also derive a lower-bound of the number of the BS antennas to achieve a satisfactory performance. Simulation results under the industrial channel model of 3GPP demonstrate that our proposed MDMP method approaches the performance of the stationary scenario even when the users' velocity reaches 120 km/h and the latency of the channel state information is as large as 16 ms

A Partial Reciprocity-based Channel Prediction Framework for FDD Massive MIMO with High Mobility

Massive multiple-input multiple-output (MIMO) is believed to deliver unrepresented spectral efficiency gains for 5G and beyond. However, a practical challenge arises during its commercial deployment, which is known as the ``curse of mobility''. The performance of massive MIMO drops alarmingly when the velocity level of user increases. In this paper, we tackle the problem in frequency division duplex (FDD) massive MIMO with a novel Channel State Information (CSI) acquisition framework. A joint angle-delay-Doppler (JADD) wideband precoder is proposed for channel training. Our idea consists in the exploitation of the partial channel reciprocity of FDD and the angle-delay-Doppler channel structure. More precisely, the base station (BS) estimates the angle-delay-Doppler information of the UL channel based on UL pilots using Matrix Pencil (MP) method. It then computes the wideband JADD precoders according to the extracted parameters. Afterwards, the user estimates and feeds back some scalar coefficients for the BS to reconstruct the predicted DL channel. Asymptotic analysis shows that the CSI prediction error converges to zero when the number of BS antennas and the bandwidth increases. Numerical results with industrial channel model demonstrate that our framework can well adapt to high speed (350 km/h), large CSI delay (10 ms) and channel sample noise.Comment: 9 figures, 15 pages, to appear in IEEE Transactions on Wireless Communication

Multi-scale study of the strength and toughness of carbon nanotube fiber materials

The control mechanisms of the strength and toughness of carbon nanotube (CNT) fibers are revealed by analyzing the load-bearing and deformation characteristics of multi-scale structures in the fiber under tensile loading. A theoretical model is established to investigate the effect of the multi-scale structures on the strength and toughness of CNT fibers. Based on our previous experimental results on tension with in situ micro-Raman monitoring [Li et al., Nanotechnology 22, 2011], the macro- and micro-mechanical behaviors of the fiber are analyzed. The tensile behaviors of the fiber are correlated with the load-bearing and deformation processes involved in the multi-scale structures in the fiber, such as the nanotube bundle and the thread in microscopic scale, and the CNT in nanoscale. The CNT fiber exhibits high strength and toughness simultaneously depending on the multi-scale structure of the material, the differences in the properties between bundles and threads, and the unique interfaces formed by the tabular geometric configuration of double-walled CNTs. A constitutive relationship for CNT fiber materials is developed to provide information on the role of multi-scale structures on the strength and toughness of fibers. Both strength and toughness of CNT fibers can be enhanced by increasing the volume ratio of bundles to threads, the interfacial shear strength, and the interface slippage friction resistive force among the CNTs

Multifunctional Nanocracks in Silicon Nanomembranes by Notch-Assisted Transfer Printing

Manipulating nanocracks to produce various nanodevices has attracted increasing interest. Here, based on the mature transfer printing technique, a novel notch-assisted transfer printing technique was engaged to produce nanocracks by simply introducing notch structures into the transferred nanomembranes. Both experiments and finite element simulations were used to elucidate the probability of nanocrack formation during the transfer process, and the results demonstrated that the geometry of nanomembranes played a key role in concentrating stress and producing nanocracks. We further demonstrated that the obtained nanocrack can be used as a surface-enhanced Raman scattering substrate because of the significant enhancement of electric fields. In addition, the capillary condensation of water molecules in the nanocrack led to an obvious change of resistance, thus providing an opportunity for the crack-based structure to be used as an ultrasensitive humidity sensor. The current approach can be applied to producing nanocracks from multiple materials and will have important applications in the field of nanodevices

Asymmetrically Curved Hyperbolic Metamaterial Structure with Gradient Thicknesses for Enhanced Directional Spontaneous Emission

We demonstrate hyperbolic metamaterials (HMMs) on a curved surface for an efficient outcoupling of nonradiative modes, which lead to an enhanced spontaneous emission. Those high-wavevector plasmonic modes can propagate along the curved structure and emit into the far field, realizing a directional light emission with maximal fluorescent intensity. Detailed simulations disclose a high Purcell factor and a spatial power distribution in the curved HMM, which agrees with the experimental result. Our work presents remarkable enhancing capability in both the Purcell factor and emission intensity, which could suggest a unique structure design in metamaterials for potential application in, e.g., high-speed optical sensing and communications