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Signal conversion plays an important role in many applications such as communication, sensing, and imaging. Realizing signal conversion between optical and microwave frequencies is a crucial step to construct hybrid communication systems that combine both optical and microwave wireless technologies to achieve better features, which are highly desirable in the future wireless communications. However, such a signal conversion process typically requires a complicated relay to perform multiple operations, which will consume additional hardware/time/energy resources. Here, we report a light-to-microwave transmitter based on the time-varying and programmable metasurface integrated with a high-speed photoelectric detection circuit into a hybrid. Such a transmitter can convert a light intensity signal to two microwave binary frequency shift keying signals by using the dispersion characteristics of the metasurface to implement the frequency division multiplexing. To illustrate the metasurface-based transmitter, a hybrid wireless communication system that allows dual-channel data transmissions in a light-to-microwave link is demonstrated, and the experimental results show that two different videos can be transmitted and received simultaneously and independently. Our metasurface-enabled signal conversion solution may enrich the functionalities of metasurfaces, and could also stimulate new information-oriented applications.A metasurface-based light-to-microwave transmitter, which can convert a light intensity signal to two microwave signals directly, was proposed to achieve the dual-channel data transmissions in light-to-microwave hybrid wireless communications.

The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

The growth of connected intelligent devices in the Internet of Things has created a pressing need for real-time processing and understanding of large volumes of analogue data. The difficulty in boosting the computing speed renders digital computing unable to meet the demand for processing analogue information that is intrinsically continuous in magnitude and time. By utilizing a continuous data representation in a nanoscale crossbar array, parallel computing can be implemented for the direct processing of analogue information in real time. Here, we propose a scalable massively parallel computing scheme by exploiting a continuous-time data representation and frequency multiplexing in a nanoscale crossbar array. This computing scheme enables the parallel reading of stored data and the one-shot operation of matrix–matrix multiplications in the crossbar array. Furthermore, we achieve the one-shot recognition of 16 letter images based on two physically interconnected crossbar arrays and demonstrate that the processing and modulation of analogue information can be simultaneously performed in a memristive crossbar array.Continuous-time data representation and frequency multiplexing enable the implementation of a scalable massively parallel computing scheme in a nanoscale crossbar array for applications in intelligent edge devices.

The accuracy of channel state information (CSI) acquisition directly affects the performance of millimeter wave (mmWave) communications. In this article, we provide an overview on CSI acquisition, including beam training and channel estimation for mmWave massive multiple-input multiple-output systems. The beam training can avoid the estimation of a high-dimension channel matrix, while the channel estimation can flexibly exploit advanced signal processing techniques. In addition to introducing the traditional and machine learning-based approaches in this article, we also compare different approaches in terms of spectral efficiency, computational complexity, and overhead.

Optical wireless communication (OWC) stands out as one of the most promising technologies in the sixth-generation (6G) mobile networks. The establishment of high-quality optical links between transmitters and receivers plays a crucial role in OWC performances. Here, by a compact beam splitter composed of a metasurface and a fiber array, we proposed a wide-angle (~120°) OWC optical link scheme that can parallelly support up to 144 communication users. Utilizing high-speed optical module sources and wavelength division multiplexing technique, we demonstrated each user can achieve a communication speed of 200 Gbps which enables the entire system to support ultra-high communication capacity exceeding 28 Tbps. Furthermore, utilizing the metasurface polarization multiplexing, we implemented a full range wide-angle OWC without blind area nor crosstalk among users. Our OWC scheme simultaneously possesses the advantages of high-speed, wide communication area and multi-user parallel communications, paving the way for revolutionary high-performance OWC in the future. In this work, the authors present a metasurface-based wide-angle beam splitter designed for future applications in optical wireless communication. By leveraging the metasurface polarization multiplexing and wavelength division multiplexing properties, they achieved a high-performance optical wireless communication system, possessing a Tbps communication rate, more than 120° coverage range, and up to 144 users parallel communication capabilities.

Microwave-optical interaction and its effective utilization are vital technologies at the frontier of classical and quantum sciences for communication, sensing, and imaging. Typically, state-of-the-art microwave-to-optical converters are realized by fiber and circuit approaches with multiple processing steps, and external powers are necessary, which leads to many limitations. Here, we propose a programmable metasurface that can achieve direct and high-speed free-space microwave-to-laser conversion. Moreover, it supports reverse conversion, achieving bidirectional operations. The programmable metasurface converter is realized by integrating subwavelength microwave resonant structures, MS junction and photoelectric PN junction components together, without connecting any direct-current supplies to provide driving bias. We further demonstrate the enormous potentials of the metasurface converter in cross-media links and develop a full-duplex air-water wireless communication system. Experimental results show that the bidirectional real-time data transmissions and exchanges are established through the air-water boundary. This work represents a decisive step towards microwave-optical interconversion on wireless and battery-free interfaces. Realizing conversion between microwave and optical signals in free space is a challenge. Here, the authors propose and demonstrate a programmable metasurface that can achieve wireless microwave-laser interconversion for bidirectional air-water cross-media wireless communications.

Intelligent reflecting surface (IRS) is a new concept originating from metamaterials, which can achieve beamforming through controllable passive reflecting. This device makes it possible to engineer the wireless communication environment, and has drawn increasing attention. However, the associated channel models in current literature are mainly borrowed from conventional wireless channel models directly, omitting the unique features of IRS. In this paper, a geometry‐based stochastic channel model for IRS‐assisted wireless communication system is employed. The model has certain accuracy and low computational complexity. In particular, it captures the correlations of subchannels associated with different IRS elements, which is typically not considered in current works. Based on this channel model and the derived channel spatial correlation functions (CFs), an iterative reflection coefficients configuration method is proposed exploiting statistical channel state information to maximise the ergodic channel capacity. The impacts of the IRS spatial positions as well as the number of the IRS elements on the ergodic channel capacity is investigated through simulations. It is found that to obtain a larger ergodic channel capacity, the IRS should be placed in the vicinity of either the transmitter side or the receiver side, which is a useful guideline for practical deployment.

Low earth orbit constellation satellite communication has the characteristics of low propagation delay, low path loss, low launch cost and wide range of applications. Due to the low orbital altitude and the short orbital period of low earth orbit satellites, the relative position between satellites and gateway stations changes fast. As a result, the links between gateway stations and satellites need to be switched continuously. Based on the minimum handover frequency algorithm, this paper considers the balance of satellite workloads, and proposes a load balanced satellite handover strategy. In the proposed handover strategy, a joint optimization algorithm is employed, and the power allocation of the satellite is optimized to improve the system capacity. In the multi‐satellite connection model, an adaptive power allocation algorithm is proposed to guarantee the service quality of the system. Simulation results demonstrate the efficiency of the proposed satellite handover strategy.

In this journal, we investigate the beam-domain channel estimation and power allocation in hybrid architecture massive multiple-input and multiple-output (MIMO) communication systems. First, we propose a low-complexity channel estimation method, which utilizes the beam steering vectors achieved from the direction-of-arrival (DOA) estimation and beam gains estimated by low-overhead pilots. Based on the estimated beam information, a purely analog precoding strategy is also designed. Then, the optimal power allocation among multiple beams is derived to maximize spectral efficiency. Finally, simulation results show that the proposed schemes can achieve high channel estimation accuracy and spectral efficiency.

In this paper, it is presented a methodology for implementing arbitrarily constructed time-homogenous Markov chains with biochemical systems. Not only discrete but also continuous-time Markov chains are allowed to be computed. By employing chemical reaction networks as a programmable language, molecular concentrations serve to denote both input and output values. One reaction network is elaborately designed for each chain. The evolution of species’ concentrations over time well matches the transient solutions of the target continuous-time Markov chain, while equilibrium concentrations can indicate the steady state probabilities. Additionally, second-order Markov chains are considered for implementation, with bimolecular reactions rather than unary ones. An original scheme is put forward to compile unimolecular systems to DNA strand displacement reactions for the sake of future physical implementations. Deterministic, stochastic and DNA simulations are provided to enhance correctness, validity and feasibility.