This paper presents 3-D vehicle massive multiple-input multiple-output (MIMO) antenna array model for vehicle-to-vehicle (V2V) communication environments. A spherical wavefront is assumed in the ...proposed model instead of the plane wavefront assumption used in the conventional MIMO channel model. Using the proposed V2V channel model, we first derive the closed-form expressions for the joint and marginal probability density functions of the angle of departure at the transmitter and angle of arrival at the receiver in the azimuth and elevation planes. We additionally analyze the time and frequency cross-correlation functions for different propagation paths. In the proposed model, we derive the expression of the Doppler spectrum due to the relative motion between the mobile transmitter and mobile receiver. The results show that the proposed 3-D channel model is in close agreement with previously reported results, thereby validating the generalization of the proposed model.
A major limitation of existing visible light communication (VLC) systems is the limited modulation bandwidth of light-emitting diodes used in such systems. Using adaptive modulation to improve the ...spectral efficiency for radio communications has been well studied. For VLC with various physical layer schemes, however, how adaptive modulation works is not well understood yet. The goal of this paper is to provide an in-depth analysis of the achievable spectral efficiency of adaptive modulation for three different schemes for high speed VLC: dc-biased optical orthogonal frequency division multiplexing (DCO-OFDM), asymmetrically clipped optical OFDM (ACO-OFDM), and single-carrier frequency-domain equalization (SC-FDE). We will show that in the low signal-to-noise ratio region, the ACO-OFDM-based adaptive modulation scheme outperforms the other two schemes. SC-FDE-based adaptive modulation achieves a better performance than the DCO-OFDM-based scheme, and it is much simpler than the other two schemes.
Selecting an appropriate direct current (dc) bias is crucial to obtain positive and low-peak-to-average-power-ratio electrical signals in the dc optical orthogonal frequency-division multiplexing ...(DCO-OFDM) system. In this letter, our goal is to propose an optimization strategy of dc bias under given lower and upper clipping bounds. We characterize the mean square error between the original signals and the clipped ones as the metric of clipping distortion. Finding the optimum dc bias can be formulated as a nonconvex optimization problem. However, the optimum dc bias can be obtained from a numerical method. The simulation results show that the bit error ratio performance can be improved when employing the optimum dc bias obtained by the proposed numerical method.
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.
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.
Convolutional neural networks (CNNs) have gained great success in various fields, such as computer vision and natural language processing. Besides, with the breakthrough in unsupervised learning, ...generative adversarial network (GAN) is recently utilized to generate virtual data from limited data sets. The generative model of GAN has impressive applications, such as style transfer and image super-resolution. However, the promising performance of CNN and GAN comes at the cost of prohibitive computation complexity. The convolution (CONV) in CNN and the transposed CONV (TCONV) in GAN are the two operations that dominant the overall complexity. The prior works exploit the fast algorithms, Winograd and fast Fourier transform (FFT), to reduce the complexity of spatial CONV. However, Winograd only supports fixed filter size while FFT has high transform overhead. Moreover, very few works apply fast algorithms to accelerate GAN models. In this article, a reconfigurable and low-complexity accelerator on ASIC for both CNN and GAN is proposed to address these problems. First, by exploiting Fermat number transform (FNT), we propose two FNT-based fast algorithms to reduce the complexity of CONV and TCONV computations, respectively. Then the architectures of the FNT-based accelerator are presented to implement the proposed fast algorithms. The methodology to determine the design parameters and optimize the dataflow is also described for obtaining maximum performance and optimal efficiency. Moreover, we implement the proposed accelerator on 65 nm 1P9M technology and evaluate it on various CNN and GAN models. The post-layout results show that our design achieves a throughput of 288.0 GOP/s on VGG-16 with 25.11 GOP/s/mm 2 area efficiency, which is superior to the state-of-the-art CNN accelerators. Furthermore, at least <inline-formula> <tex-math notation="LaTeX">1.7\times </tex-math></inline-formula> speedup over the existing accelerators is obtained on GAN. The resulting energy efficiency is <inline-formula> <tex-math notation="LaTeX">275.3\times </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">12.5\times </tex-math></inline-formula> of CPU and GPU.
In this paper, we propose a novel three-dimensional multiple-input multiple-output channel model to describe the air-to-ground (A2G) communication environments. The model introduces the unmanned ...aerial vehicle (UAV) transmitter and ground mobile receiver (MR) located at the foci points of the boundary ellipsoid, while different ellipsoids represent the propagation properties for different time delays. In light of this, we are able to investigate the propagation properties of the A2G channel model for different time delays. Furthermore, the time-varying parameters of the azimuth angle of departure, the elevation angle of departure, the azimuth angle of arrival, and elevation angle of arrival are derived to properly describe the channel non-stationarity, which is caused by the motion of the UAV transmitter, cluster, and MR. The impacts of the movement properties of the cluster in both the azimuth and elevation planes are investigated on the channel characteristics, i.e., spatial cross-correlation functions, temporal autocorrelation functions, Doppler power spectrum density, and power delay profiles.
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.
Universal filtered multi-carrier (UFMC) is a potential waveform technology, which can efficiently combat different carrier frequency offsets (CFOs) of multiple users. First, adaptive modulation and ...power allocation are applied for each subcarrier to meet a preset bit error rate (BER) requirement by ignoring CFOs. Then, we prove that different CFOs will cause different interference variances to adjacent users, which results in performance degradation in UFMC systems. To reduce the interference caused by CFOs and improve achievable rate, a novel adaptive filter configuration algorithm is proposed to adaptively design the parameters of the finite impulse response filters. Specifically, the proposed algorithm is available for the UFMC systems, where the user equipments are allocated with different bandwidths. Finally, simulation results show that the proposed adaptive filter configuration algorithm can dramatically eliminate the interference caused by different CFOs, and achieve better BER performance and a higher achievable rate than the conventional scheme.
This paper presents a generalized visual scattering channel model for car-to-car (C2C) mobile radio environments, in which an asymmetric directional antenna is deployed at the mobile transmitter ...(MT). The signals received at the mobile receiver (MR) from the MT are assumed to experience multibounced propagation paths. More importantly, the proposed model first separates the multibounced propagation paths into odd- and even-numbered-bounced propagation conditions. General formulations of the marginal probability density functions (pdfs) of the angle of departure (AoD) at the transmitter and the angle of arrival (AoA) at the receiver have been derived for the given two conditions, respectively. From the proposed model, we derive an expression for the Doppler frequency due to the relative motion between the MT and the MR, which broadens the research of the proposed visual street scattering channel model. The results show that the proposed model can fit those of the previous scattering channel models and the measurement results for dense urban street environments very well, which validate the generalization of the proposed virtual street channel model.
PDF
