Hardware emulation of wireless communication fading channels

This dissertation investigates several main challenges to implementing hardware-based wireless fading channel emulators with emphasis on incorporating accurate correlation properties. Multiple-input multiple-output (MIMO) fading channels are usually triply-selective with three types of correlation: temporal correlation, inter-tap correlation, and spatial correlation. The proposed emulators implement the triply-selective fading Channel Impulse Response (CIR) by incorporating the three types of correlation into multiple uncorrelated frequency-flat Rayleigh fading waveforms while meeting real-time requirements for high data-rate, large-sized MIMO, and/or long CIR channels. Specifically, mixed parallel-serial computational structures are implemented for Kronecker products of the correlation matrices, which makes the best tradeoff between computational speed and hardware usage. Five practical fading channel examples are implemented for RF or underwater acoustic MIMO applications. The performance of the hardware emulators are verified with an Altera Field-Programmable Gate Array (FPGA) platform and the results match the software simulators in terms of statistical and correlation properties. The dissertation also contributes to the development of a 2-by-2 MIMO transceiver testbench that is used to measure real-world fading channels. Intensive channel measurements are performed for indoor fixed mobile-to-mobile channels and the estimated CIRs demonstrate the triply-selective correlation properties --Abstract, page iv

Accuracy-Complexity Tradeoff Analysis and Complexity Reduction Methods for Non-Stationary IMT-A MIMO Channel Models

open access journalHigh-mobility wireless communication systems have attracted growing interests in recent years. For the deployment of these systems, one fundamental work is to build accurate and efficient channel models. In high-mobility scenarios, it has been shown that the standardized channel models, e.g., IMT-Advanced (IMT-A) multiple-input multiple-output (MIMO) channel model, provide noticeable longer stationary intervals than measured results and the wide-sense stationary (WSS) assumption may be violated. Thus, the non-stationarity should be introduced to the IMT-A MIMO channel model to mimic the channel characteristics more accurately without losing too much efficiency. In this paper, we analyze and compare the computational complexity of the original WSS and non-stationary IMT-A MIMO channel models. Both the number of real operations and simulation time are used as complexity metrics. Since introducing the nonstationarity to the IMT-A MIMO channel model causes extra computational complexity, some computation reduction methods are proposed to simplify the non-stationary IMT-A MIMO channel model while retaining an acceptable accuracy. Statistical properties including the temporal autocorrelation function, spatial cross-correlation function, and stationary interval are chosen as the accuracy metrics for verifications. It is shown that the tradeoff between the computational complexity and modeling accuracy can be achieved by using these proposed complexity reduction methods

On the Fundamentals of Stochastic Spatial Modeling and Analysis of Wireless Networks and its Impact to Channel Losses

With the rapid evolution of wireless networking, it becomes vital to ensure transmission reliability, enhanced connectivity, and efficient resource utilization. One possible pathway for gaining insight into these critical requirements would be to explore the spatial geometry of the network. However, tractably characterizing the actual position of nodes for large wireless networks (LWNs) is technically unfeasible. Thus, stochastical spatial modeling is commonly considered for emulating the random pattern of mobile users. As a result, the concept of random geometry is gaining attention in the field of cellular systems in order to analytically extract hidden features and properties useful for assessing the performance of networks. Meanwhile, the large-scale fading between interacting nodes is the most fundamental element in radio communications, responsible for weakening the propagation, and thus worsening the service quality. Given the importance of channel losses in general, and the inevitability of random networks in real-life situations, it was then natural to merge these two paradigms together in order to obtain an improved stochastical model for the large-scale fading. Therefore, in exact closed-form notation, we generically derived the large-scale fading distributions between a reference base-station and an arbitrary node for uni-cellular (UCN), multi-cellular (MCN), and Gaussian random network models. In fact, we for the first time provided explicit formulations that considered at once: the lattice profile, the users’ random geometry, the spatial intensity, the effect of the far-field phenomenon, the path-loss behavior, and the stochastic impact of channel scatters. Overall, the results can be useful for analyzing and designing LWNs through the evaluation of performance indicators. Moreover, we conceptualized a straightforward and flexible approach for random spatial inhomogeneity by proposing the area-specific deployment (ASD) principle, which takes into account the clustering tendency of users. In fact, the ASD method has the advantage of achieving a more realistic deployment based on limited planning inputs, while still preserving the stochastic character of users’ position. We then applied this inhomogeneous technique to different circumstances, and thus developed three spatial-level network simulator algorithms for: controlled/uncontrolled UCN, and MCN deployments

Hardware Emulation of Wideband Correlated Multiple-input Multiple-output Fading Channels

A low-complexity hardware emulator is proposed for wideband, correlated, multiple-input multiple-output (MIMO) fading channels. the proposed emulator generates multiple discrete-time channel impulse responses (CIR) at the symbol rate and incorporates three types of correlation functions of the subchannels via Kronecker product: The spatial correlation between transmit or receive elements, temporal correlation due to Doppler shifts, and inter-tap correlation due to multipaths. the Kronecker product is implemented by a novel mixed parallel-serial (mixed P-S) matrix multiplication method to reduce memory storage and to meet the real-time requirement in high data-rate, large MIMO size, or long CIR systems. We present two practical MIMO channel examples implemented on an Altera Stratix III EP3SL150F FPGA DSP development kit: A 2-by-2 MIMO WiMAX channel with a symbol rate of 1.25 million symbols/second and a 2-by-6 MIMO underwater acoustic channel with 100-tap CIR. Both examples meet real-time requirement using only 12?14% of hardware resources of the FPGA. © Springer Science Business Media, LLC 2011

Roadmap on optical security

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Neuromorphic Engineering Editors' Pick 2021

This collection showcases well-received spontaneous articles from the past couple of years, which have been specially handpicked by our Chief Editors, Profs. André van Schaik and Bernabé Linares-Barranco. The work presented here highlights the broad diversity of research performed across the section and aims to put a spotlight on the main areas of interest. All research presented here displays strong advances in theory, experiment, and methodology with applications to compelling problems. This collection aims to further support Frontiers’ strong community by recognizing highly deserving authors