Classification and comparison of massive MIMO propagation channel models

Considering great benefits brought by massive multiple-input multiple-output (MIMO) technologies in Internet of things (IoT), it is of vital importance to analyze new massive MIMO channel characteristics and develop corresponding channel models. In the literature, various massive MIMO channel models have been proposed and classified with different but confusing methods, i.e., physical vs. analytical method and deterministic vs. stochastic method. To have a better understanding and usage of massive MIMO channel models, this work summarizes different classification methods and presents an up-to-date unified classification framework, i.e., artificial intelligence (AI)-based predictive channel models and classical non-predictive channel models, which further clarify and combine the deterministic vs. stochastic and physical vs. analytical methods. Furthermore, massive MIMO channel measurement campaigns are reviewed to summarize new massive MIMO channel characteristics. Recent advances in massive MIMO channel modeling are surveyed. In addition, typical non-predictive massive MIMO channel models are elaborated and compared, i.e., deterministic models and stochastic models, which include correlation-based stochastic model (CBSM), geometry-based stochastic model (GBSM), and beam domain channel model (BDCM). Finally, future challenges in massive MIMO channel modeling are given

Pervasive wireless channel modeling theory and applications to 6G GBSMs for all frequency bands and all scenarios

In this paper, a pervasive wireless channel modeling theory is first proposed, which uses a unified channel modeling method and a unified equation of channel impulse response (CIR), and can integrate important channel characteristics at different frequency bands and scenarios. Then, we apply the proposed theory to a three dimensional (3D) space-time-frequency (STF) non-stationary geometry-based stochastic model (GBSM) for the sixth generation (6G) wireless communication systems. The proposed 6G pervasive channel model (6GPCM) can characterize statistical properties of channels at all frequency bands from sub-6 GHz to visible light communication (VLC) bands and all scenarios such as unmanned aerial vehicle (UAV), maritime, (ultra-)massive multiple-input multiple-output (MIMO), reconfigurable intelligent surface (RIS), and industry Internet of things (IIoT) scenarios. By adjusting channel model parameters, the 6GPCM can be reduced to various simplified channel models for specific frequency bands and scenarios. Also, it includes standard fifth generation (5G) channel models as special cases. In addition, key statistical properties of the proposed 6GPCM are derived, simulated, and verified by various channel measurement results, which clearly demonstrates its accuracy, pervasiveness, and applicability

A novel 3D non-stationary channel model for 6G indoor visible light communication systems

The visible light communication (VLC) technology has attracted much attention in the research of the sixth generation (6G) communication systems. In this paper, a novel three dimensional (3D) space-time-frequency non-stationary geometry-based stochastic model (GBSM) is proposed for indoor VLC channels. The proposed VLC GBSM can capture unique indoor VLC channel characteristics such as the space-time-frequency non-stationarity caused by large light-emitting diode (LED) arrays in indoor scenarios, long travelling paths, and large bandwidths of visible light waves, respectively. In addition, the proposed model can support special radiation patterns of LEDs, 3D translational and rotational motions of the optical receiver (Rx), and can be applied to angle diversity receivers (ADRs). Key channel properties are simulated and analyzed, including the space-time-frequency correlation function (STFCF), received power, root mean square (RMS) delay spread, and path loss (PL). Simulation results verify the space-time-frequency non-stationarity in indoor VLC channels. In addition, the influence of light source radiation patterns, receiver rotations, and ADRs on channel characteristics have been investigated. Finally, the accuracy and practicality of the proposed model are validated by comparing the simulation result of channel 3dB bandwidth with the existing measurement data. The proposed channel model will play a supporting role in the design of future 6G VLC systems

Ondas milimétricas e MIMO massivo para otimização da capacidade e cobertura de redes heterogeneas de 5G

Today's Long Term Evolution Advanced (LTE-A) networks cannot support the exponential growth in mobile traffic forecast for the next decade. By 2020, according to Ericsson, 6 billion mobile subscribers worldwide are projected to generate 46 exabytes of mobile data traffic monthly from 24 billion connected devices, smartphones and short-range Internet of Things (IoT) devices being the key prosumers. In response, 5G networks are foreseen to markedly outperform legacy 4G systems. Triggered by the International Telecommunication Union (ITU) under the IMT-2020 network initiative, 5G will support three broad categories of use cases: enhanced mobile broadband (eMBB) for multi-Gbps data rate applications; ultra-reliable and low latency communications (URLLC) for critical scenarios; and massive machine type communications (mMTC) for massive connectivity. Among the several technology enablers being explored for 5G, millimeter-wave (mmWave) communication, massive MIMO antenna arrays and ultra-dense small cell networks (UDNs) feature as the dominant technologies. These technologies in synergy are anticipated to provide the 1000_ capacity increase for 5G networks (relative to 4G) through the combined impact of large additional bandwidth, spectral efficiency (SE) enhancement and high frequency reuse, respectively. However, although these technologies can pave the way towards gigabit wireless, there are still several challenges to solve in terms of how we can fully harness the available bandwidth efficiently through appropriate beamforming and channel modeling approaches. In this thesis, we investigate the system performance enhancements realizable with mmWave massive MIMO in 5G UDN and cellular infrastructure-to-everything (C-I2X) application scenarios involving pedestrian and vehicular users. As a critical component of the system-level simulation approach adopted in this thesis, we implemented 3D channel models for the accurate characterization of the wireless channels in these scenarios and for realistic performance evaluation. To address the hardware cost, complexity and power consumption of the massive MIMO architectures, we propose a novel generalized framework for hybrid beamforming (HBF) array structures. The generalized model reveals the opportunities that can be harnessed with the overlapped subarray structures for a balanced trade-o_ between SE and energy efficiently (EE) of 5G networks. The key results in this investigation show that mmWave massive MIMO can deliver multi-Gbps rates for 5G whilst maintaining energy-efficient operation of the network.As redes LTE-A atuais não são capazes de suportar o crescimento exponencial de tráfego que está previsto para a próxima década. De acordo com a previsão da Ericsson, espera-se que em 2020, a nível global, 6 mil milhões de subscritores venham a gerar mensalmente 46 exa bytes de tráfego de dados a partir de 24 mil milhões de dispositivos ligados à rede móvel, sendo os telefones inteligentes e dispositivos IoT de curto alcance os principais responsáveis por tal nível de tráfego. Em resposta a esta exigência, espera-se que as redes de 5a geração (5G) tenham um desempenho substancialmente superior às redes de 4a geração (4G) atuais. Desencadeado pelo UIT (União Internacional das Telecomunicações) no âmbito da iniciativa IMT-2020, o 5G irá suportar três grandes tipos de utilizações: banda larga móvel capaz de suportar aplicações com débitos na ordem de vários Gbps; comunicações de baixa latência e alta fiabilidade indispensáveis em cenários de emergência; comunicações massivas máquina-a-máquina para conectividade generalizada. Entre as várias tecnologias capacitadoras que estão a ser exploradas pelo 5G, as comunicações através de ondas milimétricas, os agregados MIMO massivo e as redes celulares ultradensas (RUD) apresentam-se como sendo as tecnologias fundamentais. Antecipa-se que o conjunto destas tecnologias venha a fornecer às redes 5G um aumento de capacidade de 1000x através da utilização de maiores larguras de banda, melhoria da eficiência espectral, e elevada reutilização de frequências respetivamente. Embora estas tecnologias possam abrir caminho para as redes sem fios com débitos na ordem dos gigabits, existem ainda vários desafios que têm que ser resolvidos para que seja possível aproveitar totalmente a largura de banda disponível de maneira eficiente utilizando abordagens de formatação de feixe e de modelação de canal adequadas. Nesta tese investigamos a melhoria de desempenho do sistema conseguida através da utilização de ondas milimétricas e agregados MIMO massivo em cenários de redes celulares ultradensas de 5a geração e em cenários 'infraestrutura celular-para-qualquer coisa' (do inglês: cellular infrastructure-to-everything) envolvendo utilizadores pedestres e veiculares. Como um componente fundamental das simulações de sistema utilizadas nesta tese é o canal de propagação, implementamos modelos de canal tridimensional (3D) para caracterizar de forma precisa o canal de propagação nestes cenários e assim conseguir uma avaliação de desempenho mais condizente com a realidade. Para resolver os problemas associados ao custo do equipamento, complexidade e consumo de energia das arquiteturas MIMO massivo, propomos um modelo inovador de agregados com formatação de feixe híbrida. Este modelo genérico revela as oportunidades que podem ser aproveitadas através da sobreposição de sub-agregados no sentido de obter um compromisso equilibrado entre eficiência espectral (ES) e eficiência energética (EE) nas redes 5G. Os principais resultados desta investigação mostram que a utilização conjunta de ondas milimétricas e de agregados MIMO massivo possibilita a obtenção, em simultâneo, de taxas de transmissão na ordem de vários Gbps e a operação de rede de forma energeticamente eficiente.Programa Doutoral em Telecomunicaçõe

A Statistical MIMO Channel Model for Reconfigurable Intelligent Surface Assisted Wireless Communications

Reconfigurable intelligent surface (RIS) consisting of a large number of programmable near-passive units has been a hot topic in wireless communications due to its capability in providing smart radio environments to enhance the communication performance. However, the existing research are mainly based on simplistic channel models, which will, in principle, lead to inaccurate analysis of the system performance. In this paper, we propose a general three-dimensional (3D) wideband non-stationary end-to-end channel model for RIS assisted multiple-input multiple-output (MIMO) communications, which takes into account the physical properties of RIS, such as unit numbers, unit sizes, array orientations and array configurations. By modeling the RIS by a virtual cluster, we describe the end-to-end channel by a superposition of virtual line-of-sight (V-LoS), single-bounced non-LoS (SB-NLoS), and double-bounced NLoS (DB-NLoS) components. We also derive an equivalent cascaded channel model and show the equivalence between end-to-end and cascaded modeling of RIS channels. Then, a sub-optimal solution with low complexity is used to derive the RIS reflection phases. The impact of physical properties of RIS, such as unit numbers, unit sizes, array orientations, array configurations and array relative locations, on channel statistical characteristics has been investigated and analyzed, the results demonstrate that the proposed model is helpful for characterizing the RIS-assisted communication channels

Channel Measurement and Characterization with Modified SAGE Algorithm in an Indoor Corridor at 300 GHz

The much higher frequencies in the Terahertz (THz) band prevent the effective utilization of channel models dedicated for microwave or millimeter-wave frequency bands. In this paper, a measurement campaign is conducted in an indoor corridor scenario at 306-321 GHz with a frequency-domain Vector Network Analyzer (VNA)-based sounder. To realize high-resolution multipath component (MPC) extraction for the direction-scan measurement campaigns in the THz band, a novel modified space-alternating generalized expectation-maximization (SAGE) algorithm is further proposed. Moreover, critical channel characteristics, including the path loss, shadow fading, K-factor, delay spread, angular spreads, cluster parameters, and cross correlations are calculated and analyzed in the LoS case. Besides, two contrasted measurement campaigns in the NLoS case are conducted, with and without additional reflective foils on walls to serve as effective scatterers. Comparison results indicate that the reflective foils are useful to improve the channel conditions in the NLoS case by nearly 6 dB, which is potential to be utilized as alternative of intelligent reflecting surfaces (IRS) to enhance the coverage ability of THz communications.Comment: 12 pages, 8 figure