Massive MIMO Channel Models: A Survey

The exponential traffic growth of wireless communication networks gives rise to both the insufficient network capacity and excessive carbon emissions. Massive multiple-input multiple-output (MIMO) can improve the spectrum efficiency (SE) together with the energy efficiency (EE) and has been regarded as a promising technique for the next generation wireless communication networks. Channel model reflects the propagation characteristics of signals in radio environments and is very essential for evaluating the performances of wireless communication systems. The purpose of this paper is to investigate the state of the art in channel models of massive MIMO. First, the antenna array configurations are presented and classified, which directly affect the channel models and system performance. Then, measurement results are given in order to reflect the main properties of massive MIMO channels. Based on these properties, the channel models of massive MIMO are studied with different antenna array configurations, which can be used for both theoretical analysis and practical evaluation

Alzheimer's Disease Detection from Spontaneous Speech through Combining Linguistic Complexity and (Dis)Fluency Features with Pretrained Language Models

In this paper, we combined linguistic complexity and (dis)fluency features with pretrained language models for the task of Alzheimer's disease detection of the 2021 ADReSSo (Alzheimer's Dementia Recognition through Spontaneous Speech) challenge. An accuracy of 83.1% was achieved on the test set, which amounts to an improvement of 4.23% over the baseline model. Our best-performing model that integrated component models using a stacking ensemble technique performed equally well on cross-validation and test data, indicating that it is robust against overfitting.Comment: accepted at Interspeech202

Measurement-Based Characterization of 39 GHz Millimeter-Wave Dual-Polarized Channel Under Foliage Loss Impact

This paper presents a measurement-based analysis of wideband 39 GHz millimeter wave (mm-wave) dual-polarized propagation channel under the impact of foliage presence between a transmitter (Tx) and a receiver (Rx). The measurements were conducted in a rich-vegetation area, and the so-called direction-scan-sounding (DSS) method which rotates a horn antenna in angular domains was applied, aiming at investigating the direction-of-arrival (DoA)-dependent characteristics of polarimetric channels. Four Tx-to-Rx polarization configurations were considered, including co-polarization scenarios with vertical Tx-polarization to vertical Rx-polarization (VV) and horizontal to horizontal (HH), as well as cross-polarization with vertical to horizontal (VH) and horizontal to vertical (HV), which allow scrutinizing the differences in delay-direction dispersion for usually-encountered scenarios. A foliage loss model for various vegetation depths in VV polarization configuration, was also presented in this paper. The results show that the foliage-loss DoA spectra for VH and HV are similar, while the spectra exhibit less penetration loss in most directions for VV than for the HH. Furthermore, the presence of vegetation between the Tx and the Rx leads to larger dispersion in delay compared to the clear line-of-sight (LoS) scenario, particularly for vertical polarization in the Tx side, and additionally, the foliage presence also results in evident DoA dispersion, specially in the HV scenario. Selectivity in directions caused by foliage is more significant in vertically-polarized Tx scenarios than in the horizontally-polarized Tx scenarios. A statistical model is established summarizing these comparison details

An Empirical Air-to-Ground Channel Model Based on Passive Measurements in LTE

In this paper, a recently conducted measurement campaign for unmanned-aerial-vehicle (UAV) channels is introduced. The downlink signals of an in-service long-time-evolution (LTE) network which is deployed in a suburban scenario were acquired. Five horizontal and five vertical flight routes were considered. The channel impulse responses (CIRs) are extracted from the received data by exploiting the cell specific signals (CRSs). Based on the CIRs, the parameters of multipath components (MPCs) are estimated by using a high-resolution algorithm derived according to the space-alternating generalized expectation-maximization (SAGE) principle. Based on the SAGE results, channel characteristics including the path loss, shadow fading, fast fading, delay spread and Doppler frequency spread are thoroughly investigated for different heights and horizontal distances, which constitute a stochastic model.Comment: 15 pages, submitted version to IEEE Transactions on Vehicular Technology. Current status: Early acces