Experimental study of depolarization and antenna correlation in tunnels in the 1.3 GHz band

Measurements have been carried out in a low-traffic road tunnel to investigate the influence of the polarization of the transmitting and receiving antennas on the channel characteristics. A real-time channel sounder working in a frequency band around 1.3 GHz has been used, the elements of the transmitting and receiving arrays being dual-polarized patch antennas. Special emphasis is made on cross-polarization discrimination factor and on the spatial correlation between array elements which has a great influence on the performances of transmit/receive diversity schemes. Various polarizations both at the transmitter and the receiver have been tested to minimize this spatial correlation while keeping the size of the array as small as possible

Impact of polarization diversity in massive MIMO for industry 4.0

The massive polarimetric radio channel is evaluated in an indoor industrial scenario at 3.5 GHz using a 10×10 uniform rectangular array (URA). The analysis is based on (1) propagation characteristics like the average received gain and the power to interference ratio from the Gram matrix and (2) system-oriented metrics such as sum-rate capacity with maximum-ratio transmitter (MRT). The results clearly show the impact of polarization diversity in an industrial scenario and how it can considerably improve different aspects of the system design. Results for sum-rate capacity are promising and show that the extra degree of freedom, provided by polarization diversity, can optimize the performance of a very simple precoder, the MRT

Channel correlation-based approach for feedback overhead reduction in massive MIMO

For frequency-division duplex multiple-input-multiple-output (MIMO) systems, the channel state information at the transmitter is usually obtained by sending pilots or reference signals from all elements of the antenna array. The channel is then estimated by the receiver and communicated back to the transmitter. However, for massive MIMO, this periodical estimation of the full transfer matrix can lead to prohibitive overhead. To reduce the amount of data, we propose to estimate the updated channel matrix from the knowledge of the full correlation matrix at the transmitter made during some initialization time and the instantaneous measured channel matrix of smaller size, characterizing the link between the user and a limited number of reference array elements. The proposed algorithm is validated with measured massive MIMO channel transfer functions at 3.5GHz between a $9 \times 9$ uniform rectangular array and different user positions. Since measurements were made in static conditions, the criteria chosen for evaluating the performance of the algorithm are based on a comparison of the predicted channel capacity calculated from either the measured or estimated channel matrix

Hybrid virtual polarimetric massive MIMO measurements at 1.35 GHz

The polarimetric massive multiple-input multiple-output (MIMO) radio channel of an indoor line-of-sight scenario is investigated at 1.35 GHz using a real-time radio channel sounder. The 8 x 12 massive MIMO transmitter is constructed using a hybrid architecture including a vertical uniform linear array translated at different horizontal positions forming a virtual, yet realistic, uniform rectangular array. The performance of the system is evaluated with six users distributed in the room for different polarisation schemes and receiver orientations using propagation channel-based metrics (such as receiver spatial correlation and Rician factor) and system-oriented metrics such as sum-rate capacity and signal to interference and noise ratio. The results show a clear dependence of the performance to the polarisation schemes and receiver orientation and showing that when facing the array, cross-polarisation can be very beneficial. Furthermore, it is concluded that the additional degree of freedom brought by the polarisation diversity can contribute to improve spectral efficiency (similar to 20% depending on the configuration), paving the way for further capacity enhancements in massive MIMO systems. It was also found that the receiver spatial correlation can be modelled using a Burr distribution

Stationarity analysis of V2I radio channel in a suburban environment

Due to rapid changes in the environment, vehicular communication channels no longer satisfy the assumption of wide-sense stationary uncorrelated scattering. The non-stationary fading process can be characterized by assuming local stationarity regionswith finite extent in time and frequency. The local scattering function (LSF) and channel correlation function (CCF) provide a framework to characterize the mean power and correlation of the non-stationary channel scatterers, respectively. In this paper, we estimate the LSF and CCF from measurements collected in a vehicle-to-infrastructure radio channel sounding campaign in a suburban environment in Lille, France. Based on the CCF, the stationarity region is evaluated in time as 567 ms and used to capture the non-stationary fading parameters. We obtain the time-varying delay and Doppler power profiles fromthe LSF, and we analyze the corresponding root-mean-square delay and Doppler spreads. We show that the distribution of these parameters follows a lognormal model. Finally, application relevance in terms of channel capacity and diversity techniques is discussed. Results show that the assumption of ergodic capacity and the performance of various diversity techniques depend on the stationarity and coherence parameters of the channel. The evaluation and statistical modeling of such parameters can provide away of tracking channel variation, hence, increasing the performance of adaptive schemes

Experimental characterization of non-stationary V2I radio channel in tunnels

The fading process in vehicular communications is inherently non-stationary. In this paper, vehicle-to-infrastructure (V2I) radio channel measurements are performed inside a tunnel for low and medium traffic conditions to estimate the stationarity time, in addition to the time-varying RMS delay and Doppler spreads. Furthermore, we show the good fit of the spreads to a lognormal distribution, as well as for the Rician K-factor of the fading amplitude. From our analysis we conclude that the traffic density has an impact on the large-scale parameters as it increases delay and Doppler spreads, while reducing the correlation between them as well as the average K-factor. Larger traffic densities may be required to impact the stationarity time

Experimental study on the impact of antenna characteristics on non-stationary V2I channel parameters in tunnels

This paper analyses the experimentally-assessed dual-polarized (DP) mobile channel in a tunnel environment at 1.35 GHz under traffic conditions. We investigate the impact of antenna polarization and radiation pattern on the non-stationary vehicle-to-infrastructure (V2I) channel. Basic channel evaluation metrics are examined including path gain, co-polarization ratio (CPR), and cross-polarization discrimination (XPD). In addition, the stationarity region is estimated using the channel correlation function approach, and used to calculate the time-varying delay and Doppler power profiles. Statistical models are presented for parameters like CPR, XPD, RMS delay and Doppler spreads, where the lognormal distribution provides the best fit. The polarization and the opening angle of the antennas into the propagation channel are found to strongly influence the observed non-stationarity of the channel. They impact the degree of multipath richness that is captured, thus providing different path gain, delay and Doppler spreads. Based on our analysis, the directional antenna with vertical polarization provides the longest stationarity time of 400 ms at 90 km/h, as well as the highest path gain and lowest dispersion. Furthermore, the DP channel capacity is calculated and its dependence on different normalization approaches is investigated. We propose a more accurate normalization for the DP channels that takes the conservation of energy into account. Moreover, the subchannels correlation coefficients are determined. While the condition number is found to be low on average, the correlation results show high correlation among the DP subchannels. As conclusion, we show how the CPR and XPD play the main role in providing multiplexing gain for DP tunnel channels

Massive MIMO communication strategy using polarization diversity for industrial scenarios

International audienc

Autoregressive modeling approach for non-stationary vehicular channel simulation

A framework is proposed for long-term vehicular channel simulation based on the vector time-frequency autoregressive (VTFAR) model for a sparse parametric description of nonstationary multivariate random processes. Based on vehicle-to-infrastructure tunnel measurements, we estimate the VTFAR model parameters and validate the model by comparing the parametric and non-parametric spectra of the measured channel in terms of the delay spread and stationarity time. In addition, the VTFAR model stability is investigated and an approximation for the correlated scattering channel is proposed. The experimental validation shows a good agreement with RMSE of only 0.01 for the delay spread and 0.4 for the stationarity time. This approach provides an efficient alternative for non-stationary channel simulation that is measurement-based and computationally inexpensive

Angular characteristics of multipath propagation in an indoor industrial environment

International audienceThe characteristics of multipath components (MPCs) are addressed in an industrial environment at 1.3 GHz by means of measurements with a multidimensional channel sounder. The maximum likelihood estimator, RiMAX, is used to determine the MPCs parameters and takes into account the diffuse scattering. Both line-of-sight (LOS) and obstructed LOS (OLOS) scenarios have been considered, along with the four polarization states. We found that the environment is very rich in multipath, that is on average, about 120 (resp. 70) MPCs in LOS (resp. OLOS) scenario due to the presence of several metallic reflectors. The azimuthal angle implies clustering of the MPCs, and therefore, the estimated MPCs are grouped in clusters using the K-powers-means algorithm based on the multipath component distance. In general, one to four clusters are determined with three clusters occurring with the highest probability, regardless of the scenario. Next, the intra-cluster parameters have been determined, and we show that the root-mean-square (rms) delay spread and rms angular spread follow a gamma distribution, regardless of the polarization. The MPC characteristics agree with the results in the literature and can be valuable when deploying a wireless sensor network in industrial environments