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

Experimental investigation of V2I radio channel in an arched tunnel

This paper describes the results of the experimental radio channel sounding campaign performed in an arched road tunnel in Le Havre, France. The co-polar and cross-polar channels measurements are carried out in the closed side lane, while the lane along the center of the tunnel is open to traffic. We investigate the channel characteristics in terms of: path loss, fading distribution, polarization power ratios and delay spread. All these parameters are essential for the deployment of vehicular communication systems inside tunnels. Our results indicate that, while the H-polar channel gain attenuates slower than the V-polar channel due to the geometry of the tunnel, the mean delay spread of the H-polar channel is larger than that of the V-polar channel

Dual-Polarized Ricean MIMO Channels: Modeling and Performance Assessment

In wireless communication systems, dual-polarized (DP) instead of single-polarized (SP) multiple-input multiple-output (MIMO) transmission is used to improve the spectral efficiency under certain conditions on the channel and the signal-to-noise ratio (SNR). In order to identify these conditions, we first propose a novel channel model for DP mobile Ricean MIMO channels for which statistical channel parameters are readily obtained from a moment-based channel decomposition. Second, we derive an approximation of the mutual information (MI), which can be expressed as a function of those statistical channel parameters. Based on this approximation, we characterize the required SNR for a DP MIMO system to outperform an SP MIMO system in terms of the MI. Finally, we apply our results to channel measurements at 2.53 GHz. We find that, using the proposed channel decomposition and the approximation of the MI, we are able to reproduce the (practically relevant) SNR values above which DP MIMO systems outperform SP MIMO systems.Comment: submitted to the IEEE Transactions on Communication

Polarization properties of specular and dense multipath components in a large industrial hall

This paper presents an analysis of the polarization characteristics of specular and dense multipath components (SMC & DMC) in a large industrial hall based on frequency-domain channel sounding experiments at 1.3 GHz with 22 MHz bandwidth. The RiMAX maximum-likelihood estimator is used to extract the full polarimetric SMC and DMC from the measurement data by taking into account the polarimetric radiating patterns of the dual-polarized antennas. Cross-polar discrimination (XPD) values are presented for the measured channels and for the SMC and DMC separately

Multi-user Linear Precoding for Multi-polarized Massive MIMO System under Imperfect CSIT

The space limitation and the channel acquisition prevent Massive MIMO from being easily deployed in a practical setup. Motivated by current deployments of LTE-Advanced, the use of multi-polarized antennas can be an efficient solution to address the space constraint. Furthermore, the dual-structured precoding, in which a preprocessing based on the spatial correlation and a subsequent linear precoding based on the short-term channel state information at the transmitter (CSIT) are concatenated, can reduce the feedback overhead efficiently. By grouping and preprocessing spatially correlated mobile stations (MSs), the dimension of the precoding signal space is reduced and the corresponding short-term CSIT dimension is reduced. In this paper, to reduce the feedback overhead further, we propose a dual-structured multi-user linear precoding, in which the subgrouping method based on co-polarization is additionally applied to the spatially grouped MSs in the preprocessing stage. Furthermore, under imperfect CSIT, the proposed scheme is asymptotically analyzed based on random matrix theory. By investigating the behavior of the asymptotic performance, we also propose a new dual-structured precoding in which the precoding mode is switched between two dual-structured precoding strategies with 1) the preprocessing based only on the spatial correlation and 2) the preprocessing based on both the spatial correlation and polarization. Finally, we extend it to 3D dual-structured precoding.Comment: accepted to IEEE Transactions on Wireless Communication

Polarization reconfigurable antennas for space limited multiple input multiple output system

Wireless communication undergoes rapid changes in recent years. More and more people are using modern communication services, thus increasing the need for higher capacity in transmission. One of the methods that is able to meet the demands is the use of multiple antennas at both link ends known as Multiple Input Multiple Output (MIMO) system. However, for the space limited MIMO system, it is relatively difficult to accomplish good performance by using conventional antennas. Therefore, to further improve the performance offered by MIMO, Polarization Reconfigurable Antennas (PRAs) can be adopted. The diversity in polarization can be exploited to increase channel capacity. Moreover, the use of PRAs can also provide savings in terms of space and cost by arranging orthogonal polarized together instead of two physically space separation antennas. Here, single and dual port PRAs are proposed. Two techniques are deployed to achieve the PRAs are slits perturbation (switches on the radiating patch) and alteration of the feeding network (switches on the ground plane). Switching mechanism (ideal and PIN diode) is introduced to reconfigure the polarization between left-hand circular polarizations, right-hand circular polarizations, or linear polarization, operating at wireless local area network frequency band (2.4 – 2.5 GHz). Furthermore, by exploiting the odd and even mode of the coplanar waveguide structure, dual ports PRAs are realized with the ability to produce orthogonal linear polarization (LP) and circular polarization (CP) modes simultaneously. Good measured port polarization isolations (S21) of -16.3 dB and -19 dB are obtained at the frequency of 2.45 GHz for configuration A1 (orthogonal LP) and A2 (orthogonal CP), respectively. The proposed PRAs are tested in 2 x 2 MIMO indoor environments to validate their performances by using scalar power correlation method when applied as receiver in both line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Channel capacity improvement has been achieved for spatial diversity (92.9% for LOS and 185.9% for NLOS) and polarization diversity (40.7% for LOS and 57.9% for NLOS). The proposed antenna is highly potential to be adopted to enhance the performance of the MIMO system, especially in dealing with multipath environment and space limited applications

Analysis of the Local Quasi-Stationarity of Measured Dual-Polarized MIMO Channels

It is common practice in wireless communications to assume strict or wide-sense stationarity of the wireless channel in time and frequency. While this approximation has some physical justification, it is only valid inside certain time-frequency regions. This paper presents an elaborate characterization of the non-stationarity of wireless dual-polarized channels in time. The evaluation is based on urban macrocell measurements performed at 2.53 GHz. In order to define local quasi-stationarity (LQS) regions, i.e., regions in which the change of certain channel statistics is deemed insignificant, we resort to the performance degradation of selected algorithms specific to channel estimation and beamforming. Additionally, we compare our results to commonly used measures in the literature. We find that the polarization, the antenna spacing, and the opening angle of the antennas into the propagation channel can strongly influence the non-stationarity of the observed channel. The obtained LQS regions can be of significant size, i.e., several meters, and thus the reuse of channel statistics over large distances is meaningful (in an average sense) for certain algorithms. Furthermore, we conclude that, from a system perspective, a proper non-stationarity analysis should be based on the considered algorithm

MIMO Systems: Principles, Iterative Techniques, and advanced Polarization

International audienceThis chapter considers the principles of multiple-input multiple-output (MIMO) wireless communication systems as well as some recent accomplishments concerning their implementation. By employing multiple antennas at both transmitter and receiver, very high data rates can be achieved under the condition of deployment in a rich-scattering propagation medium. This interesting property of MIMO systems suggests their use in the future high-rate and high-quality wireless communication systems. Several concepts in MIMO systems are reviewed in this chapter. We first consider MIMO channel models and recall the basic principles of MIMO structures and channel modeling. We next study the MIMO channel capacity and present the early developments in these systems concerning the information theory aspect. Iterative signal detection is considered next; it considers iterative techniques for space-time decoding. As the capacity is inversely proportional to the spatial channel correlation, MIMO antennas should be sufficiently separated, usually by several wavelengths. In order to minimize antennas' deployment, we present advanced polarization diversity techniques for MIMO systems and explain how they can help to reduce the spatial correlation in order to achieve high transmission rates. We end the chapter by considering the application of MIMO systems in local area networks, as well as their potential in enhancing range, localization, and power efficiency of sensor networks