Turbo Transceivers in MIMO Wireless Communications and Their Performance Verification via Multi-Dimensional Channel Sounding

The discovery of the Turbo codes has driven research on the creation of new signal detection concepts that are, in general, referred to as the Turbo approach. Recently, this approach has made a drastic change in creating signal detection techniques and algorithms such as equalization of inter-symbol interference (ISI) experienced by broadband single carrier signaling over mobile radio channels. A goal of this paper is to provide readers with broad views and knowledge of the Turbo concept-based Multiple-Input Multiple-Output (MIMO) signal transmission techniques. How the techniques have been developed in various applications and how they perform in real-field environments are introduced

Channel Correlation Diversity in MU-MIMO Systems – Analysis and Measurements

In multiuser multiple–input multiple–output (MU–MIMO) systems, channel correlation is detrimental to system performance. We demonstrate that widely used, yet overly simplified, correlation models that generate identical correlation profiles for each terminal tend to severely underestimate the system performance. In sharp contrast, more physically motivated models that capture variations in the power angular spectra across multiple terminals, generate diverse correlation patterns. This has a significant impact on the system performance. Assuming correlated Rayleigh fading and downlink zero–forcing precoding, tight closed form approximations for the average signal–to–noise–ratio, and ergodic sum spectral efficiency are derived. Our expressions provide clear insights into the impact of diverse correlation patterns on the above performance metrics. Unlike previous works, the correlation models are parameterized with measured data from a recent 2.53 GHz urban macrocellular campaign in Cologne, Germany. Overall, results from this paper can be treated as a timely re–calibration of performance expectations from practical MU–MIMO systems

Channel Correlation Diversity in MU-MIMO Systems - Analysis and Measurements

In multiuser multiple–input multiple–output (MU–MIMO) systems, channel correlation is detrimental to system performance. We demonstrate that widely used, yet overly simplified, correlation models that generate identical correlation profiles for each terminal tend to severely underestimate the system performance. In sharp contrast, more physically motivated models that capture variations in the power angular spectra across multiple terminals, generate diverse correlation patterns. This has a significant impact on the system performance. Assuming correlated Rayleigh fading and downlink zero–forcing precoding, tight closed form approximations for the average signal–to–noise–ratio, and ergodic sum spectral efficiency are derived. Our expressions provide clear insights into the impact of diverse correlation patterns on the above performance metrics. Unlike previous works, the correlation models are parameterized with measured data from a recent 2.53 GHz urban macrocellular campaign in Cologne, Germany. Overall, results from this paper can be treated as a timely re–calibration of performance expectations from practical MU–MIMO systems

IEEE Access Special Section Editorial: Millimeter-Wave and Terahertz Propagation, Channel Modeling, and Applications

The demand for ever-increasing wireless data transmission rates and throughput area-densities, especially with regard to microcellular networks, internet access, back-hauling, inter-device transmission, and sensing applications, has spurred the exploration of new spectra in the millimeter-wave (30–300 GHz) and terahertz bands (0.1–10 THz), and the study of techniques for multi-Gigabit transmission based on very high-gain antennas [items 1) and 2) in the Appendix]

Spatial Correlation Variability in Multiuser Systems

Spatial correlation across an antenna array is known to be detrimental to the terminal signal-to- interference-plus-noise-ratio (SINR) and system spectral efficiency. For a downlink multiuser multiple-input multiple-output system (MU-MIMO), we show that the widely used, yet overly simplified, correlation models which generate fixed correlation patterns for all terminals tend to underestimate the system performance. This is in contrast to more sophisticated, yet physically motivated, remote scattering models that generate variations in the correlation structure across multiple terminals. The remote scattering models are parameterized with measured data from a recent 2.53 GHz urban macrocellular channel measurement campaign in Cologne, Germany. Assuming spatially correlated Ricean fading, with maximum-ratio transmission precoding, tight closed-form approximations to the expected (average) SINR, and ergodic sum spectral efficiency are derived. The expressions provide clear insights into the impact of variable correlation patterns on the above performance metrics. Our results demonstrate the sensitivity of the MU-MIMO performance to different correlation models, and provide a cautionary tale of its impact