Joint Characterization of MM-Wave and CM-Wave Device-to-Device Fading Channels

Device-to-Device (D2D) wireless communications has many envisioned applications such as proximity-based networking, tactical communications and situation awareness of military personnel in a battlefield. The joint use of multiple frequency bands could provide further enhancement to existing D2D wireless system and localization architectures. However, the development of any suitable communication system with this capability will requires accurate propagation channel measurement and modeling to understand channel frequency dependencies in an environment in which the system will operate. In this paper, we present a detailed description of a propagation channel measurement campaign performed in an outdoor environment within the millimeter wave (mm-wave) 59 - 63 GHz and centimeter wave (cm-wave) 2 - 6 GHz frequency bands. The measurements were conducted for both line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. We extracted (and compared) propagation channel parameters such as distance-dependent pathlossexponent (γ), shadowing gain (ξσ), root-mean-square (rms) delay spread (T rms ) and amplitude fading statistics to motivate a suitable channel model in both bands. The model developed can be used for realistic performance evaluations of devices operating in the cm-wave and/or mm-wave bands.Peer reviewe

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

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