A Non-Stationary Channel Model with Correlated NLoS/LoS States for ELAA-mMIMO

Abstract

In this paper, a novel spatially non-stationary fading channel model is proposed for multiple-input multiple-output (MIMO) system with extremely-large aperture service-array (ELAA). The proposed model incorporates three key factors which cause the channel spatial non-stationarity: 1) link-wise path-loss; 2) shadowing effect; 3) line-of-sight (LoS)/non-LoS state. With appropriate parameter configurations, the proposed model can be used to generate computer-simulated channel data that matches the published measurement data from practical ELAA-MIMO channels. Given such appealing results, the proposed fading channel model is employed to study the cumulative distribution function (CDF) of ELAA-MIMO channel capacity. For all of our studied scenarios, it is unveiled that the ELAA-MIMO channel capacity obeys the skew normal distribution. Moreover, the channel capacity is also found close to the Gaussian or Weibull distribution, depending on users' geo-location and distribution. More specifically, for single-user equivalent scenarios or multiuser scenarios with short user-to-ELAA distances (e.g., 1 m), the channel capacity is close to the Gaussian distribution; and for others, it is close to the Weibull distribution. Finally, the proposed channel model is also employed to study the impact of channel spatial non-stationarity on linear MIMO receivers through computer simulations. The proposed fading channel model is available at https://github.com/ELAA-MIMO/ non-stationary-fading-channel-model.

Constellation-Oriented Perturbation for Scalable-Complexity MIMO Nonlinear Precoding

“…Moreover, as already discussed in [2], it is very hard to find the optimum of τ in a mathematical form. Therefore, the objective of this experiment is to study the optimum configuration of the parameter (τ ) in (10) through extensive computer simulations. Fig.…”

“…2) Optimality of WL-COP: Mathematically, (10) shows that WL-COP differs from VP mainly in its linear precoding matrix denoted by…”

“…When W does not satisfy the condition C3), the objective function (10) cannot be represented into a similar form as ( 14). This is because W is divided into J groups; column vectors within each group are linearly combined.…”

“…This could drag user terminals into the near field of the transmitter and renders wireless channels spatially non-stationary [8], [9]. Also, as discussed in [10], current MIMO transceivers are not yet optimized for nonstationary MIMO channels. As a conclusion of our brief background review, (close-to) symmetric MIMO architecture is still one of important candidates for future wireless MIMO technology, where scalable NLP technique plays a central role.…”

Very large scale integration architectures of discrete transforms for digital signal processing applications

“…• Much smaller antenna spacing: Note that half-wavelength antenna spacing is widely considered in conventional mMIMO [63]. However, in XL-MIMO, the antenna spacing is expected to be much smaller than the conventional halfwavelength.…”