Performance analysis of spatially distributed MIMO systems

With the growing popularity of ad-hoc sensor networks, spatially distributed multiple-input multiple-output (MIMO) systems have drawn a lot of attention. This work considers a spatially distributed MIMO system with randomly distributed transmit and receive antennas over spatial regions. The authors use the modal decomposition of wave propagation to analyse the performance limits of such system, since the sampling of the spatial regions populated with antennas is a form of mode excitation. Specifically, they decompose signals into orthogonal spatial modes and apply concepts of MIMO communications to quantify the instantaneous capacity and the outage probability. The authors’ analysis shows that analogous to conventional point-to-point MIMO system, the instantaneous capacity of spatially distributed MIMO system over Rayleigh fading channel is equivalent to a Gaussian random variable. Afterwards, they derive an accurate closed-form expression for the outage probability of proposed system utilising the definition of instantaneous capacity. Besides, in rich scattering environment, the spatially distributed MIMO system provides best performance when the spatial regions are of same size, and each region is equipped with equal number of antennas. Furthermore, to facilitate the total transmit power allocation among the channels, they propose an algorithm which indicates a significant performance improvement over conventional equal transmit power allocation scheme, even at low signal-to-noise ratio

Spatial Limits to Mutual Information Scaling in Multi-Antenna Systems

Previous results have shown significant capacity gains by employing multiple antennas at both transmitter and receiver, however, due to physical size restraints (particularly at the receiver) these may not be obtained. In this paper we consider the capacity behaviour of multi-antenna systems when the receiver sampling is constrained to a finite region of space. By characterizing the wavefield generated at the receiver due to transmitted signals and the scattering environment, a theoretically derived sampling threshold is shown to exist, at which the capacity growth is reduced from linear to logarithmic with increasing number of sampling outputs. Furthermore, this threshold is shown to be linearly dependent on the receiver region radius within which the sampling is constrained, and is independent of the sampling characteristics such as the antenna properties, array geometry, and/or array signal processing

Applications of Continuous Spatial Models in Multiple Antenna Signal Processing

This thesis covers the investigation and application of continuous spatial models for multiple antenna signal processing. The use of antenna arrays for advanced sensing and communications systems has been facilitated by the rapid increase in the capabilities of digital signal processing systems. The wireless communications channel will vary across space as different signal paths from the same source combine and interfere. This creates a level of spatial diversity that can be exploited to improve the robustness and overall capacity of the wireless channel. Conventional approaches to using spatial diversity have centered on smart, adaptive antennas and spatial beam forming. Recently, the more general theory of multiple input, multiple output (MIMO) systems has been developed to utilise the independent spatial communication modes offered in a scattering environment. ¶ ..