Overview of spatial channel models for antenna array communication systems

Abstract

Throughout the history of wireless communications, spatial antenna diversity has been important in improving the radio link between wireless users. Historically, microscopic antenna diversity has been used to reduce the fading seen by a radio receiver, whereas macroscopic diversity provides multiple listening posts to ensure that mobile communication links remain intact over a wide geographic area. In recent years, the concepts of spatial diversity have been expanded to build foundations for emerging technologies, such as smart (adaptive) antennas and position location systems. Smart antennas hold great promise for increasing the capacity of wireless communications because they radiate and receive energy only in the intended directions, thereby greatly reducing interference. To properly design, analyze, and implement smart antennas and to exploit spatial processing in emerging wireless systems, accurate radio channel models that incorporate spatial characteristics are necessary. In this tutorial, we review the key concepts in spatial channel modeling and present emerging approaches. We also review the research issues in developing and using spatial channel models for adaptive antennas.

On the capacity of OFDM-based spatial multiplexing systems

“…The base transceiver station (BTS), however, is sufficiently high so that it is unobstructed and no local scattering occurs. Therefore, spatial fading at the BTS will be correlated with the exact correlation depending on the BTS antenna spacing and the angle spread observed at the BTS array [17]. Our model incorporates the power delay profile of the channel, but neglects shadowing.…”

“…Our model incorporates the power delay profile of the channel, but neglects shadowing. These assumptions on the propagation scenario are typical for cellular suburban deployments [17], where the BTS is on a tower or on the roof of a building and the terminal is on the street level and experiences local scattering. For the sake of simplicity, throughout the paper, we restrict our attention to the uplink case.…”

Optimization of Channel Capacity for Indoor Mimo Systems Using Genetic Algorithm

“…Therefore, multiple antenna arrays used in the transmitter and the receiver should be accurately designed to reduce the spatial correlation and achieve higher capacity. In the antenna design process, spatially correlated MIMO channels are typically modeled under certain assumptions about the scattering in the propagation environment and the geometry of the antenna arrays as in [2][3][4][5][6][7][8][9][10][11]. The proper modeling of channel is a challenging task and important part of the antenna design procedure as it can affect the performance of the wireless system under consideration.…”

“…The proper modeling of channel is a challenging task and important part of the antenna design procedure as it can affect the performance of the wireless system under consideration. The channel model employed in this work is a discrete model based on statistical distribution of the AoAs of the incoming rays as in [11] for the receiver part. The spatial correlation matrix at the transmitter will be modeled as in [12][13][14].…”

Distributed Antenna System for Mitigating Shadowing Effect in 60 GHz WLAN

“…The path difference of different antenna elements can be simplified into the phase difference induced by their relative distance. The mathematical description for obtaining the spatial CIRs can be found in [23]. We formulate this theory in the following in combination with the channel model provided previously.…”