Paul Lusina

User Effects on MIMO Performance: From an Antenna to a Link Perspective

We investigate in this paper the effects of the users presence on the performance of a multiple-input multiple-output (MIMO) system in data and in voice usage scenarios. The investigation studies the user effects on the antenna performance and how these are incorporated into the MIMO channel and the link characteristics. The antennas and the user are deterministic. These are then integrated into the statistical 3GPP spatial channel model (SCM) for a typical macrocell propagation environment setting. The channel performance is analyzed based on the average channel capacity, the average power transfer, the correlation, and the cumulative distribution function of the channel capacity as well as the link throughout and the error performance. The mentioned channel and link properties are tied to the MIMO antenna properties that are represented in the mutual coupling between the antennas, the power loss, the total radiated power, the mean effective gain (MEG), as well as the efficiency with emphasis on how the user affects each. It was found that the presence of the user contributed to a loss of up to 50% in the average channel power transfer. The data position was found to be the lowest in terms of channel capacity performance. The voice position performance showed a large dependence on the user orientation with respect to the line of sight path while the data position showed less dependence on the users orientation. We also discuss through the examined antenna and channel properties the importance of the channel multipath on the MIMO performance. In some scenarios, it was found that a well-conditioned channel can compensate for losses due to the presence of the user, improving the overall system performance. The presented investigation at the link level also discusses the user effects in different MIMO transmission schemes.

A 3D-to-2D Transform Algorithm for Incorporating 3D Antenna Radiation Patterns in SCM

We present a method to incorporate the effect of the three-dimensional (3D) antenna radiation patterns into a two-dimensional (2D) multiple-inputmultiple-output (MIMO) channel model. The proposed method is a low-complexity technique that increases the accuracy of existing 2D spatial channel model (SCM) proposed by 3GPP for performance analysis of long-term evolution (LTE) MIMO. Using a realistic 3D antenna field pattern and the 2D 3GPP SCM, the 3D-to-2D transform algorithm (3D-2D-TF) gives a 5% outage capacity within 0.5 b/s/Hz when compared to a higher complexity averaging approach using 18-cut planes (18-CP) of the 3D radiation pattern. This is achieved with 6% of the run-time complexity. By not including the elevation information, the original SCM 2D model gives an outage capacity prediction error of up to 2.4 b/s/Hz as compared to the 18-CP averaging approach. The 3D-2D-TF is therefore a promising low-complexity candidate that increases the accuracy of 2D channel models for MIMO 4G performance evaluations.

Analysis of MIMO Channel Capacity Dependence on Antenna Geometry and Environmental Parameters

We evaluate the multiple-input multiple-output (MIMO) channel capacity dependence on angular spread, antenna element separation, and angle of arrival. The empirically derived spatial channel model (SCM) is selected for the simulations and an uncoupled ideal dipole uniform linear array is considered. We show that for a small angular spread (8deg), the angle of arrival (AoA) will increase the required signal-to-noise ratio (SNR) for a high ergodic capacity by more than 4 dB as it moves away from the array broadside. For the case of a large angular spread (68deg), the AoA has a minimal impact on the ergodic capacity. Insight into the capacity behavior is explained in terms of the minimum channel eigenvalue and the path correlation. We also found that as the channel outage capacity threshold decreases, the impact of the system parameters is reduced.

Remote sampler - central brain architecture

We present a new distributed antenna system which uses compressive sampling in the uplink. We distill the receive points to minimum requirements of battery-powered receive-only “remote samplers.” The remote samplers transfer to a “central brain” the limited samples they capture. The central brain solves a linear program based on the L1 norm to determine the presence of a signalling mobile station (UE).

Deterministic and Statistical-Based Channel Models in the MIMO Link Evaluation

This letter studies the performance of a multiple-input-multiple-output (MIMO) link in a macrocell environment, with emphasis on the effects of the antenna parameters as applied in different channel models. Two types of channel models are used in this evaluation. The first is a deterministic electromagnetic-based channel model that physically describes the antennas within the channel environment, capturing their detailed effects on the link performance. The second is a standardized statistical-based model where the 3GPP spatial channel model (SCM) is investigated. The antenna effects in this channel are roughly included through the radiation patterns of isolated dipoles. The differences between the channel model types as applied to the antenna parameters are discussed. Our analyses show that understanding the assumptions made in the different channel models is important in the evaluation of a system, especially in multiple-antenna systems.

Impact of MIMO channel models on outage capacity

The comparison of the outage capacity for multiple-input multiple-output (MIMO) channel models that are based on different channel models is made. For this comparison, we chose the 3GPP Spatial Channel Model (SCM), a METRA Analytical Spatial Channel Model (A-SCM), and the correlation-based Long Term Evolution channel model (LTE). The effects of antenna element separation, array orientation, angle spread, and mutual coupling are compared for the models. The SCM performance showed the best agreement with how measurement results from the literature depend on the parameters studied, followed by the A-SCM and then the LTE model. The SCM was also the most computationally involved, followed by the A-SCM, and then the LTE models. We also discuss in what situations a particular channel model could be advantageous.

User Presence and Antenna Efficiency Effects on MIMO Link Performance

We discuss in this paper the effects of antenna efficiency in the presence of a user and on the performance of a multiple-input multiple-output system. The investigation is carried out in different usage scenarios where the antenna efficiency changes significantly from one scenario to another. The propagation channel is defined to include the 3D antenna electromagnetic properties with the 3GPP spatial channel model. We then investigate at a link level using a Long Term Evolution (LTE) link simulator where the antenna and the user are integrated into the link. The analyses are based on channel correlation, channel power transfer factor, and the link throughput. We show the importance of accurately accounting for the antenna efficiency for realistic MIMO link performance. We also show that accounting for the antenna efficiency is a weighted factor defined by the antenna pattern behavior.

Usage analysis in a MIMO channel for voice and data

We investigate the effects of the user presence on a multi-antenna design from the channel perspective. Two usage scenarios are investigated, data and voice. The antennas and the user are electromagnetically simulated and are then integrated into the statistical 3GPP spatial channel model. There, the channel statistics are analyzed through the average channel capacity, correlation, and the channel power transfer. It was found that the presence of the user contributed to a loss up to 50% in the channel power. The data position was found to be the lowest in terms of channel capacity. The user orientation caused the most variability in the performance for the voice position, while it had negligible impact on performance in the data position.