Tommi Jämsä

Channel Modelling for Multiprobe Over-the-Air MIMO Testing

This paper discusses over-the-air (OTA) test setup for multiple-input-multiple-output (MIMO) capable terminals with emphasis on channel modelling. The setup is composed of a fading emulator, an anechoic chamber, and multiple probes. Creation of a propagation environment inside an anechoic chamber requires unconventional radio channel modelling, namely, a specific mapping of the original models onto the probe antennas. We introduce two novel methods to generate fading emulator channel coefficients; the prefaded signals synthesis and the plane wave synthesis. To verify both methods we present a set of simulation results. We also show that the geometric description is a prerequisite for the original channel model.

Comparison of SCM, SCME, and WINNER Channel Models

This paper is summarizing and comparing properties of channel models used for Beyond-3G (B3G) MIMO simulations: 3GPP spatial channel model (SCM), its extension (SCME), and models developed by WINNER. Compared models are offering complete channel model description in a sense of large-scale as well as small-scale effects in MIMO radio-channel. WINNER targeted model was supposed to provide reliable tool for estimation of system performance, covering frequencies up to 5 GHz and bandwidths of 100 MHz in different types of environment. Since SCM was originally proposed for 2 GHz range and 5 MHz bandwidth, certain extensions (SCME) were necessary. However, SCME performance was restricted since it has been design as backward compatible with SCM. That was the motivation to start using the new WINNER generic channel model, where model parameters are extracted from channel-sounding measurements covering targeted frequency range and bandwidth. This paper describes all important differences and compares features and performances of the models.

Analysis and measurements for indoor polarization MIMO in 5.25 GHz band

We present the results of multiple-input multiple-output (MIMO) indoor channel measurements in the 5.25 GHz band, emphasizing the case where both transmitter and receiver apply dual-polarized antennas. Wideband (100 MHz) capacity results show that dual-polarized antennas provide an attractive solution for MIMO multiplexing. This is due to the fact that the static component in a line-of-sight (LOS) channel preserves its polarization, and channels between dual-polarized antennas may still remain separated. This is not necessarily the case if spatially separated copolarized antennas are applied.

Implementation techniques of broadband radio channel simulators

This paper discusses the advantages and disadvantages of different implementation techniques of radio channel simulators and analyses in more depth the challenges of increasing bandwidth and dynamic range. One selected technology has been implemented and tested. A block diagram of the simulator and test results are shown.

Radio propagation modeling for 5G mobile and wireless communications

This article first identifies requirements of 5G radio propagation models for relevant propagation scenarios and link types derived from the analysis of recently discussed 5G visions and respective 5G technology trends. A literature survey reveals that none of the state-of-the-art propagation models such as WINNER/IMT-Advanced, COST 2100, and IEEE 802.11 fully satisfies the model requirements without significant extensions, and therefore there is room for a new framework of propagation models. We then present a novel map-based propagation model that satisfies the model requirements, and also introduce new extensions to existing stochastic models. Several open issues are finally identified that require further studies in 5G propagation modeling.

Complexity Comparison of MIMO Channel Modelling Methods

Computational complexity of simulation of channel models has become an important issue due to the increased requirements for, e.g., bandwidth, number of antennas, quality of service (QoS), number of users, and advanced network topologies. This paper compares the computational complexity of generation of multiple-input multiple-output (MIMO) radio channel realizations with different modelling principles, namely correlation matrix based and sum of rays based methods. Three different aspects are compared. They are complexity of channel coefficient generation, number of required parameters, and the complexity of simulation. The comparison shows that the complexity of the channel coefficient generation is in about the same order of magnitude when the number of MIMO antenna pairs is up to 16 (e.g. 4times4 MIMO). When the number of antennas is higher, the correlation matrix method has higher complexity. The complexity of correlation method depends strongly on the number of antennas while the sum-of-rays method is quite insensitive to it. The simulation complexity dominates the overall complexity and is the same for both methods. The main conclusion of this paper is that the sum-of-rays based method is recommendable especially when the number of antenna pairs is high.

Empirical Models and Parameters for Rural and Indoor Wideband Radio Channels At 2.45 and 5.25 GHZ

The modeling results from wideband radio channel measurements are presented for two environments: rural and indoor. The paper focuses on the average and instantaneous characteristics of received power including: path loss, shadow fading, power delay profiles, and rms delay spreads. Furthermore, the cross correlation between shadowing of the path loss and the delay spread is investigated and found to be large. Doppler measurement campaigns were conducted in both environments, at 2.45 GHz and 5.25 GHz along the same measurement routes, with 100 MHz bandwidth. In this paper it is shown that we may apply 2.45 GHz band small scale models into 5.25 GHz band. It can be also seen, as for the measured scenarios, on average, the difference in terms of path loss between 2.45 GHz and 5.25 GHz in line-of-sight indoor environment, where waveguide effect is encountered, is c.a. 8 dB, instead in rural outdoor the mentioned difference is c.a. 6 dB

Real time simulation of measured radio channels

Recent advancements in radio channel measuring and simulation/emulation technologies have enabled the simulation of recorded radio channel data in real time simulators. The paper presents and compares different methods to simplify radio channel measurement data for channel simulation purposes. Different processing methods are compared by utilizing an air interface evaluation platform. The platform consists of SW radio units, a multichannel simulator and graphical user interface. BER results show that too optimistic results are obtained if only simple standardized models are utilized.

On Angular Sampling Methods for 3-D Spatial Channel Models

This letter discusses generating three-dimensional (3-D) spatial channel models with emphasis on the angular sampling methods. Three angular sampling methods-i.e., modified uniform power sampling, modified uniform angular sampling, and random pairing methods-are proposed and investigated in detail. The random pairing method, which uses only 20 sinusoids in the ray-based model for generating the channels, presents good results if the spatial channel cluster is with a small elevation angle spread. For spatial clusters with large elevation angle spreads, however, the random pairing method would fail, and the other two methods should be considered.

Correlations of Wide-Band Channel Parameters in Street Canyon at 2.45 and 5.25 GHz

The correlation between channel parameters root mean square delay spread (DS), shadow fading, number of clusters, and Rician factors (K-factors or K) is investigated based on wide-band channel measurements. The channel measurements were performed at 2.45 and 5.25 GHz in long line-of-sight (LOS) and non-LOS (NLOS) street canyons. The relation of the channel parameters to distance is illustrated. Very high correlation between channel parameters was found in the LOS street canyon, while much lower correlation was found in the NLOS street canyon. The linear relationship between the DS and the other channel parameters is derived in the LOS case, thus allowing the use of one channel parameter (e.g., the DS) to predict the others.