Reduced Complexity Channel Models for IMT-Advanced Evaluation

Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2009, Article ID 195480, 13 pages doi:10.1155/2009/195480 Research Article Reduced Complexity Channel Models for IMT-Advanced Evaluation Yu Zhang,1 Jianhua Zhang,1 Peter J. Smith,2 Mansoor Shafi,3 and Ping Zhang4 1 Wireless Technology Innovation Institute, Beijing University of Posts and Telecommunications, P.O. Box 92, Beijing 100876, China 2 Department of Electrical and Computer Engineering, University of Canterbury, Private Bag 4800, 8140 Christchurch, New Zealand 3 Telecom New Zealand, P.O. Box 293, 6001 Wellington, New Zealand 4 Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, P.O. Box 92, Beijing 100876, China Correspondence should be addressed to Yu Zhang, yu Received 31 July 2008; Revised 6 November 2008; Accepted 26 February 2009 Recommended by Claude Oestges Accuracy and complexity are two crucial aspects of the applicability of a channel model for wideband multiple input multiple output (MIMO) systems. For small number of antenna element pairs, correlation-based models have lower computational complexity while the geometry-based stochastic models (GBSMs) can provide more accurate modeling of real radio propagation. This paper investigates several potential simplifications of the GBSM to reduce the complexity with minimal impact on accuracy. In addition, we develop a set of broadband metrics which enable a thorough investigation of the differences between the GBSMs and the simplified models. The impact of various random variables which are employed by the original GBSM on the system level simulation are also studied. Both simulation results and a measurement campaign show that complexity can be reduced significantly with a negligible loss of accuracy in the proposed metrics. As an example, in the presented scenarios, the computational time can be reduced by up to 57% while keeping the relative deviation of 5% outage capacity within 5%. Copyright © 2009 Yu Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. Introduction The pioneering work by Winters [1], Telatar [2], Foschini and Gans [3] ignited enormous interest in multiple input multiple output (MIMO) systems as they have the potential to provide remarkable spectral efficiencies when the channel exhibits rich scattering. Wideband wireless systems with multiple antennas have been recognized as one of the most promising candidates for next generation mobile systems which are also known as IMT-Advanced systems. It is well known that the propagation conditions have a crucial impact on the design, simulation, and deployment of new communication systems. Therefore, it is of great interest to characterize and model the wideband MIMO channel to enable accurate simulations of system performance. Propagation characteristics have been investigated thoroughly based on measured data from channel sounding in various different scenarios [4–8]. An overview of the state-of-theart channel models is provided in [9]. These channel models can be divided into two major categories: (a) the correlation based models, for example, the Kronecker model [10] and the Weichselberger model [11]; and (b) the parametric or geometry-based stochastic models (GBSMs), for example, the COST 259 directional channel model (DCM) [12], the COST 273 channel model [13], the 3rd Generation Partnership Project (3GPP) spatial channel model (SCM) [14], and the WINNER channel model [15, 16], and so forth. Because of their simplicity, the correlation-based models are widely used for analyzing and designing spacetime transmission technologies. The GBSM is more complex and less easy to use. One feature of a GBSM is that the simulation is divided into a number of drops which can be thought as channel segments with infinite time. Within each drop, different random geometries are generated. This 2 EURASIP Journal on Wireless Communications and Networking modeling methodology is adopted by the International Telecommunication Union (ITU) for the evaluation of IMTAdvanced systems [17]. In comparison with the broadly adopted traditional tapped delay line (TDL) models in the GSM and IMT-2000 systems, there are two main challenges for the IMT-Advanced channel model. Firstly, the TDL models in [18, 19] have an invariant channel profile. (The “channel profile” stands for the channel characteristics over a fading distance of tens of wavelengths, in spatial, temporal, and frequency domains, including the power delay profile (PDP), power angular spectrum (PAS), Doppler spectrum, and so forth.) However, even for a single link, geometry-based MIMO channel models need multiple channel profiles to accurately characterize the extra degrees of freedom induced by employing multiple antennas. As a result, far more random variables (RVs) have to be embedded into the channel model than are required by the TDL models. Secondly, because of the higher data rates targeted with a system bandwidth of up to 100 MHz, many more multipath components (MPCs) can be resolved, which leads to an increase in the number of taps for wideband MIMO channel models. Since the system level evaluation of radio interface technologies (RITs) usually requires the generation of multiple users dropped into a 19 hexagonal cell network, these two challenges faced by GBSMs make the evaluation a time consuming exercise. Hence, there is an urgent need to simplify the geometry-based MIMO channel models. As the correlation-based models have greatly reduced computational complexity, several papers have tried to bridge the gap between the correlated models and GBSMs. The separability of spatial-temporal correlation in the 3GPP SCM model is investigated in [20], which proposed a correlation-based model to replace the geometrybased model. A numerically efficient approximation of spatial correlation models is proposed in [21], which shows a good fit to the existing parametric models with a uniform linear array (ULA) or uniform circular array (UCA) for an angular spread (AS) smaller than 10◦ . A simplified approach to apply the 3GPP SCM model was suggested in [22], which was also proposed for the evaluation of the 3GPP long-term evolution (LTE) systems. Correlation-based replacements of the GBSM can substantially reduce the computational complexity. However, in such simplified models the antenna geometries and radiation patterns cannot be altered easily by the user of the model. On the other hand, this feature is automatically enabled by the geometry-based modeling for the propagation parameters and antennas. In this paper, we investigate five possible simplifications to the GBSM model. These simplifications are much more straightforward than those obtained by converting a GBSM to its correlat (...truncated)