A Double-directional Channel Model for Multiuser Mimo Systems

A new geometry-based stochastic channel model called multiuser double-directional channel model (MDDCM) for macro cellular environments is introduced in this paper. It combines several ideas of directional channel modeling and includes propagation effects like over rooftop propagation, street canyon effect, Line-of-Sight (LOS) and far clusters. The details of the propagation effects and the corresponding model in the MDDCM are presented. INTRODUCTION Wireless communication systems with multiple antennas at the transmitter and the receiver (multiple input multiple output MIMO) have been reported recently to satisfy the demand for high data rates [1]. They are able to use the temporal and spatial character of the communication channel in an optimized way. In other words, higher data rates per user compared to today’s communication systems are possible. Necessary steps towards new MIMO systems are link and system level simulations. These simulations allow to estimate the performance of MIMO-algorithms, capacity gains and the behavior of the total communication network. The basis for this performance evaluation procedure is a realistic description of the wireless communication channel with a channel model that reproduces the stochastic character of the physical channel in time, frequency and in space. The potential of MIMO systems has been proofed under realistic channel conditions in many link-level simulations. But these gains cannot be translated directly into a corresponding gain on system-level [2]. On system-level interand intracell interference deteriorate the quality of the communication link and the whole system performance. Intracell interference means interference resulting from other users of the same cell. Intercell interference describes interference caused by users in other cells. For a correct interference analysis the channel impulse responses (CIR) between several MIMO mobile stations (MS) and MIMO base stations (BS) must be calculated, providing information about the correlation in time and space. This means that if two users are at the same place at the same time their CIR’s should be identical. A simple stochastic channel model, i.e. the rayleigh channel model, which is often used in information theoretical investigations, is no more realistic. Only spatial channel models fulfill this constraint. SPATIAL CHANNEL MODELS A general survey of spatial channel models can be found in [3]. They can be divided into deterministic, measurement based and geometry-based stochastic channel models. Because of their high calculation time, it is not possible to apply deterministic channel models, e.g. ray-tracing in multiuser environments. Measurement based channel models are based on channel information taken from real-time broadband MIMO measurement data [4]. From these data, sets of certain path parameters are extracted using a highresolution channel parameter estimation algorithm. As for each transmit and each receive position sitespecific channel data must be available, these models are particular suited for link-level simulations. Stochastic channel models with geometrical background are based on the assumption, that the directional structure of the channel can be modeled by the last interaction point between physical objects and electromagnetic waves, before the waves reach the base and the mobile station [5]. The interaction points can be grouped together and represent different propagation mechanisms. This reduces the complexity and the calculation time significantly compared to deterministic channels models. MULTIUSER DOUBLE-DIRECTIONAL CHANNEL MODEL A new geometry-based stochastic channel model called multiuser double-directional channel model (MDDCM) for macro cellular environments is introduced in this paper. It combines several ideas of directional channel modeling and includes propagation effects like over rooftop propagation, street canyon effect, Line-of-Sight (LOS) and far clusters [6], [7], [8]. The details of the propagation effects and the corresponding model in the MDDCM are presented in the following subsections.