MIMO Measurement and Joint M-D Parameter Estimation of Mobile Radio Channels Reiner S. Thomä, Andreas Richter, Dirk Hampicke and Gerd Sommerkorn 98684 Ilmenau, Germany, POB 100565, Phone: +49 3677 691160, Fax: +49 3677 691113, e-Mail:
[email protected] Ilmenau University of Technology, Dept. of Communications and Measurement
Abstract We describe a measurement and parameter identification procedure for the mobile radio propagation channel which includes azimuth directions of the propagating waves at both link ends, elevation at the base station, time delay, and Doppler shift. The measurement is based on an broadband, real-time multiple-input-multiple-output radio channel sounder. At the MS site a circular uniform beam array (CUBA) is used which covers 360° viewing angle whereas at the BS site a uniform rectangular array (URA) is deployed. We derive the underlying data model and propose a multidimensional joint parameter estimation procedure from measurements which is based o the M-D ESPRIT algorithm. The resolution of coherent paths by subspace smoothing and the reduction of measurement errors by device calibration procedures is addressed.
1
Introduction
The interest in the directional structure of the mobile radio channel is growing rapidly. Initially the motivation was the application of antenna arrays at the base station (BS). But in the recent time the doubledirectional structure of the radio channel has attracted a lot of interest. This is mainly due to two reasons. At one hand, double directional channel measurement gives better physical insight to the wave propagation mechanism in real radio environments since it has the power to gradually remove the antenna influence from the channel characterization [1]. It allows to distinguish between single and multiple bounce reflections since the propagation paths can be traced back from both sides of he link. Moreover, the resolution capability of coherent waves may be considerably enhanced even in presence of a limited measurement accuracy. On the other hand, there is a growing interest in the exploitation of multiple antennas at both the BS and MS site. These MIMO (multipleinput-multiple-output) transmission systems promise a considerable increase in capacity [2], [3]. Parametric MIMO channel models are required not only to estimate the achievable capacity from measurements [4] but also to predict the long term channel parameters for controlling of the modem signal processing at the down link. In this paper we concentrate on the measurement specific application of M-D channel parameter estimation. In [5] we have already reported on doubledirectional channel sounding. Here we present an extension which additional includes the elevation at the base station and the Doppler resolution. Also effective implementation strategies of the joint uni-
Receiver
Transmitter
Figure 1: Measurement setup tary M-D ESPIT and resolution issues related to coherent waves are considered.
2
Measurement setup and channel model
Our channel measurements are performed with the RUSK ATM wideband channel sounder [6] at 5.2 GHz (HIPERLAN II band) with a bandwidth of 120MHz. The channel sounder contains a multiplexer controller for 256 channels, that can be used to switch between the antenna elements of antenna arrays throughout the channel measurement. At the mobile transmitter we were using a 8-element circular uniform beam array (CUBA) [7] as the transmit array. The application of a circular configuration of antenna elements at the MS is reasonable since it provides 360° coverage in azimuth. At the fixed receiver, playing the role of the BS, a 8x8 element URA has been used. Due to the limited number of 256 multiplexer channels only 4 rows out of the 8 URA rows have been used for the measurements. Since all 256 channel impulse responses between the 8 transmit and the 32 receive antennas can be measured in a short time of, e.g., 2ms which corresponds to an the excess path delay of 1.6µs. This is well within the coherence time of typical HIPERLAN channels. The principal measurement setup is shown in figure 1. Using this setup it is possible to determine the direction of departure in azimuth κp, the time-delay τp, the Doppler-shift αp, the direction of arrival in azimuth θp, the direction of arrival in elevation ϕp, and the complex path weights γp of the domi-
P
H (t , f , s, l , k ) = ∑ γ p e − j 2 π tα p e − j 2 π fτ p e − j 2 π sθ p e − j 2 π lϕ p e − j 2 π kκ p
(1)
p =1
nant components P of the narrowband multipath radio channel. This leads to the data model (1) of the multipath channel. Obviously, this data model is only valid over a short time interval since it presumes static parameters. Fortunately enough, the M-D unitary ESPRIT algorithm offers the possibility of a joint superresolution channel parameter estimation from only a short sequence of MIMO measurement snapshots with a very reasonable afford.
3
Joint channel parameter estimation using the M-D Unitary ESPRIT
In order to develop double-directional channel models for link level simulations and channel capacity assessment the estimation of the parameters of the dominant multipath components of our channel model (1) is necessary. For this purpose we have developed a algorithm to transform the measured vcir into (1) using the ideas in [5]. Simultaneously we apply the frequency as well as the antenna array calibration matrices, thus reducing the influence of the channel sounder components to the measurement results. Since the parameter estimation from (1) is a multidimensional harmonic retrieval problem we apply the 5-D Unitary ESPRIT algorithm [8] to estimate the parameters of the dominant multipath channel components from the transformed MIMO recorded measurement data. In this context we will also discuss the application of multidimensional subspace smoothing for the estimation of the signal subspace required for the M-D Unitary ESPRIT. Finally we estimated the path weights γp related to the propagation path parameters estimated with the 5D Unitary ESPRIT. Table 1 gives a overview of the main processing steps for the parameter estimation from channel sounder measurements. Table 1 1. Transformation of the measured data into the M-D Unitary ESPRIT data space. 2. Estimation of the signal subspace. 3. Estimation of the inherent correct paired DoD (Azimuth), time-delay, Doppler-shift, and DoA (Azimuth and Elevation) parameter sets with the 5-D Unitary ESPRIT algorithm. 4. Least squares estimation of the complex propagation path weights using the estimated parameters. We will show the performance of the proposed channel parameter estimation algorithm by means of measurement results, and discuss some implementation issues of the M-D Unitary ESPRIT since it is a computational very demanding task.
Figure 2: measurement trolley with the CUBA array (left) and the URA (right)
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