One of the major error components of differential global navigation satellite systems is a multipath error in a reference station. This paper introduces a deep neural network based multipath modeling method. A signal to noise ratio, as well as satellite geometry, is used as a feature parameter to capture the variation of the multipath error caused by unavoidable changes in the vicinity of the reference station. The performance of the proposed method is demonstrated for both normal and varying multipath cases using experimental data. The remaining multipath error after mitigation is well bounded by the standardized error model.

Array processing proved itself in the last decades as a powerful approach to suppress harmful radio frequency interference. However, the interference mitigation in the spatial domain can also lead to the attenuation and loss of the desired Global Navigation Satellite System (GNSS) signals that are not sufficiently separated by their directions of arrival from the interfering signals. In order to overcome this effect, this paper proposes an approach to combine array processing and vector tracking in a single receiver. Formerly, the vector tracking loops have been shown to deliver superior performance in scenarios with blocked line-of-sight signals due to aiding of the affected signals during the outage. Since vector tracking loops are susceptible to faked GNSS signals, the proposed receiver architecture also includes a spoofing detection based on the direction-of-arrival estimation. The paper presents the technical concept and details about the realization of the array-based receiver that was developed at the German Aerospace Center (DLR). The techniques used to mitigate brute-force radio frequency interference and to detect spoofing signals are described. Experimental results obtained with these techniques in field are discussed.

A especially favorable multiple-input multiple-output (MIMO)-based concept for future mobile radio systems consists of the application of joint detection (JD) in the uplink and joint transmission (JT) in the downlink. By this, all the computational complex signal processing is shifted to the base station (BS), resulting in low-complexity mobile stations. Both JD and JT require channel knowledge at the BS which, if time-division duplexing is applied, can be obtained by training signal-based channel estimation in the uplink. Unfortunately, channel estimates are never perfect, which leads to performance degradations if these channel estimates, instead of perfect channel knowledge, are used for JD or JT. Especially channel errors due to the time variance of the mobile radio channel are often considered to be a severe problem in the application of MIMO techniques in high-mobility scenarios, which requires closer investigation. In this paper, a novel analysis of the performance degradations of zero-forcing JD and JT due to imperfect channel knowledge is presented. The analysis is based on linear Taylor approximation of the data-estimation error due to imperfect channel knowledge.

The demand for accurate positioning of mobile terminals for emergency services like E911 inspired extensive research not only on position estimation in mobile radio scenarios but also on new location based services. Unfortunately, mobile radio scenarios are characterized by shadowing and multipath propagation, which renders accurate position estimation a difficult task. This is especially true for indoor scenarios. Both position estimation based on satellite signals like GPS or GALILEO and position estimation based on the mobile radio system's signals suffer from these adverse propagation conditions. In the present paper we just accept that initial position estimates in mobile radio scenarios are rather rough. We focus on combining multiple successively obtained rough position estimates in order to obtain improved estimates of the path on which the mobile terminal moved or of the position at a certain time instant. When combining position estimates we have to consider that the mobile terminal may move during the measurement period in which the initial position estimates are obtained. We describe the mobility of the mobile terminal by a Markoff Model, whose states correspond to the positions, and apply the theory of hidden Markoff models for obtaining the improved position estimates

A specially favorable concept for interference reduction in future mobile radio systems consists in the application of joint detection in the uplink and joint transmission in the downlink. Concerning joint detection both optimum nonlinear and low complexity suboptimum linear signal processing algorithms are well known. This is not the case for joint transmission, where up to now most research work focuses on linear signal processing algorithms, which are dual to the ones applied for joint detection. In the present paper a novel signal processing algorithm for joint transmission, termed transmit nonlinear zero forcing, is presented. The main characteristic is the application of an unconventional multiply connected quantization scheme, which allows to improve the energy efficiency, i.e., for data symbols to be transmitted over channels with high attenuations without introducing excessive interferences. Especially in scenarios with large gain differences of the channels between the access point and individual mobile terminals said improved energy efficiencies allow a significant reduction of the required transmitted powers, a feature mitigating intercell interference in cellular systems and thereby enhancing system capacity. In practical systems such gain differences, due to shadowing and largely different distances between the access point and the mobile terminals, prevail.

In mobile radio networks with several operators covering the same geographic area, interferences between the frequency channels of the model used in 3GPP to evaluate the interference between operators is relined so that the simulation results reflect the parameters used for path to reduce the interference between the operators by radiation pattern design of the antennas at the base stations.

It is expected that in the forthcoming 3/sup rd/ generation (3G) mobile radio systems the downlinks will have to support much higher data rates than the uplinks. A promising measure to enable high downlink data rates consists in improving the carrier-to-interference ratios at the mobile receivers by the utilization or adaptive mufti-element transmit antennas. However, for the efficient operation of such antennas information about the downlink radio channels is required at the base stations. In the case of the 3G partial standard time division(TD)-CDMA designated for the time division duplexing (TDD) radio frequency bands, such information-thanks to the reciprocity theorem-is readily available from the uplink channel estimators. However, the 3G partial standard W(wideband)-CDMA designated for the frequency division duplexing (FDD) radio frequency bands suffers from the inherent disadvantage that, due to the frequency difference between uplink and downlink, the results of the uplink channel estimation cannot be directly used as the channel information required for adjusting the multi-element transmit antennas. Nevertheless, as long as the frequency difference between uplink and downlink is not too large, approaches to an at least sub-optimum adjustment of the downlink transmit antennas based on uplink channel estimates exist. In the paper such approaches are presented and evaluated by simulations.