Matthias Stege

A multiple input-multiple output channel model for simulation of Tx- and Rx-diversity wireless systems

Space-time receivers for wireless communication systems offer the possibility to have both Tx- and Rx-antennas. For a realistic simulation of such systems, a multiple input multiple output (MIMO) spatial channel model is required which reasonably characterizes the space- and time-variant effects of the mobile radio channel. This paper describes a space-time vector channel model with realistic fading simulation for different scenarios. Mutual correlation between the fading coefficients is considered. This allows an estimation of the diversity gain, that can be achieved with space-time receivers in different scenarios.

MIMO channel estimation with dimension reduction

The number of channel estimates that have to be estimated in multiple-input multiple-output (MIMO) system is in general much larger, than in a single antenna communication scheme. This leads to lower signal to noise ratios (SNR) of the channel estimates if a constant pilot power independent from the number of transmit antennas is assumed. The use of long-term spatial channel characteristics can improve channel estimation for MIMO wireless systems. Separating the signal and the noise subspace followed by a dimension reduction can significantly reduce additive noise on channel estimates. This leads to improved channel estimation, especially for MIMO systems with high numbers of antennas, and to lower pilot power requirements.

Efficient tracking of eigenspaces and its application to eigenbeamforming

To achieve high performance for MIMO wireless systems with multiple transmit and receive antennas a detailed understanding of the characteristics of the eigenspace of the channel is essential. It represents the spatial characteristics of the propagation scenario in general and can be expressed by different covariance matrices of the channel coefficients. In many MIMO-algorithms the knowledge of the eigenvectors and eigenvalues is required. As typical for the wireless channel, the spatial characteristics continuously change. Therefore, an efficient method for tracking the eigenspace with moderate computational complexity is required. Tracking of the eigenspace using incremental Jacobi rotations is presented and compared to other known algorithms for subspace tracking. Eigenbeamforming serves as an example, where such a tracking algorithm can be applied.

Multistratum-permutation codes for MIMO communication

Multiple-input-multiple-output (MIMO) systems offer much capacity gain over single antenna approaches. The recently proposed multistratum space-time code (MSSTC) is such a MIMO-scheme among many others. In this paper, a generalization of the multistratum idea is presented and leads to the new family of multistratum-permutation codes. It is shown, that this scheme can achieve a higher link capacity than the MSSTC or Vertical-Bell Labs Layered Space-Time (V-BLAST). Scheme examples are presented for a 4/spl times/4 antenna system transmitting four data streams in parallel. They also show a promising performance for successive interference cancellation (SIC) receiver algorithms with a realistic complexity.

On the performance of space-time block codes

Space-time block codes (STBC), that have been introduced by S.M. Alamouti (IEEE Journal on Selected Areas in Communication, vol.16, no.8, p.1451-8, 1998) and V. (IEEE-info, vol.45, 1999), are now considered in the current 3GPP standard as one method to achieve spatial diversity. While the performance of space-time block codes has been subject of extensive research (see Parkvall, S. et al, 2000; Correia, A. et al., 1999; Tharokh et al., 1999), the impact of channel estimation errors and closed loop power control on the performance of STBC remain open for further research. The performance of STBC with imperfect channel estimates and closed loop power control is analyzed for flat fading channels as well as for multipath channels.

Successive interference cancellation and its implications for the design of layered mimo-algorithms

In rich scattering environments, wireless systems with multiple transmit and receive antennas (MIMO) offer large capacity gains. They are in general based on a parallel transmission of 1 5 M 5 NT signal steams called layers (NT is the number of transmit antennas). If the channel is not known to the t r ansmi t t e r the best strategy would be to exploit transmit diversity for each layer. This ensures, that all layer achieve full diversity of the MIMO-channel and therefore would perform equally. D-BLAST [l] is able to exploit the transmit diversity through channel coding and multiplexing parts of the code words over different antennas. MultiStratum-Space-Time-Coding [2] (MSSTC) uses Space-TimeBlock-Codes (STBC) for the same purpose. MSSTC suffers from rate loss for more than two transmit antennas due to the Space-Time-Block-Coding. D-BLAST needs guard intervals which leads also to some capacity loss. Multi-StratumPermutation-Codes (MSPC) [3] avoid this rate loss by using orthogonal transformations over space (antennas) and time (successive symbols). This ensures a good reparability of the layers a t the receiver. Remark, that different from BLAST approaches, all antennas are used all time even if M < N T , whereas BLAST would have to leave out antennas for transmission in this case. A detailed description of the construction of MSPC can be found in [3] .

Integrated broadband mobile system (IBMS) featuring smart antennas

IBMS is a concept for future mobile communication systems to provide a large range of data rates with different degrees of mobility. The integration of heterogeneous services and communication systems requires a common Network Access and Connectivity CHannel (NACCH) for basic signaling to provide permanent network access. Smart Antennas are utilized to adaptively enable a trade-off between mobility and data rate.

Hardware in a loop-a system prototyping platform for MIMO-approaches

The hardware in a loop concept is introduced for the design of wireless communication chipsets. The aim is to verify the algorithm design followed by extensive software simulations of the proposed algorithms. Signalion provides a rapid prototyping platform to enable this algorithm verification on a hardware. This approach helps to identify design errors and implementation faults. The hardware platform can be used for complex PHY implementations such as MIMO-OFDM modems.

A stochastic vector channel model-implementation and verification

The simulation of space-time receivers for wireless communication systems requires a spatial channel model which reasonably characterizes the time-variant effects of the mobile radio channel. This paper describes a space-time vector channel model with stochastic fading simulation and its effective implementation for bit-level simulations. Measurements have been analyzed in order to verify the assumptions of the channel model.