Ralf Eickhoff

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In this paper, we study transmission schemes for a novel OFDM-based MIMO system which performs adaptive signal combining in radio-frequency (RF). Specifically, we consider the problem of selecting the linear precoder and the transmit and receive RF weights (or beamformers) for minimizing the bit error rate (BER) under the assumption of perfect channel(More)
In this paper, we study beamforming schemes for a novel MIMO transceiver, which performs adaptive signal combining in the radio-frequency domain. Assuming perfect channel knowledge at both the transmit and receive sides, we consider the problem of selecting the transmit and receive RF beamformers that maximize the capacity (MaxCAP criterion) of the system(More)
The transmission phase variations versus gain in common emitter and common base amplifiers are analyzed revealing that these stages can be tuned to yield opposite phase characteristics versus gain. By cascading these two stages, e.g., on the basis of a cascode, and optimizing added feedback elements, it is possible to compensate these phase variations. A(More)
The challenge of future nanoelectronic applications, e.g. in quantum computing or in molecular computing, is to assure reliable computation facing a growing number of malfunctioning and failing computational units. Modeled on biology artificial neural networks are intended to be one preferred architecture for these applications because their architectures(More)
In this paper, we study beamforming schemes for a novel MIMO transceiver, which performs adaptive signal combining in the radio-frequency (RF) domain. Assuming perfect channel knowledge at the receiver side, we consider the problem of designing the transmit and receive RF beamformers under orthogonal frequency division multiplexing (OFDM) transmissions. In(More)
Artificial neural networks are used in various applications and research areas. Mathematically inspired approaches use these types of networks to solve complex classification or function approximation tasks whereas biologically motivated models attempt to adapt desired properties from biology such as robustness or fault tolerance to technical systems and(More)
An architecture for implementing the maximum ratio combining (MRC) in the radio-frequency (RF) domain has recently been proposed based on applying vector modulators at each branch. In this paper we study a simplified architecture, which eliminates the need for IQ mixing and reduces the number of adders. Interestingly, the optimal beamforming solution,(More)