Steffen Bittner

GFDM - Generalized Frequency Division Multiplexing

This paper presents the GFDM system, a generalized digital multi-carrier transceiver concept. GFDM is based on traditional filter bank multi-branch multi- carrier concepts which are now implemented digitally. Our GFDM approach exhibits some attractive features which are of particular importance for scenarios exhibiting high degrees of spectrum fragmentation. Spectrum fragmentation is a typical technical challenge of digital dividend use cases, exploiting spectrum white spaces in the TV UHF bands which are located in close proximity to allocated spectrum. Specifically, the GFDM features are a lower PAPR compared to OFDM, a ultra-low out-of- band radiation due adjustable Tx-filtering and last but not least a block-based transmission using cyclic prefix insertion and efficient FFT-based equalization. GFDM enables frequency and time domain multi-user scheduling comparable to OFDM and provides an efficient alternative for white space aggregation even in heavily fragmented spectrum regions.

Analysis of and compensation for non-ideal RoF links in DAS [Coordinated and Distributed MIMO]

Distributed antenna systems have been found to be an elegant solution for the problems arising in high-data-rate wireless communication, particularly in large service areas. This article considers radio over fiber links as an essential part of the DAS, connecting the central unit with the remote antenna units. In particular, we analyze and discuss delays and nonlinearities stemming from the RoF links. In addition, we study the compensation for these impairments. Our studies indicate that the RoF links are a viable and cost-effective solution for implementing the DAS, although some of the RoF link non-idealities require compensation.

Iterative Phase Noise Mitigation in MIMO-OFDM Systems with Pilot Aided Channel Estimation

The use of multiple transmit and receive antennas in combination with multicarrier modulation, e.g. MIMO-OFDM, is a very promising technique for future wireless communication systems. In this work we investigate preamble based channel estimation under the presence of phase noise. Neglecting the influence of phase noise in the design of the preamble will lead to a significant loss in accuracy of the channel estimation. The solution involves an analysis of the mean square error approximation of the channel estimation and incorporating the result in the phase noise mitigation and data detection step.

Exploiting Phase Noise Properties in the Design of MIMO-OFDM Receivers

Phase noise (PN) is a serious challenge for multi- carrier systems as it can drastically decrease the system performance. In order to tackle this problem, recent contributions propose iterative approaches which compensate both the common phase error and the intercarrier interference (ICI) resulting from PN. However, the fact that the ICI is not Gaussian distributed has so far not been taken into account in the calculation of detector soft output. Furthermore, the ICI is typically approximated by a truncated Fourier series, implicitly assuming a periodicity of the PN trajectory - which is in general not the case. In this paper we will address these problems and show that taking the PN properties properly into account allows to significantly improve the system performance.

Low Complexity Soft Interference Cancellation for MIMO-Systems

Iterative equalization has emerged as an efficient means of achieving near-capacity detection performance in multiple-antenna (MIMO) systems. However, many proposed detection strategies still exhibit a very high complexity which may render them unsuited for practical implementation. In this paper, we show that the appropriate use of a-priori knowledge during iterative equalization based on soft interference cancellation enables to drastically reduce detection complexity. More specifically, we propose to take into account only a subset of constellation points in the calculation of detector soft output, by considering the vicinities of the interference reduced received signal and the constellation points supported by the a-priori knowledge. Additionally, a threshold rule on symbol probabilities is used to reduce complexity in the calculation of soft symbols and residual noise during soft interference cancelling. Our results show that the computational effort required for detection can be lowered by as much as 50% for 16-QAM and 96% for higher order constellations (64-256-QAM), without any significant loss in performance

Joint Iterative Transmitter and Receiver Phase Noise Correction using Soft Information

In this paper we discuss the effect of phase noise at both, transmitter and receiver in an OFDM system. We study an iterative equalization system at the receiver. The system is based on a joint linear MMSE estimation of the transmitter and receiver phase noise. We propose a receiver module which can be considered as a serial concatenation of an outer decoder with an inner phase noise correction/metric computation block. For intercarrier interference (ICI) suppression we introduce a method to only use the most reliable decoded symbols, which results in a significant performance improvement. The performance is shown by simulation results for different oscillator qualities and an ETSI HiperLan A channel.

Oscillator Phase Noise compensation using Kalman tracking

Phase Noise (PN) is a serious challenge in wireless transmission systems as it can cause significant degradation of the system performance. Recent publications propose iterative PN compensation algorithms for single or multicarrier systems. In this paper we will present an unscented Kalman filter PN tracking algorithm working in time domain, which is independent of the underlying system. Furthermore, we propose a reduced complexity tracking algorithm, where we perform an interpolation between the estimated PN samples. Simulation results for an OFDM setup show that by using this technique the system performance can be improved significantly.

Phase Noise Suppression in OFDM with Spatial Multiplexing

A very promising way to achieve high spectral efficiency in wireless communication is the use of multiple transmit and receive antennas. However, in combination with multicarrier modulation, e.g. MIMO-OFDM, the performance of such a system can be drastically limited due to the existence of RF imperfections such as oscillator phase noise. Many methods for phase noise compensations in a single antenna environment have been developed, whereas only a few deal with the problem in a MIMO case. Those contributions mainly discuss the common phase error (CPE) correction. In this work we extend the CPE correction and perform a linear minimum mean square error (LMMSE) estimation of higher order phase noise harmonics in order to compensate intercarrier interference (ICI) in a multi antenna system. In a coded multi antenna environment it is common to perform detector-decoder iterations which lead to an improved performance behavior. During the iterations we use the a-priori knowledge provided by the decoder to improve the phase noise estimation. This is done by using only the most reliable symbols for performing the LMMSE estimate. As for the detection we use a simple MMSE equalizer where we use the general expression and adapt the noise covariance matrix according to the remaining ICI. Finally the performance is shown by simulation results for an IEEE 802.11n E channel.

Iterative Correction of Clipped and Filtered Spatially Multiplexed OFDM Signals

Peak-to-Average Power Ratio (PAPR) reduction in multicarrier systems with multiple transmit and receive antennas is considered. One attractive method for reducing the PAPR is to use clipping and filtering in the digital domain at the transmitter, which results in signal distortion prior to transmission. In this work, soft clipping correction at the receiver, recently proposed in literature, is extended to multi antenna systems. It is shown that taking the clipping noise into consideration leads to a significant performance improvement. The behaviour of the clipping correction algorithm is studied by error rates as well as EXIT charts. Moreover, the low complexity of the proposed scheme makes it attractive for various kinds of multi antenna detection algorithms.

List Sequential MIMO Detection: Noise Bias Term and Partial Path Augmentation

Near-capacity performance can be achieved in multiple-antenna systems by using a list sequential (LISS) detector for iterative equalization. Path augmentation is known to increase the performance of this detector, while a so-called bias term has been used to reduce its computational complexity, in applications other than MIMO detection. In this work, we extend the LISS MIMO detector [1] to incorporate different implementations of the bias term. We show that following the traditional approach of using an auxiliary stack for this purpose leads to a strong narrowing of the search tree, but also to a significant performance degradation, due to a reduced quality of the detector soft output. We therefore propose to use a so-called noise bias term instead, which can be implemented with negligible effort, significantly reduces the size of the search tree, but allows for almost retaining detector performance. Finally, we demonstrate that the extension of only a small fraction of the incomplete stack entries is sufficient to leverage the full gains of path augmentation, thus enabling further substantial savings in computational complexity.