Peter Zillmann

Dirty RF: a new paradigm

The implementation challenge for new low-cost low-power wireless modem transceivers has continuously been growing with increased modem performance, bandwidth, and carrier frequency. Up to now we have been designing transceivers in a way that we are able to keep the analog (RF) problem domain widely separated from the digital signal processing design. However, with todays deep sub-micron technology, analog impairments-dirt effects-are reaching a new problem level which requires a paradigm shift in the design of transceivers. Examples of these impairments are phase noise, non-linearities, IQ imbalance, ADC impairments, etc. In the world of dirty RF we assume to design digital signal processing such that we can cope with a new level of impairments, allowing lee-way in the requirements set on future RF sub-systems. This paper gives an overview of the topic and presents analytical evaluations of the performance losses due to RF impairments as well as algorithms that allow to live with imperfect RF by compensating the resulting error effects using digital baseband processing

Dirty RF: A New Paradigm

The implementation challenge for new low-cost low-power wireless modem transceivers has continuously been growing with increased modem performance, bandwidth, and carrier frequency. Up to now we have been designing transceivers in a way that we are able to keep the analog (RF) problem domain widely separated from the digital signal processing design. However, with today’s deep sub-micron technology, analog impairments – “dirt effects” – are reaching a new problem level which requires a paradigm shift in the design of transceivers. Examples of these impairments are phase noise, non-linearities, I/Q imbalance, ADC impairments, etc. In the world of “Dirty RF” we assume to design digital signal processing such that we can cope with a new level of impairments, allowing lee-way in the requirements set on future RF sub-systems. This paper gives an overview of the topic and presents analytical evaluations of the performance losses due to RF impairments as well as algorithms that allow to live with imperfect RF by compensating the resulting error effects using digital baseband processing.

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.

On the capacity of multicarrier transmission over nonlinear channels

This paper presents new results on the achievable capacity of multicarrier systems impaired by clipping at the transmitter. A general framework for capacity analysis of multicarrier systems with complex baseband signals is derived, based on the mutual information of the transmitted and received signals. Specific results are given for the soft limiter nonlinearity with different values of the input power backoff (IBO), and for the hard limiter nonlinearity. These capacity results are a true upper bound for multicarrier systems with a large number of subcarriers and can be used for evaluation of receive algorithms for nonlinearly distorted multicarrier signals. It is shown that clipping results only in a small capacity loss even for low IBO.

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.

Equalisation of MIMO-OFDM Signals Affected by Phase Noise and Clipping and Filtering

Combined peak-to-average power ratio (PAPR) reduction and Phase Noise mitigation 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 addition, phase noise caused by non ideal oscillators, results in interference among the subcarriers. Thus, an appropriate correction method compensating both effects has to be considered at the receiver. However, an ideal maximum likelihood based impairment compensation algorithm is computationally infeasible. In this work a soft correction method is proposed, resulting in a substantial reduction of both impairments. Moreover, an expression of the remaining noise is given, which is essential for advanced equalisation techniques.

Soft Detection and Decoding of Clipped and Filtered COFDM Signals

Clipping and filtering is an attractive method for the reduction of the PAPR of OFDM signals before transmission. However, the resulting distortion noise impacts the error rate performance. An iterative receive algorithm employing soft modulation and soft input-soft output (SISO) decoding is presented, and its coded frame error rate (FER) performance over both AWGN and frequency-selective fading channels is evaluated. The performance of an approach with reduced complexity is also shown.

Turbo Equalization for Clipped and Filtered COFDM Signals

Clipping and filtering is an attractive method for the reduction of the PAPR of OFDM signals before transmission. However, the resulting in-band distortion noise impacts the error rate performance. Since the optimum soft iterative equalization scheme has a prohibitively high computational complexity, we present two equalization algorithms for clipped and filtered COFDM signals with reduced complexity. The coded frame error rate (FER) performance over both AWGN and frequency-selective fading channels is evaluated for typical OFDM system parameters.

A Detection Algorithm for Clipped OFDM Signals Using the IDFT-Matrix

A major drawback of the orthogonal frequency division multiplex (OFDM) principle is the high dynamic range of the transmit signal. The transmit power amplifier (PA) and other elements in the signal path have to operate at high input power backoff (IBO), which decreases the efficiency of the PA and leads to higher costs. This paper presents a novel receive algorithm for OFDM signals with limited dynamic range. The received signal in the time domain (TD) is examined in order to estimate those samples which have not been distorted by the PA. In the frequency domain (FD), some of the most reliable subcarrier symbols are detected. The combination of the information from TD as well as from FD allows the computation of the remaining subcarrier symbols by using a truncated version of an inverse discrete Fourier transform (IDFT) matrix. The simulation results show that this receive algorithm significantly improves the error rate of OFDM systems impaired by clipping at the transmitter.