arXiv subjects

Josef A. Nossek

Publications and source records attributed to Josef A. Nossek.

At least 55 records · Page 3Linked to original sources

arXiv2017

Minimum BER Precoding in 1-Bit Massive MIMO Systems

1-bit digital-to-analog (DACs) and analog-to-digital converters (ADCs) are gaining more interest in massive MIMO systems for economical and computational efficiency. We present a new precoding technique to mitigate the inter-user-interference (IUI) and the channel distortions in a 1-bit downlink MUMISO system with QPSK symbols. The transmit signal vector is optimized taking into account the 1-bit quantization. We develop a sort of mapping based on a look-up table (LUT) between the input signal and the transmit signal. The LUT is updated for each channel realization. Simulation results show a significant gain in terms of the uncoded bit-error-ratio (BER) compared to the existing linear precoding techniques.

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arXiv2017

Achievable Rate and Energy Efficiency of Hybrid and Digital Beamforming Receivers with Low Resolution ADC

For 5G it will be important to leverage the available millimeter wave spectrum. To achieve an approximately omni- directional coverage with a similar effective antenna aperture compared to state of the art cellular systems, an antenna array is required at both the mobile and basestation. Due to the large bandwidth and inefficient amplifiers available in CMOS for mmWave, the analog front-end of the receiver with a large number of antennas becomes especially power hungry. Two main solutions exist to reduce the power consumption: Hybrid BeamForming (HBF) and Digital BeamForming (DBF) with low resolution ADC. Hybrid beamforming can also be combined with low resolution ADCs. This paper compares the spectral and energy efficiency based on the chosen RF-frontend configuration. A channel with multipath propagation is used. In contrast to previous publication, we take the spatial correlation of the quantization noise into account. We show that the low resolution ADC are robust to small Automatic Gain Control (AGC) imperfections. We showed that in the low SNR regime the performance of DBF even with 1-2 bit resolution outperforms HBF. If we consider the relationship of spectral and energy efficiency then DBF with 3-5 bits resolution achieves the best ratio of spectral efficiency per power consumption of the RF receiver frontend over a very wide SNR region. The power consumption model is based on components reported in literature.

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arXiv2017

Arbitrary Beam Synthesis of Different Hybrid Beamforming Systems

For future mmWave mobile communication systems the use of analog/hybrid beamforming is envisioned be a key as- pect. The synthesis of beams is a key technology of enable the best possible operation during beamsearch, data transmission and MU MIMO operation. The developed method for synthesizing beams is based on previous work in radar technology considering only phase array antennas. With this technique it is possible to generate a desired beam of any shape with the constraints of the desired target transceiver antenna frontend. It is not constraint to a certain antenna array geometry, but can handle 1d, 2d and even 3d antenna array geometries like cylindric arrays. The numerical examples show that the method can synthesize beams by considering a user defined tradeoff between gain, transition width and passband ripples.

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arXiv2017

Massive MIMO Downlink 1-Bit Precoding with Linear Programming for PSK Signaling

Quantized massive multiple-input-multiple-output (MIMO) systems are gaining more interest due to their power efficiency. We present a new precoding technique to mitigate the multi-user interference and the quantization distortions in a downlink multi-user (MU) multiple-input-single-output (MISO) system with 1-bit quantization at the transmitter. This work is restricted to PSK modulation schemes. The transmit signal vector is optimized for every desired received vector taking into account the 1-bit quantization. The optimization is based on maximizing the safety margin to the decision thresholds of the PSK modulation. Simulation results show a significant gain in terms of the uncoded bit-error-ratio (BER) compared to the existing linear precoding techniques.

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arXiv2017

Precoding under Instantaneous Per-Antenna Peak Power Constraint

We consider a multi-user (MU) multiple-input-single-output (MISO) downlink system with M single-antenna users and N transmit antennas with a nonlinear power amplifier (PA) at each antenna. Instead of emitting constant envelope (CE) signals from the antennas to have highly power efficient PAs, we relax the CE constraint and allow the transmit signals to have instantaneous power less than or equal to the available power at each PA. The PA power efficiency decreases but simulation results show that the same performance in terms of bit-error-ratio (BER) can be achieved with less transmitted power and less PA power consumption. We propose a linear and a nonlinear precoder design to mitigate the multi-user interference (MUI) under the constraint of a maximal instantaneous per-antenna peak power.

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arXiv2016

16 QAM Communication with 1-Bit Transmitters

We present a novel non-linear precoding technique for the transmission of 16 quadrature amplitude modulation (QAM) symbols in a 1-bit massive multi-user (MU) multipleinput- single-output (MISO) downlink system. We deploy low resolution digital-to-analog converters (DACs) at the transmitter for the sake of decreasing the high energy consumption related to the massive MISO system. To mitigate the multi-user interference (MUI) and the distortions due to the low resolution DACs, the minimum bit error ratio (MBER) precoder was introduced in previous work. However, this precoder technique is restricted to quadrature phase shift keying (QPSK) signaling. Our approach consists in upgrading this method to the transmission of 16 QAM symbols. Simulation results show that the performance in terms of uncoded BER is significantly improved for larger massive MISO gain.

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arXiv2016

Chromatic Dispersion Compensation Using Filter Bank Based Complex-Valued All-Pass Filter

A long-haul transmission of 100 Gb/s without optical chromatic-dispersion (CD) compensation provides a range of benefits regarding cost effectiveness, power budget, and nonlinearity tolerance. The channel memory is largely dominated by CD in this case with an intersymbol-interference spread of more than 100 symbol durations. In this paper, we propose CD equalization technique based on nonmaximally decimated discrete Fourier transform (NMDFT) filter bank (FB) with non-trivial prototype filter and complex-valued infinite impulse response (IIR) all-pass filter per sub-band. The design of the sub-band IIR all-pass filter is based on minimizing the mean square error (MSE) in group delay and phase cost functions in an optimization framework. Necessary conditions are derived and incorporated in a multi-step and multi-band optimization framework to ensure the stability of the resulting IIR filter. It is shown that the complexity of the proposed method grows logarithmically with the channel memory, therefore, larger CD values can be tolerated with our approach.

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arXiv2016

DOA Parameter Estimation with 1-bit Quantization - Bounds, Methods and the Exponential Replacement

While 1-bit analog-to-digital conversion (ADC) allows to significantly reduce the analog complexity of wireless receive systems, using the exact likelihood function of the hard-limiting system model in order to obtain efficient algorithms in the digital domain can make 1-bit signal processing challenging. If the signal model before the quantizer consists of correlated Gaussian random variables, the tail probability for a multivariate Gaussian distribution with N dimensions (general orthant probability) is required in order to formulate the likelihood function of the quantizer output. As a closed-form expression for the general orthant probability is an open mathematical problem, formulation of efficient processing methods for correlated and quantized data and an analytical performance assessment have, despite their high practical relevance, only found limited attention in the literature on quantized estimation theory. Here we review the approach of replacing the original system model by an equivalent distribution within the exponential family. For 1-bit signal processing, this allows to circumvent calculation of the general orthant probability and gives access to a conservative approximation of the receive likelihood. For the application of blind direction-of-arrival (DOA) parameter estimation with an array of K sensors, each performing 1-bit quantization, we demonstrate how the exponential replacement enables to formulate a pessimistic version of the Cramér-Rao lower bound (CRLB) and to derive an asymptotically achieving conservative maximum-likelihood estimator (CMLE). The 1-bit DOA performance analysis based on the pessimistic CRLB points out that a low-complexity radio front-end design with 1-bit ADC is in particular suitable for blind wireless DOA estimation with a large number of array elements operating in the medium SNR regime.

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arXiv2016

Measurement-driven Quality Assessment of Nonlinear Systems by Exponential Replacement

We discuss the problem how to determine the quality of a nonlinear system with respect to a measurement task. Due to amplification, filtering, quantization and internal noise sources physical measurement equipment in general exhibits a nonlinear and random input-to-output behaviour. This usually makes it impossible to accurately describe the underlying statistical system model. When the individual operations are all known and deterministic, one can resort to approximations of the input-to-output function. The problem becomes challenging when the processing chain is not exactly known or contains nonlinear random effects. Then one has to approximate the output distribution in an empirical way. Here we show that by measuring the first two sample moments of an arbitrary set of output transformations in a calibrated setup, the output distribution of the actual system can be approximated by an equivalent exponential family distribution. This method has the property that the resulting approximation of the statistical system model is guaranteed to be pessimistic in an estimation theoretic sense. We show this by proving that an equivalent exponential family distribution in general exhibits a lower Fisher information measure than the original system model. With various examples and a model matching step we demonstrate how this estimation theoretic aspect can be exploited in practice in order to obtain a conservative measurement-driven quality assessment method for nonlinear measurement systems.

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arXiv2016

Performance Analysis for Pilot-based 1-bit Channel Estimation with Unknown Quantization Threshold

Parameter estimation using quantized observations is of importance in many practical applications. Under a symmetric $1$-bit setup, consisting of a zero-threshold hard-limiter, it is well known that the large sample performance loss for low signal-to-noise ratios (SNRs) is moderate ($\frac{2}π$ or $-1.96$dB). This makes low-complexity analog-to-digital converters (ADCs) with $1$-bit resolution a promising solution for future wireless communications and signal processing devices. However, hardware imperfections and external effects introduce the quantizer with an unknown hard-limiting level different from zero. In this paper, the performance loss associated with pilot-based channel estimation, subject to an asymmetric hard limiter with unknown offset, is studied under two setups. The analysis is carried out via the Cramér-Rao lower bound (CRLB) and an expected CRLB for a setup with random parameter. Our findings show that the unknown threshold leads to an additional information loss, which vanishes for low SNR values or when the offset is close to zero.

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arXiv2015

Asymptotic Performance Analysis for 1-bit Bayesian Smoothing

Energy-efficient signal processing systems require estimation methods operating on data collected with low-complexity devices. Using analog-to-digital converters (ADC) with $1$-bit amplitude resolution has been identified as a possible option in order to obtain low power consumption. The $1$-bit performance loss, in comparison to an ideal receiver with $\infty$-bit ADC, is well-established and moderate for low SNR applications ($2/π$ or $-1.96$ dB). Recently it has been shown that for parameter estimation with state-space models the $1$-bit performance loss with Bayesian filtering can be significantly smaller ($\sqrt{2/π}$ or $-0.98$ dB). Here we extend the analysis to Bayesian smoothing where additional measurements are used to reconstruct the current state of the system parameter. Our results show that a $1$-bit receiver performing smoothing is able to outperform an ideal $\infty$-bit system carrying out filtering by the cost of an additional processing delay $Δ$.

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arXiv2015

Asymptotic Parameter Tracking Performance with Measurement Data of 1-bit Resolution

The problem of signal parameter estimation and tracking with measurement data of low resolution is considered. In comparison to an ideal receiver with infinite receive resolution, the performance loss of a simplistic receiver with 1-bit resolution is investigated. For the case where the measurement data is preprocessed by a symmetric hard-limiting device with 1-bit output, it is well-understood that the performance for low SNR channel parameter estimation degrades moderately by 2/pi (-1.96 dB). Here we show that the 1-bit quantization loss can be significantly smaller if information about the temporal evolution of the channel parameters is taken into account in the form of a state-space model. By the analysis of a Bayesian bound for the achievable tracking performance, we attain the result that the quantization loss in dB is in general smaller by a factor of two if the channel evolution is slow. For the low SNR regime, this is equivalent to a reduced loss of sqrt(2/pi) (-0.98 dB). By simulating non-linear filtering algorithms for a satellite-based ranging application (GPS) and a UWB channel estimation problem, both with low-complexity 1-bit analog-to-digital converter (ADC) at the receiver, we verify that the analytical characterization of the tracking error is accurate. This shows that the performance loss due to observations with low amplitude resolution can, in practice, be much less pronounced than indicated by classical results. Finally, we discuss the implication of the result for medium SNR applications like channel estimation in the context of mobile wireless communications.

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arXiv2015

Compensation of Amplifier Distortion for OFDM signals based on Iterative Hard Thresholding

The mitigation of nonlinear distortion caused by power amplifiers (PA) in Orthogonal Frequency Division Multiplexing (OFDM) systems is an essential issue to enable energy efficient operation. In this work we proposed a new algorithm for receiver-based clipping estimation in OFDM systems that combines the Iterative Hard Thresholding (IHT) method with a weighting corresponding to the estimated probability of clipping. Thereby a more general amplifier input-output characteristic is considered, which is assumed to be unknown at the receiver side. Further, we avoid the use of dedicated subcarriers and formulate the recovery problem solely on reliably detected sub-carriers. Through simulations, we show that the proposed technique achieves a better complexity-performance tradeoff compared to existing methods.

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arXiv2014

Overdemodulation for High-Performance Receivers with Low-Resolution ADC

The design of the analog demodulator for receivers with low-resolution analog-to-digital converters (ADC) is investigated. For infinite ADC resolution, demodulation to baseband with M = 2 orthogonal sinusoidal functions (quadrature demodulation) is an optimum design choice. For receive systems which are restricted to ADC with low amplitude resolution we show here that this classical demodulation approach is suboptimal. To this end we analyze the theoretical channel parameter estimation performance based on a simple pessimistic characterization of the Fisher information measure when forming M > 2 analog demodulation channels prior to an ADC with 1-bit amplitude resolution. In order to emphasize that this inside is also true for communication problems, we provide an additional discussion on the behavior of the Shannon information measure under overdemodulation and 1-bit quantization.

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arXiv2014

Information Theoretic Analysis of Concurrent Information Transfer and Power Gain

In this paper, we analyze the fundamental trade-off between information transfer and power gain by means of an information-theoretic framework in communications circuits. This analysis is of interest as many of today's applications require that maximum information and maximum signal power are extracted (or transferred) through the circuit at the same time for further processing so that a compromise concerning the signal spectral shape as well as the matching network has to be found. To this end, the optimization framework is applied to a two-port circuit, which is used as an abstraction for a broadband amplifier. Thereby, we characterize the involved Pareto bound by considering different optimization problems. The first one aims at optimizing the input power spectral density (PSD) as well as the source and load admittances, whereas the second approach assumes the PSD to be fixed and uniformly distributed within a fixed bandwidth and optimizes the source and load admittances only. Moreover, we will show that additional matching networks may help to improve the trade-off.

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arXiv2014

A Lower Bound for the Fisher Information Measure

The problem how to approximately determine the absolute value of the Fisher information measure for a general parametric probabilistic system is considered. Having available the first and second moment of the system output in a parametric form, it is shown that the information measure can be bounded from below through a replacement of the original system by a Gaussian system with equivalent moments. The presented technique is applied to a system of practical importance and the potential quality of the bound is demonstrated.

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arXiv2010

Analysis of 1-bit Output Noncoherent Fading Channels in the Low SNR Regime

We consider general multi-antenna fading channels with coarsely quantized outputs, where the channel is unknown to the transmitter and receiver. This analysis is of interest in the context of sensor network communication where low power and low cost are key requirements (e.g. standard IEEE 802.15.4 applications). This is also motivated by highly energy constrained communications devices where sampling the signal may be more energy consuming than processing or transmitting it. Therefore the analog-to-digital converters (ADCs) for such applications should be low-resolution, in order to reduce their cost and power consumption. In this paper, we consider the extreme case of only 1-bit ADC for each receive signal component. We derive asymptotics of the mutual information up to the second order in the signal-to-noise ratio (SNR) under average and peak power constraints and study the impact of quantization. We show that up to second order in SNR, the mutual information of a system with two-level (sign) output signals incorporates only a power penalty factor of almost 1.96 dB compared to the system with infinite resolution for all channels of practical interest. This generalizes a recent result for the coherent case.

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arXiv2010

Achieving near-Capacity on Large Discrete Memoryless Channels

We propose a method to increase the capacity achieved by uniform prior in discrete memoryless channels (DMC) with high input cardinality. It consists in appropriately reducing the input set. Different design criteria of the input subset are discussed. We develop an efficient algorithm to solve this problem based on the maximization of the cut-off rate. The method is applied to a mono-bit transceiver MIMO system, and it is shown that the capacity can be approached within tenths of a dB by employing standard binary codes while avoiding the use of distribution shapers.

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