Wolfgang H. Gerstacker

Multiple-antenna techniques for wireless communications - a comprehensive literature survey

The use of multiple antennas for wireless communication systems has gained overwhelming interest during the last decade - both in academia and industry. Multiple antennas can be utilized in order to accomplish a multiplexing gain, a diversity gain, or an antenna gain, thus enhancing the bit rate, the error performance, or the signal-to-noise-plus-interference ratio of wireless systems, respectively. With an enormous amount of yearly publications, the field of multiple-antenna systems, often called multiple-input multiple-output (MIMO) systems, has evolved rapidly. To date, there are numerous papers on the performance limits of MIMO systems, and an abundance of transmitter and receiver concepts has been proposed. The objective of this literature survey is to provide non-specialists working in the general area of digital communications with a comprehensive overview of this exciting research field. To this end, the last ten years of research efforts are recapitulated, with focus on spatial multiplexing and spatial diversity techniques. In particular, topics such as transmitter and receiver structures, channel coding, MIMO techniques for frequency-selective fading channels, diversity reception and space-time coding techniques, differential and non-coherent schemes, beamforming techniques and closed-loop MIMO techniques, cooperative diversity schemes, as well as practical aspects influencing the performance of multiple-antenna systems are addressed. Although the list of references is certainly not intended to be exhaustive, the publications cited will serve as a good starting point for further reading.

Equalization concepts for EDGE

An equalization concept for the novel radio access scheme Enhanced Data rates for GSM Evolution (EDGE) is proposed by which high performance can be obtained at moderate computational complexity. Because high-level modulation is employed in EDGE, optimum equalization as usually performed in Global System for Mobile Communications (GSM) receivers is too complex and suboptimum schemes have to be considered. It is shown that delayed decision-feedback sequence estimation (DDFSE) and reduced-state sequence estimation (RSSE) are promising candidates. For various channel profiles, approximations for the bit error rate of these suboptimum equalization techniques are given and compared with simulation results for DDFSE. It turns out that a discrete-time prefilter creating a minimum-phase overall impulse response is indispensable for a favorable tradeoff between performance and complexity. Additionally, the influence of channel estimation and of the receiver input filter is investigated and the reasons for performance degradation compared to the additive white Gaussian noise channel are indicated. Finally, the overall system performance attainable with the proposed equalization concept is determined for transmission with channel coding.

On prefilter computation for reduced-state equalization

In advanced time-division multiple-access (TDMA) mobile communications systems, reduced-state equalization algorithms have to be employed because high-level modulation is used in order to improve spectral efficiency. Reduced-state equalizers yield only high performance, if the overall discrete-time system to be equalized is minimum-phase. Therefore, in general, a discrete-time prefilter has to be inserted in front of equalization. For prefilter computation, several approaches are investigated in this paper. For the finite impulse response (FIR) prefilter case, which seems to be more relevant for practical applications than the in finite impulse response case, we discuss a method based on minimum mean-squared error decision-feedback equalization and a novel approach based on linear prediction (LP). The LP method seems to be very robust and requires an only moderate amount of computational complexity. Here, the prefilter consists of the cascade of a channel-matched filter and a prediction-error filter, which may be viewed as a finite-length approximation to the noise whitening part of the ideal prefilter transfer function. A key observation of the paper is that the proposed cascaded structure enables a very efficient prefilter computation because a prediction-error filter can be calculated via the Levinson-Durbin algorithm. Simulation results are given, which demonstrate that the performance of reduced-state equalization with proper FIR prefiltering is close to that of equalization combined with ideal all-pass prefiltering. Furthermore, it is shown that high performance can be obtained for TDMA mobile communications systems, if the LP scheme is employed for prefiltering.

Data-aided and blind stochastic gradient algorithms for widely linear MMSE MAI suppression for DS-CDMA

In this paper, three novel stochastic gradient algorithms for adjustment of the widely linear (WL) minimum mean-squared error (MMSE) filter for multiple access interference (MAI) suppression for direct-sequence code-division multiple access (DS-CDMA) are introduced and analyzed. In particular, we derive a data-aided WL least-mean-square (LMS) algorithm, a blind WL minimum-output-energy (MOE) algorithm, and a WL blind LMS (BLMS) algorithm. We give analytical expressions for the steady-state signal-to-interference-plus-noise ratios (SINRs) of the proposed WL algorithms, and we also investigate their speed of convergence. Wherever possible, comparisons with the corresponding linear adaptive algorithms are made. Both analytical considerations and simulations show, in good agreement, the superiority of the novel WL adaptive algorithms. Nevertheless, all proposed WL algorithms require a slightly lower computational complexity than their linear counterparts.

An efficient method for prefilter computation for reduced-state equalization

In advanced TDMA mobile communications systems, reduced-state equalization algorithms have to be employed because a high-level modulation is used in order to improve the spectral efficiency. Such equalizers only have a high performance, if the overall discrete-time system to be equalized is minimum-phase. Therefore, in general, a discrete-time prefilter has to be inserted in front of equalization. In the literature, several approaches have been proposed for computation of a suitable FIR or IIR prefilter. We present an approach for FIR prefilter computation, which is quite robust and requires an only moderate computational complexity. The prefilter consists of the cascade of a channel-matched filter and a prediction-error filter, which can be calculated via the Levinson-Durbin algorithm. Simulation results are given, which demonstrate that the performance of the proposed approach is essentially equivalent to the case of reduced-state equalization combined with ideal allpass prefiltering.

On the capacity loss due to separation of detection and decoding

The performance loss due to separation of detection and decoding on the binary-input additive white Gaussian noise (AWGN) channel is quantified in terms of mutual information. Results are reported for both the code-division multiple-access (CDMA) channel in the large system limit and the intersymbol interference (ISI) channel. The results for CDMA rely on the replica method developed in statistical mechanics. It is shown that a previous result of Shamai and Verdu found for Gaussian input alphabet holds also for binary input alphabets. For the ISI channel, the performance loss is calculated via the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. Comparisons are made to the capacity of separate detection and decoding using suboptimum detectors such as a decision-feedback equalizer.

Equalization concepts for Alamouti's space-time block code

In this paper, we develop receiver concepts for transmission with space-time block codes (STBCs) over frequency-selective fading channels. The focus lies on Alamoutis space-time block-coding scheme, but the results may be generalized to other STBCs as well. We show that a straightforward combination of conventional equalizers and a space-time block decoder is only possible if at least as many receive antennas as transmit antennas are employed, but not for the practically interesting case of pure transmit diversity, for which space-time coding had been originally developed. This restriction is circumvented by our approach. Here, the structural properties of the transmit signal of space-time block coding, which is shown to be improper (rotationally variant), are fully used. For this, equalizers with widely linear (WL) processing are designed, such as a WL equalizer, a decision-feedback equalizer with WL feedforward and feedback filtering, and a delayed decision-feedback sequence estimator with WL prefiltering. Simulation results demonstrate that the proposed concepts may be successfully employed in an enhanced data rates for GSM evolution (EDGE) receiver, especially for pure transmit diversity. Here, significant gains can be observed, compared with a conventional single-input single-output transmission.

A single antenna interference cancellation algorithm for increased gsm capacity

In mobile communications networks, system capacity is often limited by cochannel interference. Therefore, receiver algorithms for cancellation of cochannel interference have recently attracted much interest. At the mobile terminal, algorithms can usually rely only on one received signal delivered by a single receive antenna. In this letter, a low-complexity single antenna interference cancellation (SAIC) algorithm for real-valued modulation formats referred to as mono interference cancellation (MIC) is introduced which is well suited for practical applications. Field trials in commercial GSM networks using prototype terminals with the proposed MIC algorithm have demonstrated that the novel concept may yield capacity improvements of up to 80%. The underlying principle is also beneficial for adjacent channel interference and receivers with multiple antennas. Furthermore, in coverage-limited scenarios, there is no performance degradation compared with conventional receivers

Dynamics limited precoding, shaping, and blind equalization for fast digital transmission over twisted pair lines

A new combined precoding/shaping technique for fast digital transmission over twisted pair lines is proposed. Major advantages of this “dynamics shaping” are: dynamics of the signal at the input of the decision device are reduced by a great amount. Thereby, A/D-conversion, adaptive equalization, and symbol timing are rather facilitated. A trade-off between signal dynamics at the transmitter output, decision device input and SNR-gain by noise whitening is offered. For dynamics limitation relevant in practice, gains up to 6 dB are achieved. Additionally, the transmitter can be fixed to a typical application because, in contrast to Tomlinson-Harashima or other precoding techniques, blind adaptive equalization is practicable to remove residual intersymbol interference in the case of a mismatch of precoding and actual cable characteristics. The residual SNR-loss is negligible in most applications. SNR-gains due to noise prediction, channel coding and signal shaping simply can be combined using dynamics shaping. Nevertheless, system complexity is of the order of other precoding/shaping techniques. Although numerical results are only presented for a HDSL-application in the German Telekom subscriber network, the proposed transmission scheme may simplify all kinds of high-speed data communications via copper lines, such as LANs, ADSL, CDDI, etc

Decision-feedback differential detection based on linear prediction for MDPSK signals transmitted over Ricean fading channels

In this paper, linear prediction-based decision-feedback differential detection (DF-DD) for M-ary differential phase-shift keying (MDPSK) signals transmitted over Ricean fading channels is proposed. This scheme can improve conventional DD significantly for a multitude of frequency-nonselective channels, as shown analytically and by computer simulations. Prediction-based DF-DD is particularly well suited for application in mobile communications since the predictor coefficients may be updated regularly using the recursive least squares (RLS) algorithm. Here, adaptation can start blind, i.e., no training sequence and no a prior knowledge about the channel statistics are required. A further important characteristic of the proposed detection scheme is that no degradation occurs under frequency offset. The bit error rate (BER) performance of QDPSK with genie-aided prediction-based DF-DD is analyzed, and it is shown under which conditions the irreducible error floor of conventional DD can be removed entirely. In addition, the influence of Doppler shift is discussed. Last, the proposed scheme is compared with a second DF-DD scheme, which is based on multiple-symbol detection.