Smoothing techniques for decision-directed MIMO OFDM channel estimation

With the purpose of supplying the demand of faster and more reliable communication, multiple-input multiple-output (MIMO) systems in conjunction with Orthogonal Frequency Division Multiplexing (OFDM) are subject of extensive research. Successful Decoding requires an accurate channel estimate at the receiver, which is gained either by evaluation of reference symbols which requires designated resources in the transmit signal or decision-directed approaches. The latter offers a convenient way to maximize bandwidth efficiency, but it suffers from error propagation due to the dependency between the decoding of the current data symbol and the calculation of the next channel estimate. In our contribution we consider linear smoothing techniques to mitigate error propagation by the introduction of backward dependencies in the decision-based channel estimation. Designed as a post-processing step, frame repeat requests can be lowered by applying this technique if the data is insensitive to latency. The problem of high memory requirements of FIR smoothing in the context of MIMO-OFDM is addressed with an recursive approach that acquires minimal resources with virtual no performance loss. Channel estimate normalized mean square error and bit error rate (BER) performance evaluations are presented. For reference, a median filtering technique is presented that operates on the MIMO time-frequency grids of channel coefficients to reduce the peak-like outliers produced by wrong decisions due to unsuccessful decoding. Performance in terms of Bit Error Rate is compared to the proposed smoothing techniques

Signal processing for plane wave actuators

Plane wave actuators without an enclosure per se have a forward and backward radiation. The backward radiation is unwanted in many applications when a single direction radiation is desired. To avoid the disadvantages of an enclosure a system is proposed, which provides a high suppression of the unwanted backward radiation using a pair of plane wave actuators. This is achieved by adapted input signal filters. The influences of the second plane wave actuator to the forward radiated signal are suppressed as well. Additionally, the system also provides for- and backward radiation of different signals with a high suppression of the radiation directions crosstalk. The required power for the signal suppression depends on the physical damping of the plane wave actuators and the space in between. The first realized prototype is designed for flat panel dipole loudspeakers to deal with the mentioned problems in the acoustic domain. The filter design and a calibration algorithm for any given pairs of dipole loudspeaker are explained. The good performance of the developed system is proven by measurement results with the prototype system

Forward and backward RLS-DDCE processing in MIMO-OFDM spatial multiplexing receivers

In this paper we present a novel approach in frequency domain channel estimation technique. Our proposal is based on the recursive least squares (RLS) algorithm combined with the decision making process called decision directed channel estimation (RLS-DDCE). The novelty and key concept of this technique is the block-wise causal and anti-causal RLS processing that yields two independent processing of RLS along with the associated decisions. Due to the implemented low density parity check (LDPC) code the receiver operates with soft information, which enables us to introduce a new modification of the Turbo principle as well as simple addition of the a-posteriori log-likelihood ratios (LLRs). Although the computational complexity is increased by both of our approaches, the latter is relatively less complex than the earlier. Simulation results show that these implementations outperform the simple RLS-DDCE algorithm and yield lower bit error rates (BER) and more accurate channel information

A single channel speech enhancement technique exploiting human auditory masking properties

To enhance extreme corrupted speech signals, an Improved Psychoacoustically Motivated Spectral Weighting Rule (IPMSWR) is proposed, that controls the predefined residual noise level by a time-frequency dependent parameter. Unlike conventional Psychoacoustically Motivated Spectral Weighting Rules (PMSWR), the level of the residual noise is here varied throughout the enhanced speech based on the discrimination between the regions with speech presence and speech absence by means of segmental SNR within critical bands. Controlling in such a way the level of the residual noise in the noise only region avoids the unpleasant residual noise perceived at very low SNRs. To derive the gain coefficients, the computation of the masking curve and the estimation of the corrupting noise power are required. Since the clean speech is generally not available for a single channel speech enhancement technique, the rough clean speech components needed to compute the masking curve are here obtained using advanced spectral subtraction techniques. To estimate the corrupting noise, a new technique is employed, that relies on the noise power estimation using rapid adaptation and recursive smoothing principles. The performances of the proposed approach are objectively and subjectively compared to the conventional approaches to highlight the aforementioned improvement

Adaptive Channel Estimation based on Soft Information Processing in Broadband Spatial Multiplexing Receivers

In this paper we present a novel approach in Multiple-Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) channel estimation technique based on a Decision Directed Recursive Least Squares (RLS) algorithm in which no pilot symbols need to be integrated in the data after a short initial preamble. The novelty and key concept of the proposed technique is the block-wise causal and anti-causal RLS processing that yields two independent processings of RLS along with the associated decisions. Due to the usage of low density parity check (LDPC) channel code, the receiver operates with soft information, which enables us to introduce a new modification of the Turbo principle as well as a simple information combining approach based on approximated aposteriori log-likelihood ratios (LLRs). Although the computational complexity is increased by both of our approaches, the latter is relatively less complex than the former. Simulation results show that these implementations outperform the simple RLS-DDCE algorithm and yield lower bit error rates (BER) and more accurate channel estimates

Filters and delays

Textbook chapter covering the following topics: *Basic filters: Filter classification in the frequency domain, Canonical filters, State variable filter, Normalization, Allpass-based filters, FIR filters, Convolution; *Equalizers: Shelving filters, Peak filters; *Time-varying filters: Wah-wah filter, Phaser, Time-varying equalizers; *Basic delay structures: FIR comb filter, IIR comb filter, Universal comb filter, Fractional delay lines; *Delay-based audio effects: Vibrato, Flanger, chorus, slapback, echo, Multiband effects, Natural sounding comb filter