Sofiène Affes

A signal subspace tracking algorithm for microphone array processing of speech

This paper presents a method of adaptive microphone array beamforming using matched filters with signal subspace tracking. Our objective is to enhance near-field speech signals by reducing multipath and reverberation. In real applications such as speech acquisition in acoustic environments, sources do not propagate along known and direct paths. Particularly in hands-free telephony, we have to deal with undesired propagation phenomena such as reflections and reverberation. Prior methods developed adaptive microphone arrays for noise reduction after a time delay compensation of the direct path. This simple synchronization is insufficient to produce an acceptable speech quality, and makes adaptive beamforming unsuitable. We prove the identification of source-to-array impulse responses to be possible by subspace tracking. We consequently show the advantage of treating synchronization as a matched filtering step. Speech quality is indeed enhanced at the output by the suppression of reflections and reverberation (i.e., dereverberation), and efficient adaptive beamforming for noise reduction is applied without risk of signal cancellation. Evaluations confirm the performance achieved by the proposed algorithm under real conditions.

Radio-channel characterization of an underground mine at 2.4 GHz

This paper presents comprehensive experimental results obtained from narrowband and wideband radio-channel measurements in an underground mine with narrow veins at 2.4 GHz. From continuous-wave (CW) measurement data, large-scale distance-power curves and path-loss exponents of the environment are determined. Other relevant parameters, such as the mean excess delay, the maximum excess delay, the root-mean-square (rms) delay spread, and the coherence bandwidth are extracted from the wideband-measurement data. Results show a propagation behavior that is specific for these underground environments with rough surfaces. The rms delay spread does not follow a dual-slope relation with respect to distance, as in environments with smooth surfaces. Moreover, the dependence of the rms delay spread on the bidimensional position of the user is found to be very significant. For the majority of locations, the rms delay-spread values are less than 60 ns.

Radio Wave Characterization and Modeling in Underground Mine Tunnels

Results are presented on wideband radio propagation measurements and statistical modeling at 2.4 GHz and 5.8 GHz in real underground mine tunnels. This peculiar type of confined environment is characterized by very rough surfaces and a frequent absence of a line-of-sight between transmitting and receiving antennas. The resulting propagation characteristics differ from those frequently encountered in more typical indoor environments such as offices and corridors. Indeed, the rms delay spread shows little or no correlation with respect to transmitter-receiver distance and, in addition, no impulse response path arrival clustering effect is observed. However, the path amplitude distribution does tend to follow a Rice distribution in the line-of-sight case, and a Rayleigh distribution otherwise.

A Generalized Steered Response Power Method for Computationally Viable Source Localization

The process of locating an acoustic source given measurements of the sound field at multiple microphones is of significant interest as both a classical array signal processing problem, and more recently, as a solution to the problems of automatic camera steering, teleconferencing, hands-free processing, and others. Despite the proven efficacy of steered-beamformer approaches to localization in harsh conditions, their practical application to real-time settings is hindered by undesirably high computational demands. This paper presents a computationally viable implementation of the steered response power (SRP) source localization method. The conventional approach is generalized by introducing an inverse mapping that maps relative delays to sets of candidate locations. Instead of traversing the three-dimensional location space, the one-dimensional relative delay space is traversed; at each lag, all locations which are inverse mapped by that delay are updated. This means that the computation of the SRP map is no longer performed sequentially in space. Most importantly, by subsetting the space of relative delays to only those that achieve a high level of cross-correlation, the required number of algorithm updates is drastically reduced without compromising localization accuracy. The generalization is scalable in the sense that the level of subsetting is an algorithm parameter. It is shown that this generalization may be viewed as a spatial decomposition of the SRP energy map into weighted basis functions-in this context, it becomes evident that the full SRP search considers all basis functions (even the ones with very low weighting). On the other hand, it is shown that by only including a few basis functions per microphone pair, the SRP map is quite accurately represented. As a result, in a real environment, the proposed generalization achieves virtually the same anomaly rate as the full SRP search while only performing 10% the amount of algorithm updates as the full search.

On the performance analysis of composite multipath/shadowing channels using the G-distribution

Composite multipath fading/shadowing environments are frequently encountered in different realistic scenarios. These channels are generally modeled as a mixture of Nakagami-m multipath fading and log-normal shadowing. The resulting composite probability density function (pdf) is not available in closed form, thereby making the performance evaluation of communication links in these channels cumbersome. In this paper, we propose to model composite channels by the G-distribution. This pdf arises when the log-normal shadowing is substituted by the inverse-Gaussian one. This substitution will prove to be very accurate for several shadowing conditions. In this paper we conduct a performance evaluation of single-user communication systems operating in a composite channel. Our study starts by deriving an analytical expression for the outage probability. Then, we derive the moment generating function of the G-distribution, hence facilitating the calculation of average bit error probabilities. We also derive analytical expressions for the channel capacity for three adaptive transmission techniques, namely, i) optimal rate adaptation with constant power, ii) optimal power and rate adaptation, and iii) channel inversion with fixed rate.

On the capacity of generalized-k fading channels

This paper investigates the capacity of generalized- K fading channels. This very general model describes accurately composite multipath/shadowing fading channels which are widely encountered in real-world environments. We derive closed-form expressions for three adaptive transmission techniques, namely, i) optimal rate adaptation with constant power, ii) optimal power and rate adaptation, and iii) channel inversion with fixed rate. The analytical expressions obtained match perfectly the results obtained by computer simulations. These expressions provide a good tool to assess the spectral efficiency of the aforementioned adaptive transmission techniques over composite channels.

Interference subspace rejection: a framework for multiuser detection in wideband CDMA

We present a unifying framework for a new class of receivers that employ linearly-constrained interference cancellation (IC). The associated multiuser detectors operate in various modes and options ranging in performance from that of IC detectors to that of linear receivers, yet provide more attractive performance/complexity tradeoffs. They exploit both space and time diversities as well as the array-processing capabilities of multiple antennas and carry out simultaneous channel and timing estimation, signal combining and interference rejection. Additionally, they can operate on both links and in multiple mixed-rate traffic scenarios. The improved performance can be translated to increased utilization of wideband code division multiple access networks, particularly at high data rates.

A new receiver structure for asynchronous CDMA: STAR-the spatio-temporal array-receiver

We propose a spatio-temporal array-receiver (STAR) for asynchronous code division multiple access (CDMA), using a new space/time structural approach. First, STAR performs blind identification and equalization of the propagation channel from each mobile transmitter. Second, it provides fast and accurate estimates of the number, relative magnitude, and delay of the multipath components. From this space/time separation, STAR reconstructs the identified channel with respect to a partially revealed space/time structure and reduces identification errors by the order of the ratio of the processing gain and the number of paths. Therefore, STAR offers a high potential for increasing capacity, with relatively low computational complexity. Simulations confirm the good multipath acquisition and tracking properties of STAR in the presence of strong interference and fast Doppler.

Direction of Arrival Estimation Using the Parameterized Spatial Correlation Matrix

The estimation of the direction-of-arrival (DOA) of one or more acoustic sources is an area that has generated much interest in recent years, with applications like automatic video camera steering and multiparty stereophonic teleconferencing entering the market. DOA estimation algorithms are hindered by the effects of background noise and reverberation. Methods based on the time-differences-of-arrival (TDOA) are commonly used to determine the azimuth angle of arrival of an acoustic source. TDOA-based methods compute each relative delay using only two microphones, even though additional microphones are usually available. This paper deals with DOA estimation based on spatial spectral estimation, and establishes the parameterized spatial correlation matrix as the framework for this class of DOA estimators. This matrix jointly takes into account all pairs of microphones, and is at the heart of several broadband spatial spectral estimators, including steered-response power (SRP) algorithms. This paper reviews and evaluates these broadband spatial spectral estimators, comparing their performance to TDOA-based locators. In addition, an eigenanalysis of the parameterized spatial correlation matrix is performed and reveals that such analysis allows one to estimate the channel attenuation from factors such as uncalibrated microphones. This estimate generalizes the broadband minimum variance spatial spectral estimator to more general signal models. A DOA estimator based on the multichannel cross correlation coefficient (MCCC) is also proposed. The performance of all proposed algorithms is included in the evaluation. It is shown that adding extra microphones helps combat the effects of background noise and reverberation. Furthermore, the link between accurate spatial spectral estimation and corresponding DOA estimation is investigated. The application of the minimum variance and MCCC methods to the spatial spectral estimation problem leads to better resolution than that of the commonly used fixed-weighted SRP spectrum. However, this increased spatial spectral resolution does not always translate to more accurate DOA estimation

An Integrated Solution for Online Multichannel Noise Tracking and Reduction

Noise statistics estimation is a paramount issue in the design of reliable noise-reduction algorithms. Although significant efforts have been devoted to this problem in the literature, most developed methods so far have focused on the single-channel case. When multiple microphones are used, it is important that the data from all the sensors are optimally combined to achieve judicious updates of the noise statistics and the noise-reduction filter. This contribution is devoted to the development of a practical approach to multichannel noise tracking and reduction. We combine the multichannel speech presence probability (MC-SPP) that we proposed in an earlier contribution with an alternative formulation of the minima-controlled recursive averaging (MCRA) technique that we generalize from the single-channel to the multichannel case. To demonstrate the effectiveness of the proposed MC-SPP and multichannel noise estimator, we integrate them into three variants of the multichannel noise reduction Wiener filter. Experimental results show the advantages of the proposed solution.