International audience

Non-Intrusive Load Monitoring (NILM) attempts to break down the aggregated electrical consumption signal into the power consumption of each individual appliance, which can provide helpful understanding on energy consumption patterns and helps reduce overall energy usage and costs. This paper proposes an occupancy-aided energy disaggregation approach to address the NILM problem. Our methodology encompasses three key steps: firstly, features extraction from environmental sensors through the training of a DAE model; secondly, inference of occupancy information using the K-means algorithm; and finally, the disaggregation process using a Recurrent Neural Network (RNN) model, incorporating the detected occupancy status alongside power data. Experiments conducted on our real-world dataset demonstrate that our method significantly outperforms the state-of-the-art models while having good generalization capacity, achieving roughly 40% Mean Absolute Error (MAE) gain and 30% Root Mean Squared Error (RMSE) gain on a specific appliances disaggregation compared to the conventional NILM approach where only the power data is used.

Nowadays, there is a high demand for human and/or objects monitoring/localizing in the context of applications like Building Information Modeling (BIM), automated drone missions, contextual visits of museum or sports monitoring for instance. While for outdoor positioning accurate and robust solutions (i.e. GPS) exist for many years, indoor positioning is still very challenging. There is also a need of gesture/motion tracking systems that could replace video solutions. We propose in this paper a hardware/software platform named Zyggie that combines both Ultra Wide Band (UWB) technology and Received Signal Strength Indicator (RSSI) for low power accurate indoor positioning and Inertial Measurement Unit (IMU) utilization for motion tracking. Very few industrial/academic existing solutions can simultaneously perform indoor positioning and motion tracking and none of them can do both under low power, low cost and compacity constraints addressed by our platform. As Zyggie has the capability to estimate distances w.r.t other platforms in the environment and quaternions (which represents the attitude/orientation) users can test/enhance state of the art algorithms for positioning and motion tracking applications.

In wireless networks, the cooperative diversity is an implicit form of space diversity commonly used when other conventional transmit diversity methods might not be practical. It was largely proved that cooperative transmission, where a source and a relay cooperate to communicate with a unique destination, is power‐efficient compared to the point‐to‐point transmission. However, the model considered when stating this conclusion is counting only the transmission power consumption. In this study, the authors study the effect of taking into account not only the transmission power at each transmission node but also the processing power consumed in each reception node on the overall end‐to‐end performance. They formulate the optimisation problem aiming to minimise the total power consumption in order to achieve a target performance constraint, where the total power consumption stands for the sum of the transmission power and the processing power consumed in the decoding (neglecting other forms of power consumption). The authors' analysis relies on the characterisation of an information‐theoretic bound on the decoding power of any modern code to achieve a specified bit error probability while operating at a certain gap from the capacity. As this bound is built on the sphere‐packing analysis, this study focuses on message‐passing decoders. Using this theoretical framework, the improvement of well‐known cooperative protocols over the original non‐cooperative point‐to‐point system system is reinvestigated in terms of total power consumption. Thanks to this theoretical framework, a new classification of the studied cooperative protocols is given revealing some surprising conclusions. In particular, the selective decode‐and‐forward protocol is no more constantly preferred to its simpler alternative, i.e. the decode‐and‐forward protocol.

This paper addresses the problem of In-phase/Quadrature (I/Q) imbalance sensitivity of communication systems when it occurs at both Transmitter (TX) and Receiver (RX) sides of an optical coherent system. A novel blind technique is proposed based on the pseudo-rotation of the M-QAM constellation. The pseudo-rotation based compensator is a generic approach, because it does not depend on the modulation order and the level of imbalance. To implement the proposed compensation in practical systems, two algorithms are proposed: Recursive Pseudo-Rotation (RPR) that achieves the performance of the ideal compensator and LRPR, a Low complexity version of RPR. Monte Carlo simulation results show that the proposed compensator outperforms state-of-the-art algorithms for an Additive White Gaussian Noise (AWGN) and the complexity/performance trade-off is also discussed. The efficiency of the proposed method is experimentally validated with a 10 Gbaud QPSK optical system showing its operation in the presence of Inter-Symbol Interference (ISI).

Blind adaptive source separation (BASS) based compensation for transmitter (Tx) IQ imbalance is presented for the first time in an M-QAM optical coherent system. The proposed method is numerically investigated with 4-QAM and 16-QAM signals in the presence of Tx IQ imbalance up to 30o. The robustness of the BASS method is studied after 200-km optical fiber transmission, in which the effects of chromatic dispersion (CD) and carrier frequency offset (CFO) are assumed to be dominant. It is also found that CFO, inherent to frequency difference between the transmitter and receiver lasers in optical coherent transmission, should be compensated before IQ imbalance compensation to achieve a better performance. The proposed method outperforms the Gram-Schmidt orthogonalization procedure (GSOP) in the presence of CD and CFO. We further validate experimentally the proposed method with 10-Gbaud optical 4-QAM and 16-QAM signals at 30o and 10o phase imbalance, respectively, with an emulated 200-km optical fiber transmission and 200-MHz CFO. More specifically, the optical signal-to-noise ratio (OSNR) penalty reduction of the BASS method compared to the GSOP method is 1 dB for 4-QAM at a bit-error-ratio (BER) of 2×10-3 and 2 dB for 16-QAM at a BER of 10-3. Moreover, instead of being a fully independent block and requiring statistical estimation as in GSOP, the BASS method can be integrated into an equalizer and operated at the sample rate, simplifying the operation and allowing parallel implementation.

We present a novel simple blind adaptive compensation method for in-phase/quadrature (IQ) imbalance in m-ary quadrature amplitude modulation (m-QAM) coherent optical fiber communication systems. IQ-imbalance compensation is integrated into butterfly-structured finite impulse response (FIR) filters, resulting in a significant computational effort reduction in comparison to conventional methods. A reduction in hardware complexity by a factor of about 3 is achieved by the proposed joint method. The proposed structure is experimentally validated with a 40-Gbit/s 16-QAM signal. A 7-dB power penalty reduction is experimentally achieved at a bit error rate (BER) of 10-3in the presence of a 10° phase imbalance, confirming the effectiveness of the proposed algorithm. The equalization capability remains even in the presence of group velocity dispersion along the link, which is numerically confirmed with optical fiber transmission up to 1200 km and 20° phase imbalance.

A body network of Inertial Measurement Units (IMUs) is a well known solution for posture recognition based on accelerometer and magnetometer data fusion. However sensors and especially the magnetometer can be disturbed by the environment. Considering a Wireless Body Sensor Network (WBSN), we propose to use available radio received power measurements as an alternative to the magnetometer. We show with simulation and real data, that the radio signal used for WBSN communications can also provide useful location information despite highly noisy Received Signal Strength Indications (RSSI). We propose a solution for the static case that leads to a very simple yet Efficient algorithm.

A novel low complexity parallel algorithm and its associated architecture are proposed for initial synchronization in orthogonal frequency division multiplexing (OFDM) systems. The method is hierarchical and uses auto-correlation for the first step and cross-correlation for the second step. The main advantage of the proposed approach is that it reduces the computational complexity by a factor of five (80%), while achieving similar mean square error (MSE) as cross-correlation based methods. The method uses block-level parallelism for auto-correlation step, which speeds up the computation significantly. After fixed-point analysis, a parallel architecture is proposed to accelerate both coarse and fine synchronization steps. This parallel architecture is scalable and provides speed-up proportional to number of parallel blocks.

A new hierarchical synchronization method is proposed for initial timing synchronization in orthogonal frequency-division multiplexing(OFDM) systems. Based on the proposal of new training symbol, a threshold based timing metric is designed for accurate estimation of start of OFDM symbol in a frequency selective channel. Threshold is defined in terms of noise distributions and false alarm, which makes it independent of type of channel it is applied. Frequency offset estimation is also done for the proposed training symbol. The performance of the proposed timing metric is evaluated using simulation results. The proposed method achieves low mean squared error(MSE) in timing offset estimation at five(5 x) times lower computational complexity compared to cross-correlation based method in a frequency selective channel. It is also computationally efficient compared to hybrid approaches for OFDM timing synchronization.

To reduce the decoding complexity of linearly precoded MIMO systems, the sphere decoder is applied instead of maximum likelihood and the performance complexity trade-off is investigated. The max-dminprecoding criterion allows to enhance dramatically the Bit-Error-Rate (BER) of MIMO systems by maximizing the minimum Euclidean distance between the lattice points of received constellation. The maximum likelihood (ML) decoder, therefore, is the optimal solution for the receiver, but its computational complexity is exponential in function of the number of antennas and constellation size. The sphere decoding (SD) algorithm, proposed as a sub-optimal ML-decoding, just considers a subset of lattice points that drop into the sphere centered by the received point to obtain the decoded solution, thus reducing significantly the complexity. In this paper, two structures of SD will be investigated: general SD with its adaptive covering radius and real-valued fixed complexity sphere decoder (RFSD). Because the structure of max-dminis complicated and strongly depends on the channel, it exists the case when all power is poured only on the best sub-channel. Some adjustments, therefore, of traditional sphere decoding algorithm will be made to adapt to the precoded MIMO systems.

Through a feedback link, the channel state information acquired at the receiver is known at the transmitter and MIMO precoding techniques can be applied according to various criteria. In this paper, an efficient linear precoder based on the maximization of the minimum Euclidean distance between two received data vectors for three data-stream MIMO spatial multiplexing systems is proposed. By using a singular value decomposition, the precoding matrix can be parameterized as the product of a power allocation matrix and an input shaper matrix. According to this representation, the optimal precoders are proposed for the case of three independent data-streams. Simulation results over Rayleigh fading channels show considerable bit-error-rate improvement with the proposed solution in comparison with other precoding strategies.

Not only the minimum Euclidean distance but also the number of neighbors providing the dminin the received constellation has an important role in reducing the error probability when Maximum Likelihood detection is considered. Assuming that the channel-state-information is available at the transmitter, a new precoder in which the rotation parameter has no influence is proposed for two independent data-streams. The expression of the new precoding strategy is less complex and the space of solution is, therefore, smaller. Simulation results over Rayleigh fading channel confirm a bit-error-rate improvement of the proposed solution in comparison with other precoders. The improvement depends on the channel characteristics and is more significant if the channel is dispersive.

This paper proposes an efficient sub-optimal MIMO linear precoder based on the maximization of minimum distance for three virtual suchannels. A new virtual MIMO channel representation with two channel angles allows the parameterization of the linear precoder and the optimization of the distance between signal points at the received constellation. To illustrate the optimization process, a precoder is derived for BPSK and QPSK modulation following the max-SNR approach, which consists in pouring power only on the most favored virtual sub-channel. Simulation results over a Rayleigh channel confirm the interest of this new precoder in terms of bit-error-rate.

In this paper, we present a novel, frequency-domain stereo to mono downmixing, which preserves the energy of spectral components and avoids setting the left or right channel as a phase reference. Based on this downmixing technique, a parametric stereo analysis-synthesis model is described in which subband stereo parameters consist of interchannel level differences and phase differences between the mono signal and one of the stereo channels (left or right). This model is applied to the stereo extension of ITU-T G.722 at 56+8 and 64+16 kbit/s with a frame length of 5 ms. AB test results are provided to assess the quality of the proposed downmixing technique. In addition, the quality of the proposed G.722-based stereo coder is compared against reference coders (G.722.1 at 24 and 32 kbit/s dual mono and G.722 at 64 kbit/s dual mono) for clean speech, noisy speech and music.

We consider the speech enhancement problem in a moving car through a blind source separation scheme involving two closely spaced microphones. We propose the use of a double fast Newton transversal filter algorithm (DFNTF) to estimate and suppress coherent noise components from speech, and a model of signal mixtures able to represent correctly the effect of microphones spacing. We also consider the realistic case where the noises at the sensor inputs contain non-coherent components. The simulation results show that the DFNTF algorithm, when controlled by a voice activity detector (VAD), is able to fully cancel the correlated noise components from speech

This paper addresses the problem of single-microphone speech enhancement in noisy environments. State-of-the-art short-time noise reduction techniques are most often expressed as a spectral gain depending on the signal-to-noise ratio (SNR). The well-known decision-directed (DD) approach drastically limits the level of musical noise, but the estimated a priori SNR is biased since it depends on the speech spectrum estimation in the previous frame. Therefore, the gain function matches the previous frame rather than the current one which degrades the noise reduction performance. The consequence of this bias is an annoying reverberation effect. We propose a method called two-step noise reduction (TSNR) technique which solves this problem while maintaining the benefits of the decision-directed approach. The estimation of the a priori SNR is refined by a second step to remove the bias of the DD approach, thus removing the reverberation effect. However, classic short-time noise reduction techniques, including TSNR, introduce harmonic distortion in enhanced speech because of the unreliability of estimators for small signal-to-noise ratios. This is mainly due to the difficult task of noise power spectrum density (PSD) estimation in single-microphone schemes. To overcome this problem, we propose a method called harmonic regeneration noise reduction (HRNR). A nonlinearity is used to regenerate the degraded harmonics of the distorted signal in an efficient way. The resulting artificial signal is produced in order to refine the a priori SNR used to compute a spectral gain able to preserve the speech harmonics. These methods are analyzed and objective and formal subjective test results between HRNR and TSNR techniques are provided. A significant improvement is brought by HRNR compared to TSNR thanks to the preservation of harmonics

The paper addresses the problem of single microphone speech enhancement in noisy environments. Common short-time noise reduction techniques introduce harmonic distortion in enhanced speech because of the non reliability of estimators for small signal-to-noise ratios. We propose a new method, called harmonic regeneration noise reduction technique, which solves this problem. A fully harmonic signal is calculated based on the distorted signal using a non-linearity to regenerate harmonics in an efficient way. This artificial signal is then used to compute a suppression gain able to preserve the speech harmonics. This method is theoretically analyzed, then objective and formal subjective results are given and show a significant improvement compared to classical noise reduction techniques.

The implementation of adaptive filters with fixed-point arithmetic requires us to evaluate the computation quality. The accuracy can be determined by calculating the global quantization noise power in the system output. In this paper, a new model for evaluating analytically the global noise power in the APA (affine projection algorithm) is developed. The model is presented and applied to the NLMS-OCF. The accuracy of our model is analyzed by experimentation.

The paper addresses the problem of single microphone speech enhancement in noisy environments. Common short-time noise reduction techniques proposed in the art are expressed as a spectral gain depending on the a priori SNR. In the well-known decision-directed approach, the a priori SNR depends on the speech spectrum estimation in the previous frame. As a consequence, the gain function matches the previous frame rather than the current one which degrades the noise reduction performance. We propose a new method, called the two-step noise reduction (TSNR) technique, which solves this problem while maintaining the benefits of the decision-directed approach. This method is analyzed and results in voice communication and speech recognition contexts are given.

The implementation of adaptive filters with fixed-point arithmetic requires the computation quality to be evaluated. The accuracy may be determined by calculating the global quantization noise power in the system output. A new model for evaluating analytically the global noise power in the LMS algorithm and in the NLMS algorithm is developed. Two existing models are presented, then the model is detailed and compared with the ones before. The accuracy of our model is analyzed by simulation.

This paper presents a new structure of an Acoustic Echo Canceller (AEC) designed to operate in the Mobile Switching Center (MSC) of a GSM network. The purpose of such system is to cancel the echo for all the subscribers. Contrarily to the conventional AEC, the proposed combined AEC/CELP Predictor is able to take into account the non linearities introduced by the GSM speech coders/decoders. A short term predictor is used to model the behavior of the codecs. This new combined system presents higher performance compared to the conventional AEC.

The normalized LMS (NLMS) algorithm has been successfully used in many system identification problems. However, the NLMS algorithm is known to exhibit low convergence speed especially when the input data covariance matrix is ill-conditioned. In this paper, we consider a sub-optimal implementation of the affine projection (AP) algorithm based on a prewithening mechanism, which renders the convergence characteristics less sensitive to the coloring of the input signal spectrum than is the case for the NLMS algorithm. Comparisons with the AP algorithm are given to validate our approach. Implementation details are discussed in the context of hands-free telephony where echo cancelling and speech coding algorithms are integrated on the same DSP board.

In most adaptive identification applications, a finite impulse response (FIR) filter is employed with coefficients that are computed using the normalized least mean square (NLMS) algorithm. The convergence behavior of the NLMS algorithm is analyzed using a simple model of the input signal vectors. Explicit expressions of the learning curve and misadjustment are derived and compared with those previously established for the NLMS algorithm. Comparisons between theoretical and experimental results are given to validate our approach.

The modern telecommunications field is concerned with freedom and, in this context, hands-free systems offer subscribers the possibility of talking more naturally, without using a handset. This new type of use leads to new problems which were negligible in traditional telephony, namely the superposition of noise and echo on the speech signal. To solve these problems and provide a quality that is sufficient for telecommunications, combined reduction of these disturbances is required. This paper presents a summary of the solutions retained for this dual reduction in the context of mono-channel and two-channel sound pick-ups.

The goal of source controlled channel decoding is to improve the performance of the channel decoder by using the residual redundancy of the source encoded data. The original approach exploits only the interframe correlation between bits and a few simple schemes have been devised in order to use the intraframe correlation. In this paper, we present an efficient method to exploit the intraframe correlation during the channel decoding process. We estimate an a priori soft value of the bit being decoded from the bits already decoded along the trellis path. This estimate is then used together with the estimate obtained from interframe correlation in the Viterbi metric. We also introduce an adaptive estimator of bit correlation that takes into account the reliability of the bits at the decoder output. Our channel decoding algorithm is applied to the full-rate and enhanced full-rate speech codecs in the GSM system and results in a noticeable improvement of the bit error rate.

The goal of source controlled channel decoding is to improve the performance of the channel decoder by using the residual redundancy of the speech encoded data. The original approach exploits only the interframe correlation between bits and few simple schemes have been devised in order to use the intraframe correlation. In this contribution, we present an efficient method to exploit the intraframe correlation during the channel decoding process. We predict the soft value of the bit being decoded from the bits already decoded along the trellis path. Our estimator of bit correlation is adaptively estimated from the soft bits values at the decoder output. Finally, the combination of interframe and intraframe prediction is applied to the full-rate and enhanced full-rate speech codecs in the GSM system.

In this paper, we present a new approach for adaptive echo cancellation: Pseudo Affine projection algorithm. From the original update equation of the filter coefficients of the Affine Projection algorithms, which are based on multiple dimension projection of the input signal vector, we derive a simplified solution under some realistic hypothesis. We show that our solution possesses a complexity figure close to the NLMS one but with the same convergence characteristics of the original sampleby-sample AP algorithm. Implementation details are presented in the last part of the paper.

We consider an acoustic echo control system composed of a short conventional acoustic echo canceller combined with a post-filter in a teleconference context. The post-filter is implemented in an open-loop structure in the frequency domain, which provides good adaptive performance and flexibility for the choice of the post-filter length. Three post-filtering algorithms are compared in terms of residual echo attenuation and near-end speech distortion. The effect of the post-filter length is also examined. Our study confirms that the post-filtering approach provides high residual echo attenuation. Moreover, it appears that the distortion of the near-end speech can be controlled by choosing appropriately the post-filter length.

We address the problem of speech enhancement in the context of GSM hands-free radiotelephony where the signal to be transmitted is corrupted by background noise and echo signals. We propose possible schemes for combined acoustic echo cancellation (AEC) and noise reduction (NR) devices. Considering two AEC algorithms and one NR device, we show that the overall performance obtained by these schemes are greatly dependent on the intrinsic behaviour of the considered AEC algorithms. These results are confirmed by the informal listening tests presented.

This paper addresses the problem of single microphone frequency domain speech enhancement in noisy environments. The main characteristics of available frequency domain noise reduction algorithms are presented. We have confirmed that the a priori SNR estimation leads to the best subjective results. According to these conclusions, a new approach is then developed which achieves a trade-off between effective noise reduction and low computational load for real-time operations. The obtained solutions demonstrate that the subjective and objective results are much better than existing methods.