The delay-Doppler analysis for moving people detection in smart factory-like indoor environments using impulse radio ultra-wideband (IR-UWB) radar is addressed in this paper. The transmitted signal’s huge bandwidth results in a very fine range resolution, so that, unlike for a standard narrowband radar, mobile reflectors of interest to be detected (RID) migrate over several range resolution cells during the coherent integration period in slow time. The association of their motion characteristics and IR-UWB signal’s features leads to troublesome effects after Doppler focusing (DF), such as spurious peaks and shortened ambiguity window. The results revealed by our delay-Doppler (or range-Doppler) analysis of the backscattered IR-UWB signals are reported in the paper and theoretical bounds for the Doppler ambiguity window in this specific case are derived. Moreover, we suggest a way to handle these aspects in the context of the considered application.

This paper deals with the influence of a wideband signal key parameters on its spectrum reconstruction, for Internet-of-Things (IoT) applications. The impact of the frequency resolution, the bandwidths of the sensed transmitters, and the frequency spacing between their subbands are thoroughly analyzed. The spectrum detection of LoRaWAN EU868, one of the IoT standards, is simulated and examined. In the framework of cognitive networks or spectrum sensing, an input wideband signal, whose bandwidth is exceptionally large (resulting in an extremely high Nyquist rate), can be sampled at a much lower rate than the Nyquist limit. Under the hypothesis of Compressed Sensing, this paper deploys a sub-Nyquist sampling scheme, called Modulated Wideband Converter (MWC). The spectrum reconstruction is carried out from the sub-Nyquist samples, and then evaluated based on the correct reconstruction and false alarm rates.

This paper presents an implementation of the Modulated Wideband Converter (MWC) compressed sensing scheme using Commercial Off-The-Shelf (COTS) low-pass filter (SXLP-36+ from Mini-Circuits®) for spectrum surveillance in order to reconstruct a wideband signal at sub-Nyquist rate. From a theoretical point of view, the MWC scheme achieves a correct reconstruction only if all analog components are assumed ideal. Indeed, to deploy this scheme into practice, the impacts of non-ideal components need to be considered, especially lowpass filters. In this paper, the SXLP-36+ lowpass filter is characterized in order to implement amplitude and phase compensation method without any optimization algorithms. The goal of this digital compensation is to achieve an output as close as possible to the theoretical MWC output. The results of spectrum reconstruction are evaluated with respect to probability of correct reconstruction and false alarm criteria.

This paper focuses on non-ideal filters in a Modulated Wideband Converter (MWC) scheme. The MWC is a system that can sample a sparse wideband signal at sub-Nyquist rate. Generally, the output of the ideal MWC components will ensure a perfect reconstruction. In practice, the reconstruction should be based on the output of non-ideal components, especially filters. The impact of non-ideal filters will trigger to a bad reconstruction. In this paper, a detailed study on non-ideal lowpass filters imperfection used in compressed sensing MWC scheme is synthesized. A digital post-treatment scheme with amplitude and phase compensation is proposed after real lowpass filtering step in order to have the filtered output as close as the ideal lowpass filter output. At last, reconstruction spectra obtained from different simulated lowpass filters are compared with different parameters of MWC.

The concatenation of the multiple-input multiple-output (MIMO) linear precoder with an outer forward error correction (FEC) code at the transmitter is investigated in this paper. At the receiver side, the turbo detection is taken into account. It iteratively exchanges the extrinsic information between a soft-demapper and a FEC soft-decoder. We firstly propose a new precoder named FI1designed from an extrinsic information transfer (EXIT) chart analysis. The proposed precoder aims to optimize the iterative receiver convergence by maximizing the ending point I1of the soft-demapper EXIT function. For the sake of low-complexity, FI1is designed for two data streams MIMO transmission with 4-QAM only. Secondly, to cope with the higher data streams transmission, a global b = 2K data streams system is split into K two data streams subsystems. FI1is then applied at each subsystem. Finally, we propose a new algorithm to optimize the inter-subsystems power allocation by maximizing the I1of the global system.

Precoder optimization with full channel state information for finite alphabet signals over multiple-input multiple-output random channels is investigated in this paper. The precoder is represented by a product of power allocation matrix and constellation-forming matrix. There was an optimal algorithm introduced in the literature to globally maximize the channel mutual information by iteratively optimizing these two matrices. However, the computational complexity of the optimal algorithm is painfully high, especially when it is used with the high-order modulation and the high-data stream number. In this paper, we propose a novel sub-optimal low-complexity precoding algorithm and compare it with the optimal one. The new algorithm proceeds in two steps. First, the constellation-forming matrix is fixed in order to maximize the minimum Euclidean distance between the received symbols, which ensures high channel mutual information. Then, given the constellation-forming matrix, an iterative algorithm searches for the power allocation matrix that maximizes the channel mutual information. Since optimizing only one matrix instead of two, the new algorithm not only achieves a lower computational complexity but also avoids the use of initial values, which must be carefully selected for each channel and signal-to-noise ratio for fast convergence. Another advantage of the new algorithm is that the resulting precoder has a fixed form of received constellation thanks to the fixed constellation-forming matrix. This allows us to optimize the symbol mapping on the received constellation. Simulation results show that the proposed low-complexity precoder achieves error-rate performance that is close to performance of the optimal one when the conventional mapping is used. In addition, the new precoder used with optimized mapping at received constellation shows significant error-rate performance improvement.

In this paper, we focus on a multiple-input multiple-output (MIMO) linear precoder based on the minimum Euclidean distance criterion, the max- dmin precoder. We propose an optimization of this precoder for the case of an association with a non-binary low density parity check code (NB- LDPC). After recalling the well-known max-dmin precoder, we set forth an optimization of the mutual information of initial message, i.e. I(0), through the extrinsic information transfer (EXIT) analysis of the system. We present a new adaptive precoder whose forms are determined in function of an adaptive threshold angle, optimized in terms of the mutual information I(0), and depending on the signal-to-noise ratio at the reception (SNR_R). The performance of the new precoder is brought out through a theoretical study along with a series of numerical simulations.

In this paper, we investigate the concatenation of the multiple input multiple output (MIMO) max-dminlinear precoder with an outer forward error correction (FEC) code at the transmitter. At the receiver side, the turbo equalization is taken into account, which iteratively exchanges the extrinsic information between a minimum mean square error interference canceller (MMSE IC) and a FEC decoder. The analysis done by extrinsic information transfer (EXIT) chart shows that a higher mutual information (MI) at the convergence state of the turbo equalization is observed thanks to the linear precoder. In addition, we exploit this property to propose a new precoder named max-dmin-mod. Numerical simulations are in accordance with the theoretical analysis, which exhibits a significant improvement of the error-rate of the turbo equalization as well as a significant gain of max-dmin-mod compared to original max-dminprecoder.

In this paper, we consider the problem of sensing a primary user in a cognitive radio network by employing multiple antennas at the secondary user. Among the many spectrum-sensing methods, the predicted eigenvalue threshold (PET) based method is a promising non-parametric blind method that can reliably detect the primary users without any prior information. Then, a simplified PET sensing method, which needs to compare only one eigenvalue to its threshold, is introduced. Compared with the original PET sensing algorithm, the simplified algorithm significantly reduces the computational complexity without any loss in performance. A performance comparison between the proposed method and other existing methods is provided.

In this paper, we consider the problem of sensing a primary user in a cognitive radio network by employing multiple-antennas at the secondary user. Among the many spectrum-sensing methods, the predicted eigenvalue threshold (PET) based method is a promising non-parametric blind method that can reliably detect the primary users without any prior information. Also, a simplified PET sensing method, which needs to compare only one eigenvalue to its threshold, is introduced. A performance comparison between the proposed method and other existing methods is provided. Spatial antenna correlation at the secondary user is a crucial factor for practical systems. The effect of the spatial correlation presence on the different sensing methods is investigated.

Synchronization is a key performance-limiting factor in any communication system and a challenging task to accomplish. In this paper, an energy detection based non data-aided (NDA) algorithm for orthogonal pulse shape modulated (PSM) impulse radio ultra wideband (IR-UWB) system is proposed. Relying on unique signal structure, simple overlap-add operation followed by energy detection enables synchronization. The algorithm remains functional under practical scenarios i.e. in the presence of inter-frame and inter-symbol interference (IFI & ISI) and with M-ary modulation. Simulation results are provided to demonstrate the performance of proposed algorithm.

The retrieval of soccer highlights is a suitable technique for video indexing, required by the multimedia database management or for the development of television on demand. For these purposes, it should be interesting to have an automatic annotation of events happened in soccer games. One solution consists in analyzing the audio soundtrack associated to the soccer video and to detect the interesting frames. In this paper we use the adaptive time-frequency decomposition of the soundtrack as a feature extraction procedure. This decomposition is based on the Matching Pursuit concept and a dictionary composed of Gabor functions. The parameters provided by these transformations constitute the input of the classification stage. The results provided for real soccer video will prove the efficiency of the adaptive time-frequency representation as a feature extraction stage.

The high-order ambiguity function (HAF) was introduced for the estimation of polynomial-phase signals (PPS). Currently the HAF suffers from noise-masking effects and from the appearance of undesired cross terms in the presence of multi-components PPS. The multi-lag product HAF concept was then proposed as a way to improve the performance of the HAF. Nevertheless, the performance of the new methods are affected by the error propagation. This effect is due to the technique used for polynomial order reduction, common for current approaches: signal multiplication with the complex exponentials formed with the estimated coefficients. In this paper, we introduce an alternative method to reduce the polynomial order, based on the successive unitary signal transformation, according to each polynomial order. We prove that this method considerably reduces the effect of error propagation.

Sea clutter data provided by Thales Naval France are analyzed in order to determine their statistical and correlation properties. The K-compound distribution is found to match the best the amplitude pdf of the data. A new method is proposed for estimating the associated scale and shape parameters. Two innovative approaches are also described for simulating the sea clutter. The first one is based on the K-compound pdf model, while the second one is a 2D MA kernel based generating procedure.