Semantic segmentation is a fundamental task in computer vision with critical applications in autonomous driving, medical imaging, and remote sensing. However, optimizing segmentation models for real-world deployment remains challenging due to the high annotation costs and computational demands associated with large-scale datasets. In this paper, we propose a novel approach that synergistically integrates superpixels, active learning, and visual prompt tuning to enhance semantic segmentation efficiency and generalization across diverse domains. Our method leverages superpixels to guide region-based active learning, strategically selecting the most informative areas for annotation, thereby minimizing labeling costs while preserving segmentation quality. Additionally, visual prompt tuning optimizes feature adaptation, reducing both training and inference time. We validate our approach on standard domain adaptation benchmarks, including SYNTHIA, GTAV, and Cityscapes, using SAM-ViT as the backbone. Experimental results demonstrate superior performance over state-of-the-art methods, achieving faster convergence and lower computational overhead while preserving segmentation performance.

International audience

In response to the challenges of spectrum scarcity and the exponential growth of the number of connected devices, this paper addresses the joint optimization problem of user-base station association, channel assignment and power allocation in a multi-band wireless network, where sub-6 GHz, millimeter wave, and terahertz frequency bands coexist. The problem is formulated as a mixed integer non-linear programming, a known NP-hard problem. Each user requests both a minimum data rate and a minimum reliability level defined by a signal-to-noise ratio. Considering the goal of optimizing the number of satisfied users, this paper proposes a multi-agent deep reinforcement learning solution. Simulation results convincingly demonstrate the effectiveness of our proposed algorithm and its ability to learn fast the best resource allocation solution.

Maritime object detection is crucial for improving the effectiveness of unmanned surface vehicles (USVs), enhancing situational awareness at sea, and strengthening coastal surveillance. Visual understanding is a promising research thematic that can improve the accuracy of ship detection in maritime environment. However, due to the particularities of the maritime environment and the lack of datasets, this field remains limited.In this paper, we propose using Multi-Head Self-Attention (MHSA) to enhance maritime object detection and address the challenges faced. In addition, we conduct a comparative analysis of publicly available maritime datasets to evaluate the performance of different models. Our findings demonstrate that the DETR (DEtection TRansformer), AACN (Attention Augmented Convolutions Networks), and BoTNet (Bottleneck Transformers) models, based on MHSA, exhibit superior detection accuracy and efficiency compared to other existing methods in the maritime domain. This suggests that MHSA is a highly effective approach for improving maritime object detection. Our analysis of the results also provides insights into potential avenues for future research on attention mechanisms in the maritime domain.

Reconfigurable Intelligent Surface (RIS) has recently appeared as a potential candidate technology for future wireless communications with the principal goal of realizing a Smart Radio Environment (SRE), which considers the propagation environment as a controllable element. To reinforce the advantages of the RIS, Channel State Information (CSI) to and from the RIS has to be required. In this paper, we consider a multi-user MISO uplink communication system based on RIS and implement two channel estimation algorithms based on the PARAllel FACtor decomposition (PARAFAC), which are Least Squares (LS) and Alternating Least Squares (ALS), in two different scenarios, transmitarray and reflectarray. Simulation results show that the performance of the proposed channel estimation algorithms based on PARAFAC decomposition is improved with random channel matrices initializations.

To cope with the spectrum scarcity of emerging mobile applications, using higher frequency bands (such as THz) becomes a necessity. Combining simultaneously higher and lower bands is then an important step for future cellular networks. Meanwhile, resource management plays a dominant effect on the system performance especially when different quality of service requirements are considered. In this paper, we formulate and investigate a joint optimization problem of resource allocation in integrated sub-6 GHz, mmWave and THz networks to maximize the system energy efficiency (EE). Therefore, we propose efficient centralized and distributed low-complexity greedy solutions. Also, we propose more efficient multi-agent reinforcement learning (MARL) solutions where users, modeled as agents, collaborate to learn and converge to the optimal user association that maximizes the EE. Simulation results show the EE provided by the proposed solutions and illustrate the superiority of the MARL-based solutions.

In this paper, we study blind equalization techniques to mitigate inter-symbol interference (ISI), and mainly, we are focused on generic blind equalizer (GBE). A GBE has no prior information about the transmission channel or the used constellation. To solve this challenge, a joint generic blind equalizer, based on a new multi-criteria cost function and automatic modulation classification (AMC) is proposed. The new multi-criteria cost function is based on the probability density fitting (PDF) and the k-nearest neighbor (KNN) algorithm is used for the AMC stage. Thus, using a neural architecture, the new criterion is demonstrated in its linear and nonlinear context. Simulation results support our claims with Quadrature Amplitude Modulation (QAM) transmitted signals in single input single output (SISO) communication system and they show a better performance in terms of mean square error (MSE) and symbol error rate (SER) compared to other GBE from the literature.

Exploiting the advantages of both non-orthogonal multiple access technique and millimeter-wave communications requires joint efficient resource allocation techniques toward satisfying the stringent requirements of future mobile communication systems. This paper focuses on a multi-band (i.e., millimeter-wave band and sub-6 GHz band) wireless network where both orthogonal and non-orthogonal multiple access techniques coexist. A joint optimization of user association, transmit power allocation, sub-channel assignment, and multiple access technique selection is investigated to maximize the down-link sum-rate under a minimum rate requirement per user and power constraints. The problem is formulated as a non-convex mixed-integer optimization problem; then, it is proved to be$\mathcal {NP}$-hard. First, simple greedy and meta-heuristic solutions are proposed. Then, since model-based approaches have generally a high computational complexity, model-free centralized and distributed approaches based on deep reinforcement learning technique are proposed. The latter are based on multiple parallel deep neural networks to generate resource allocation solutions. The proposed approaches are evaluated and compared. Simulation results corroborate the high performance offered by the proposed solutions for stationary and mobile users. They also highlight the benefits of employing hybrid orthogonal and non-orthogonal multiple access scheme in multi-band systems in terms of down-link sum-rate and user fairness.

Even though combining multi-access techniques (i.e., orthogonal and non-orthogonal multiple access techniques) and multi-band communications (i.e., millimeter-wave and sub-6 GHz communications) is needed to satisfy the stringent requirements of emerging wireless applications, it triggers new resource management challenges. In this paper, we investigate the joint optimization problem of user association, transmit power allocation, and sub-channel assignment in a such network in order to maximize the down-link sum-rate. The problem is formulated mathematically as a mixed-integer non-linear programming problem. Due to the combinatorial and the non-convex characteristics, solving the problem demands further developed complex mathematical tools. To this end, simple but efficient centralized and fully-distributed greedy-based algorithms are proposed, then, genetic algorithms are presented. Simulation results show the efficiency of the proposed solutions and the effectiveness of using heterogeneous multi-access techniques in terms of down-link sum-rate.

In this paper, we study blind equalization techniques to reduce the intersymbol interference (ISI) and we are particularly interested in equalizers based on probability density fitting (PDF). The PDF criterion was used with conventional linear equalizers. So we try in this paper to use this criterion in a nonlinear context using a neural network architecture. The network weights are updated by minimizing, at first, the stochastic quadratic distance, then the Multimodulus quadratic distance between the equalized PDF and some target distribution. Our approach shows a better performance in terms of mean square error (MSE) and symbol error rate (SER).

This paper studies the joint problem of user association and sub-channel assignment in a wireless network, where orthogonal (OMA) and non-orthogonal multiple access (NOMA) techniques co-exist. We also assume the co-existence of millimeter wave and sub-6 GHz communications. Inspired by the fact that traditional resource allocation methods may not be effective in such heterogeneous multiple access networks (HetNets), a joint optimization problem of user association and sub-channel assignment is formulated where the objective is to maximize the number of associated users. The considered problem is proved to be NP-hard, and therefore an efficient heuristic algorithm is proposed to solve it in a polynomial time. Simulation results corroborate the effectiveness of the proposed algorithm and show that combining OMA and NOMA techniques outperforms single OMA or NOMA technique.

In this paper, we extend the joint use of the Time Reversal (TR) precoding technique and the Ping-Pong Optimized Pulse Shaping (POPS) waveform optimization algorithm to design optimal transmit and receive waveforms for Multiple Input Single Output-Orthogonal Frequency Division Multiplexing (MISO-OFDM) systems. The design process banks on a full characterization of the scattering function of the TR-MISO channel, followed by the implementation of the POPS approach. Numerical analysis reveal a significant gain, brought by the optimized waveforms in TR-MISO-OFDM systems, in terms of Signal to Interference plus Noise Ratio (SINR), compared to the optimized waveforms in TR-SISO-OFDM systems and the PHYDYAS waveform in TR-MISO-OFDM systems.

As sub-6 GHz spectrum is becoming increasingly scarce, millimeter wave (mmWave) bands are considered as one of the key technologies for future cellular networks. Motivated by the rapid growth of the data rate demands and the number of wirelessly-connected devices, this paper considers a hybrid (sub-6 GHz and mmWave) heterogeneous network with a limited number of time-frequency resource blocks (RBs). To overcome the mmWave propagation problems and the need of frequent update of association due to mobility, a novel mobility-aware user-base station association strategy based on Markov chain is proposed. Simulation results validate the performance of the proposed strategy by reducing the need of frequent handovers between mmWave base stations in the network.

The Evolved Variational Message Passing algorithm (E-VMP) and the Cooperative Robust Geometric Positioning Algorithm (C-RGPA) are two novel techniques for cooperative localization in wireless networks. They can perform an accurate location with less computational and time complexity compared to other cooperative localization algorithms. On the other side, limitations on the computational power and battery life present a critical constraint when executing these algorithms. For this reason, we propose in this paper applying these algorithms based on coalitions formation game in order to reduce communication costs. According to our simulation results, the two resulted proposed techniques give accurate location estimates compared to other cooperative localization techniques on the one hand and optimize the power and battery consumption on the other hand.

The necessity of supporting the expected 5G's services, which reveal major limits to ensure strict synchronism and orthogonality, has brought researchers to conceive new waveforms. Recently, the Ping-pong Optimized Pulse Shaping (POPS) algorithm [1] has been introduced as a powerful tool to efficiently design waveforms candidates for 5G. In this paper, we characterize a new design of PHYDYAS waveforms, namely POPS-PHYDYAS, which it is based on the mix of the POPS algorithm and the PHYDYAS waveform [2]. These new waveforms ensure higher SINR level compared to the original PHYDYAS waveforms, as they are conceived by Mirabbasi-Martin [3]. Performances of POPS-PHYDYAS are compared to several 5G waveforms in terms of SIR, OOB emissions and BER.

A major trend of the current research in 5G is to find well time and frequency localized waveforms, dedicated to non‐orthogonal wireless multi‐carrier systems. The ping‐pong optimized pulse shaping (POPS) paradigm was proposed as a powerful technique to generate a family of waveforms, ensuring an optimal signal to interference plus noise ratio (SINR) at the receiver. In this paper, we derive, for the first time, the analytical expression of the SINR for FBMC/OQAM systems. We then adopt the POPS algorithm in the design of optimum transmit and receive waveforms for FBMC/OQAM, with respect to the SINR criterion. For relatively high dispersions, numerical results show that the optimized waveforms provide a gain of 7 dB, in terms of SINR, compared to the PHYDYAS waveform. They also show that the obtained waveforms offer better out‐of‐band (OOB) emissions with regard to those of the IOTA waveform. Furthermore, we notice that FBMC/OQAM systems present a gain of 4 dB in SINR, compared to FBMC/QAM systems, when both operate at their time‐frequency lattice critical densities. However, FBMC/QAM systems can guarantee, with a reduced computational complexity, a comparable performance to FBMC/OQAM systems, in terms of SINR, when their spectral efficiency is relatively reduced by less than 5%.

Power Line Communication (PLC) channel is a fading channel whose their characteristics vary considerably over long distances and at high frequencies, therefore the major challenge, for the researchers, is how to supply robust and efficient communication in PLC systems. To overcome these constraints Cooperative Communication and Network Coding have been demonstrated to be effective techniques. Consequently in this paper, we consider a two-way relaying PLC system in which the Orthogonal Frequency Division Multiplexing (OFDM) is considered for the source 1-to-source 2, the source 1-to-relay and the relay-to-source 2 links where the relay node performs Amplify and Forward (AF) protocol. We propose a conventional bi-directional relaying schema (AF-PLC) which we compare to a schema including a Physical Network Coding (AF-PNC-PLC) for different number of time slots dedicated to exchange data messages between two source nodes S1and S2with the assistance of the relay node R. We also evaluate the data rate for OFDM-based two-way relaying AF-PLC and AF-PNC-PLC systems by applying the adaptive modulation technique.

In this paper, we propose a geometric positioning technique for cooperative localization in Wireless Networks. The proposed technique is based on building geometric constraints from radio observables. These constraints are then merged to estimate the true position. In this paper we address situations where blind nodes, due to the lack of radio observables, cooperate to estimate their positions. Compared to other techniques, Monte Carlo simulations illustrate interesting performances in terms of positioning accuracy and computation complexity and runtime.

Combining millimeter wave (mmWave) with sub-6 GHz communications is a promising solution for future heterogeneous cellular networks (HetNets) to improve coverage and capacity. This paper studies the user-base station association problem in HetNets with the existence of both sub-6 GHz and mmWave base stations (BSs) where each BS has a limited number of resource blocks (RBs). Motivated by the observation that traditional user-BS association methods may not be effective in such hybrid HetNet, an optimization problem is formulated in order to maximize the number of associated users and to ensure an efficient resource utilization by minimizing simultaneously the number of used RBs. Since the formulated problem is proved to be NP-hard, a heuristic algorithm is proposed. Simulation results show that the proposed algorithm approaches the optimal one with a significant reduction in computational complexity.

This paper investigates the efficiency of the combination of the Ping-pong Optimized Pulse Shaping-Orthogonal Frequency Division Multiplexing (POPS-OFDM) algorithm with the Time Reversal (TR) technique. This algorithm optimizes the transmit and receive OFDM waveforms with a significant reduction in the system Inter-Carrier Interference (ICI)/Inter-Symbol Interference (ISI) and guarantees maximal Signal to Interference plus Noise Ratio (SINR) for realistic mobile radio channels in 5G Systems. To this end, we characterize the scattering function of the TR channel and we derive the closed-form expression of the SINR as a Generalized Rayleigh Quotient. Numerical analysis reveals a significant gain in SINR and Out-Of-Band (OOB) emissions, brought by the proposed TR-POPS-OFDM approach.

Powerline network is recognized as a favorable infrastructure for Smart Grid to transmit information in the network thanks to its broad coverage and low cost deployment. The existing works are trying to improve and adapt transmission techniques to reduce Powerline Communication (PLC) channel attenuation and exploit the limited bandwidth to support high data rate over long distances. Two-hop relaying BroadBand PLC (BB-PLC) system, in which Orthogonal Frequency Division Multiplexing (OFDM) is used, is considered in this paper. We derive and compare the PLC channel capacity and the end-to-end Average BER (ABER) for OFDM-based direct link (DL) BB-PLC system and for OFDM-based two-hop relaying BB-PLC system for Amplify and Forward (AF) and Decode and Forward (DF) protocols. We analyze the improvements when we consider the direct link in a cooperative communication when the relay node only transmits the correctly decoded signal. Maximum ratio combining is employed at the destination node to detect the transmitted signal. In addition, in this paper, we highlight the impact of the relay location on the channel capacity and ABER for AF and DF transmission protocols. Moreover, an efficient use of the direct link was also investigated in this paper.

Since PLC channel is a fading channel whose characteristics vary considerably over long distances and at high frequencies the major challenge for researchers in Smart Grid, is how to supply robust and efficient communication. To overcome these constraints Cooperative communication and Network coding have been demonstrated to be effective. Consequently in this paper, we consider a two-way relaying PLC system in which orthogonal frequency division multiplexing (OFDM) is employed for the source 1-to-source 2, the source 1-to-relay and the relay-to-source 2 links where the relay node performs Amplify and Forward (AF) protocol. We consider a conventional bi directional relaying schema (AF-PLC) and we compare it to a schema in which we include Physical Network Coding (AF-PNC-PLC) for different number of time slots dedicated to exchange data messages between two source nodes S1and S2with the assistance of the relay node R. We also derive the channel capacity and sum-average BER (SA-BER) expressions for OFDM-based two-way relaying AF-PLC and AF-PNC-PLC systems without and with cooperative diversity. Moreover, we provide a solution based on sub-carrier pairing technique to further improve the channel capacity and SA-BER performances.

A major challenge for researchers in Smart Grid, is how to supply robust and efficient communication since PLC channel is a fading channel whose characteristics vary considerably over long distances and at high frequencies. To overcome these constraints Cooperative communication and Network coding have been demonstrated to be effective. Consequently in this paper, we consider a two-way relaying network in which orthogonal frequency division multiplexing (OFDM) is employed for the source 1-to-source 2, the source 1-to-relay and the relay-to-source 2 links where the relay node performs Amplify and Forward (AF) protocol. We consider a conventional bi directional relaying schema (AF-PLC) and we compare it to a schema in which we include Physical Network Coding (AF-PNC-PLC) for different number of time slots dedicated to exchange data messages between two source nodes S1and S2with the assistance of the relay node R. We also evaluate the channel capacity for OFDM-based two-way relaying AF-PLC and AF-PNC-PLC systems without/with cooperative diversity. Moreover, we provide a solution based on sub-carrier pairing technique to further improve the channel capacity.

In wideband communication systems, Multi-Input Multi-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) has been proposed as an efficient technique to enhance the link reliability and the spectral efficiency. However, the high Peak to Average Power Ratio (PAPR) of the output signals degrades the advantage of the MIMO-OFDM systems. In order to overcome this issue, several methods requiring the explicit transmission of Side Information (SI) bits have been investigated in the literature. Nevertheless, the wrong estimation of the SI leads not only to a damage on the total signal recovery but also to a loss of the entire OFDM sequence which, causes severe degradation in the system performance. Additionally, the transmitted bits must be channel-encoded as they are particularly susceptible to the error performance of the OFDM system, which highly increases the complexity and the end-to-end latency. Therefore, we propose in this paper a blind and reduced complexity technique for MIMO-OFDM systems under high frequency selective channels. At the transmitter side, the proposed method exploits a new form of embedded signaling such as the use of the Zadoff-Chu matrix transform. Regarding the receiver side, the proposed method exploits simultaneously an enhanced Alamouti decoder scheme and an optimized estimation process that is based on calculating the high order statistic of the received signal. Finally, performances evaluation show the usefulness of the proposed methods in Long Term Evolution (LTE) standards.

Recently, Orthogonal Frequency Division Multiplexing (OFDM) has gained more attention as an effective technique for high data rate future wireless communication systems. In order to provide maximal spectral efficiency, the prototype waveform, used in these systems, must guarantee orthogonality even the rapidly time-varying and strongly delay-spread characteristics of the channel propagation. However, its performance gain degrades in the presence of the system Inter-Carrier Interference (ICI) and Inter-Symbol Interference (ISI) which make it essential to develop an efficient technique to overcome these interference over the time-frequency dispersion of the radio mobile channel. In this paper, we propose a Ping-pong Optimized Pulse Shaping-OFDM (POPS-OFDM) algorithm that maximizes the received Signal to Interference plus Noise Ratio (SINR) by systematically optimizing the OFDM waveforms at the Transmitter (TX) and Receiver (RX) sides. We derived the exact closed-form expression of the SINR of the considered multicarrier system and the optimized waveform is searched as a linear combination of several of the most localized Hermite functions. The results confirm the advantage behind the POPS-OFDM algorithm in enhancing the performance compared to multicarrier systems using conventional waveforms. Simulations are given to support our claims.

Power Line Communication (PLC) remains the most appropriate communication architectures and technology for Smart Grid (SG) deployment. A major challenge for researchers in SG, is how to supply robust and efficient communication since PLC channel is a fading channel whose characteristics vary considerably over long distances and at high frequencies. To reach this goal, cooperative communication has been proven to be effective. Thus in this paper, we derive the channel capacity for OFDM-based two-hop relaying PLC system where we use a relay node between the source and destination nodes. We analyze channel capacity for Amplify-and-Forward (AF), Decode-and-Forward (DF) relaying protocols and Fountain-code-and-Forward (FCF) protocol which joint cooperative relay and coding techniques. We highlight in this paper how the use of this new category of cooperation relaying protocol (FCF) increases channel capacity of an OFDM-based two-hop relaying PLC system.

This paper studies the energy allocation for sensing and data transmitting in communication systems with energy harvesting sensor nodes. The investigated system consists of a point-to-point data transmission between two energy harvesting nodes that have limited batteries capacity and communicating over a wireless fading channel. The transmitter aims to optimize the throughput over slotted system and in an infinite horizon subject to time-varying conditions. These conditions include the energy harvested at both nodes, available energy at both nodes and the channel state. The energy allocation problem is formulated as a sequential decision problem. An optimal algorithm is given and a low-complexity suboptimal energy allocation algorithm is also proposed. Simulation results show the gain when the transmitter takes into account the state of energy at the receiver and that the proposed heuristic algorithm achieves near-optimal number of transmitted bits with lower complexity.

Due to high mobility situations that are commonly envisaged for the next Fifth Generation (5G) of mobile communication systems, the wireless propagation channel becomes a time-frequency variant, where the time dispersion emerges from the multipath characteristic and the time-selectivity arises from the Doppler spread. This aspect can dramatically damage the waveforms orthogonality that is induced in the Orthogonal frequency division multiplexing (OFDM) signal. Consequently, this results in oppressive Inter-Carrier Interference (ICI) and Inter-Symbol Interference (ISI), which leads to performance degradation in OFDM systems. To efficiently overcome these drawbacks, we propose Ping-pong Optimized Pulse Shaping-OFDM (POPS-OFDM ) algorithm that maximizes the received Signal to Interference plus Noise Ratio (SINR) by optimizing systematically the OFDM waveforms at the Transmitter (TX) and Receiver (RX) sides. We derived the exact closed-form expression of the SINR of the considered multicarrier system and the optimized waveform is searched as a linear combination of several of the most localized Hermite functions. Then, we go further by testing its robustness against time synchronization errors. The results confirm the advantage behind POPS-OFDM algorithm in enhancing spectacular performance and its robustness compared to multicarrier systems using conventional waveforms. Simulations are given to support our claims.

Cooperative multiband spectrum sensing presents the next generation of cognitive radio networks, where multiple bands are sensed and accessed to improve spectrum maintenance and to enhance the network throughput. In order to concretize this concept, several uniform cooperative spectrum sensing techniques have been proposed in literature which suffers from a high complexity computation over the global sensing scheme. To overcome this limitation, this work proposes a robust and efficient spectrum sensing technique. The proposal investigates a new alternative of Single-Pixel-Camera adaptation of the cooperative multiband spectrum sensing for Cognitive Radio. Instead of using the conventional uniform band measurements, we investigate a non-uniform approach, where the time of sensing is reduced by using a hard and soft decision metric. Moreover, this approach allows to enhance the performances in terms of spectrum sensing. Simulation results are given to support our claims.

Wireless mesh networks (WMNs) have been developed to answer the needs of many wireless applications. A major limiting parameter of the performance of WMNs is the interference between the several communications that occur simultaneously in the same network. To address this limitation, an adequate scheduling algorithm has to be implemented. Hence, this paper focuses on the scheduling problem under the physical interference model. This problem is known to be NP-Hard problem. In this paper we develop and propose two efficient scheduling algorithms. We evaluate their performances by simulation in terms of spatial reuse and we compare their performance with known previously-proposed algorithms. We show that our proposed algorithms provide high performances with low complexity.

Selected Mapping (SLM) is a promising technique dedicated to reduce the Peak-to-Average Power Ratio (PAPR) in OFDM systems. In this technique, different representations of OFDM symbols are generated by rotating the original frame using different phase sequences. Then, the signal having the minimum PAPR is selected and transmitted. To compensate the effect of the phase rotation at the receiver side, it is necessary to transmit the index of the selected phase sequence as an explicit Side Information (SI). In this paper, we propose a novel robust blind SLM technique that avoids sending any explicit (SI), where the selected signal index (SI) is embedded in the transmitted data by using an adequate transformation such as the Hadamard one. Furthermore, in order to recover the used (SI) index, we propose an optimized scheme which exploits mainly the higher-order statistics moments and cumulants of the received signal. We show that our proposed method guarantees a reliable signal recovery at the receiver side and dramatically reduces the PAPR level at the transmitter side. Simulation results are given to support our claims.

Orthogonal Frequency Division Multiplexing (OFDM) technique is a promising modulation scheme for high performance broadband wireless communications. This technique suffers from a major drawback which is the high Peak to Average Power Ratio (PAPR) of the output signals. In order to resolve this issue, several methods that require the transmission of explicit side information (SI) have been proposed. In this paper, we propose two robust blind techniques that offer the possibility to avoid the transmission of any explicit (SI). First, we investigate a new technique refered as Blind Dummy-Zero-Insertion (DZI) which uses an adequate embedded signaling, consisting of a special matrix mask. Second, in order to enhance the signal detection process and the PAPR gain, we combine the proposed technique with the SLM method as Combined-SLM-DZI. Both methods employ an optimized scheme, during the estimation process, based on calculating the energy of the received signal. Performance evaluation shows the advantage of the proposed methods on the PAPR reduction and also proves the perfect signal recovery at the receiver side.

In this paper we propose novel efficient algorithms that allow optimal waveform design for multicarrier systems, specifically for the Orthogonal Frequency Division Multiplexing (OFDM) based systems. We start from the rapidly time-varying and strongly delay-spread characteristics of the prorogation channel that are used for such transmission systems and include them in the closed-form expression of the Signal to Interference plus Noise Ratio (SINR) of the considered multicarrier system. Using our algorithms for maximizing the derived SINR expression leads to obtain the optimal waveforms at both the Transmitter (Tx) and the Receiver (Rx) sides, that significantly reduce the system Inter-Carrier Interference (ICI)/Inter-Symbol Interference (ISI) and guarantee maximal SINRs for realistic mobile radio channels. Our proposed algorithms allow to design waveforms at the Tx/Rx sides that are adapted to the channel propagation conditions and hence result in spectacular performance enhancement compared to multicarrier systems using conventional waveforms. Simulation results are given to support our claims.

In this paper, we propose a novel optimized blind selected mapping (SLM) technique that avoids the need of the use of any side information (SI) through the joint exploitation of a set of rotated and unrotated QAM constellation of the Orthogonal Frequency Division Multiplexing (OFDM) signal and that consequently performs the role of an inherent embedded signaling for the OFDM system. Furthermore, in order to efficiently recover the transmitted sequence, we propose a set of decision schemes that banks on the Max-Log-Maximum A Posteriori (MAP) algorithm from which we investigate hard and soft decision processes. Our proposed method guarantees a reliable and perfect signal recovery at the receiver side and dramatically reduces the peak-to-average power Ratio (PAPR) level at the transmitter side. Simulation results are given to support our claims.

Eigenvalue based detection is one of the most promising blind spectrum sensing techniques in cognitive radio. However, it suffers from computational complexity resulting from sample covariance matrix computation and eigenvalue decom-position. In this paper, we propose a reduced-complexity blind detection algorithm to detect the presence of a main direction in terms of energy. Instead of eigenvalue decomposition, our method is based on a series of beamforming using simple beam patterns to reduce computational complexity. Simulation results show that our method provides acceptable performances compared to the well-known Maximum to Minimum Eigenvalue (MME) method with a considerable gain in computational complexity.

In this paper, we propose a novel approach for multiple antenna spectrum sensing based on compressed sensing. Our focus is on the angular sparsity of the received signal given an unknown number of primary user source signals impinging upon the antenna array from different Directions Of Arrival (DOA). Given multiple snapshots over a small time period, multiple measurement vectors are available and a joint sparse recovery is performed to estimate the common sparsity profile over the angular domain. In this estimation process, we employ the regularized M-FOCUSS algorithm [1], which is the noisy multiple snapshot extension of the iterative weighted minimumnorm algorithm, called FOCUSS. The contribution of this paper is to take advantage of the sparse primary user DOA estimation within the detection framework of multiple antenna spectrum sensing. In this scope, an accurate sparse reconstruction is not required and a coarse estimation using a reduced number of snapshots is sufficient to decide about the number of present primary users reflected by the angular sparsity order of the received signal. A simulation study shows significant constant false alarm rate performance gain of the proposed approach compared to the conventional maximum to minimum eigenvalue detector especially when the number of PUs increases.

Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) is a promising modulation scheme for high performance broadband wireless communications that suffers from a major drawback, which is the high Peak-to-Average Power Ratio (PAPR) of the output signals. In this paper, we propose a new blind combined Alamouti Space-Time Bloc Codes (STBC) approach inspired from the Selected Mapping (SLM) process to solve this PAPR issue for MIMO-OFDM systems. Our solution is based on a specific STBC patterns from which we construct precoding sequences forming a codebook that ensures the role of an inherent embedded signaling for the MIMO-OFDM system. Furthermore, in order to efficiently recover the transmitted sequence, we propose a set of decision schemes that banks on the Max-Log-Maximum A Posteriori (MAP) algorithm. To significantly improve the obtained results, we add another embedded signaling through a rotated and unrotated QAM constellation set. Both embedded signallings lead to a combined SLM-Alamouti technique for which we investigate a powerful decision process. We show that our proposed method guarantees a reliable and perfect signal recovery at the receiver side and dramatically reduces the PAPR level at the transmitter side. Simulation results are given to support our claims.

In this paper, we consider the transmission coordination among multiple cell sites, namely the Coordinated MultiPoint (CoMP) transmission scheme, where several Base Stations (BSs) cooperate to serve a set of Mobile Stations (MSs) and both BSs and MSs are equipped with multiple antennas. We model this multicell cooperative system under the presence of channel estimation errors that can significantly influence the obtained results. We derive the exact sum rate expression of the multicell cooperative system in the presence of channel estimation errors and we evaluate the performance of the Block-Diagonalization (BD) and Zero-forcing (ZF) beamforming approaches. Furthermore, we investigate a power allocation policy that maximizes the system sum rate in the presence of channel estimation errors. We show that in the multicell cooperative system, the performance of the BD or ZF beamforming approaches in terms of the maximization of the system sum rate, depends essentially on the system configuration parameters (i.e., number of antennas per BS and per MS). Simulation results are given to support our claims.

Selective OFDMA is a powerfull relaying technique with subcarrier based selection. This scheeme has a high potential to considerably improve the performance of cooperative OFDM systems. However, in practice, the implementation of this technique may suffer from multiple problems caused by the separation of the subcarriers from each other's. In this Contribution, we propose a new selection scheme denoted “Optimized Selective OFDMA” that approaches selective OFDMA performance in terms of outage probability while reducing its synchronization problems that may be caused by the subcarriers separation. The outage probability and diversity order of the proposed scheme are derived. The number of the used paths is also analyzed. We proved that for high SNR, the introduced scheme gives exactly the same performance of selective OFDMA with only one path for all the subcarriers.

In this paper, we present a novel efficient algorithm for the estimation of the Channel Impulse Response (CIR) when this CIR is sparse (meaning a big number of the CIR coefficients are equal to zero) for multicarrier systems using Orthogonal Frequency-Division Multiplexing (OFDM) transmission. The derivation of this CIR estimation algorithm investigates first the sparse structure of the channel through the modeling of the sparse CIR as a Bernoulli-Gaussian process. This established modeling will allow us to exploit the relationship between the Reed-Solomon (RS) codes and the OFDM modulator to efficiently estimate the sparse CIR. To do so, we consider the pilot tones that are usually scattered among the information sequence for the synchronization or equalization purposes, as syndromes in order to estimate the sparse channel coefficients, and we prove that using our proposed algorithm, the obtained estimates are unbiased and that the estimation error is quasi-optimum. Furthermore, our proposed technique keeps valid even in the case where the pilots tones are assumed to be not uniformly placed in the transmitted sequence provided that their positions satisfy a repartition condition. Simulation results are presented to illustrate the performance of our proposed algorithm and to support our claims.

In this contribution, we investigate Decode and Forward (DF) OFDM Ad-hoc Routing strategy with bottleneck maximization. We derive the exact outage probability and diversity order for the different scenarios: with and without subcarrier grouping and with and without joint selection, where joint selection refers to the selection of the last two hops together. When joint selection is performed, numerical results show that a power gain can be obtained when using subcarrier grouping technique.

The title of the above cited paper (ibid., vol. 56, no. 8, pp. 4157-4165, Aug. 10) was printed incorrectly. The correct title is "On the Use of the First- and Second-order Sigma-Delta Quantizers in the Context of Oversampled Filter Banks."

In this paper, we extend the results that we derived in , to the case of filter banks (FBs) based transmission. We consider first- and second-order sigma-delta (SD) quantization in the context of an oversampled digital Fourier transform (DFT) FBs (DFT-FBs). In this context, we investigate the case of Odd- and Even-stacked DFT FBs. We establish the set of conditions that guarantee that the reconstruction minimum squares error (MSE) behaves as1/(r2) whererdenotes the frame redundancy and we derive the corresponding MSE upper-bounds closed-form expressions. The obtained results demonstrate that overoversampled FBs that are subject to the first- and second-order SD can exhibit a reconstruction error behavior according to1/(r2). Furthermore, the established results are shown to be true under the quantization model used in [3]-[6], as well as under the widely used additive white quantization noise assumption.

We propose a new decoding algorithm based on a cascade structure for impulsive noise correction in multicarrier systems such as orthogonal frequency division multiplexing (OFDM) based systems. This new cascade structure based algorithm has the advantage to lead on one hand to a reduced complexity implementation in an OFDM demodulator and on the other hand to overcome the lacks of other algorithms dedicated for impulsive noise correction. To do so, we start the derivation by investigating closed-form analytical expressions of the a priori probabilities used in hypotheses tests that are necessary for the different steps needed for the execution of the cascade structure based decoding algorithm. Such closed-form expressions for the a priori probabilities, result in efficient setups of the threshold values used for the execution of the decoding algorithm. Furthermore, we show that this cascade structure can be applied to efficiently cancel the impulsive noise in OFDM systems. As the clipping event, present in OFDM systems, can be seen as an additive impulsive noise, we prove that after introducing some minor modifications, we can apply the proposed cascade structure to significantly reduce the peak to average power ratio (PAPR) level in such systems. Simulation results are given to illustrate the usefulness of the proposed algorithm results in practical OFDM based communication systems such as Hiperlan 2.

In this paper, we consider sigma-delta (SD) quantization of geometrically uniform (GU) finite frames. In the first part, we prove that under some conditions, the variant I and II permutation modulation (PM) codes, first introduced by Slepian (1968, 1965), can belong to the class of GU frames. Then, we focus essentially on a subclass of a GU frame, namely, cyclic geometrically uniform (CGU) frame, family of frames containing finite harmonic frames (both in \BBCMand \BBRM). For first- and second-order SD quantizers, we establish that the reconstruction minimum squares error (MSE) behaves as [ 1/(r2)] whererdenotes the frame redundancy. This result is shown to be true both under the deterministic quantization model used in Benedetto (2004), Benedetto (2006), and Yilmaz (2001) as well as under the widely used additive white quantization noise assumption. For the widely usedLth-order noise shaping filterG(z)=(1-z-1)L, we show that the MSE behaves as [ 1/(r2)] irrespectively of the filter orderL. More importantly, we prove also that in the case of tight and normalized CGU frame, when the frame length is too large compared to the filter order and under some conditions on the quantizer, the reconstruction MSE can decay as fast asO([ 1/(r2L+1)]). Finally, it is shown that degrees of freedom in CGU frames, when compared to harmonic frames, result in a smaller MSE, albeit MSE prop [ 1/(r2)] in both cases.

We consider sigma-delta quantization of cyclic geometrically uniform (CGU) finite frames, family of frames containing finite harmonic frames (both in CMand RM). For first- and second-order sigma-delta quantizers, we establish that the reconstruction minimum squares error (MSE) behaves as 1/r2where r denotes the frame redundancy. This result is shown to be true both under the quantization model used in J.J. Benedetto et al. (2004) as well as under the widely used additive white quantization noise assumption. For the widely used L-th order noise shaping filter G(z) = (1 - z-1)L, we show that the MSE behaves as 1/r2irrespectively of the filter order L. More importantly, we prove also that in the case of tight and normalized CGU frame, when the frame length is too large compared to the filter order, the reconstruction MSE can decay as faster as O(1/r2L+1).

This paper presents a new view of the Bose-Chaudhuri-Hocquengem (BCH) code through the addition of some flexibility to the syndromes distribution in the transmitted sequence. In order to get this flexibility, we derive a necessary condition (NC) on the syndromes distribution for decoding BCH codes, which includes the already known Hartmann-Tzeng proposition. This NC is essentially deduced from the decoding process of BCH code, and is related to the locator polynomial and the requested constraints to guarantee a maximal error-correction capacity. The obtained results have the advantage to be applicable for any considered field (finite or not). Furthermore, we prove that when the correction capacity is equal to 2 or 3, the obtained NC becomes also sufficient. This result is very useful in some practical transmission systems such as orthogonal frequency-division multiplexing systems. Once the pilot tones considered in such systems verify the necessary and sufficient condition, it becomes possible to both reduce the peak-to-average-power rate and correct the impulse noise, present in such multicarrier systems. The usefulness of the presented analysis and the exploitation of the derived condition on the pilot tones distribution is illustrated by simulation results in the case of the Hiperlan2 system

A parallel between Reed-Solomon codes in the complex field and multicarrier transmission using orthogonal frequency-division multiplexing (OFDM) is first presented. This shows that when the signal is sent over some channel composed of Gaussian plus impulsive noise, the impulsive noise can be removed by a procedure similar to channel decoding, using information carried by the "syndrome." This result is first derived in a simple situation (oversampled discrete multitone, additive channel), which is merely of theoretical interest. In any case, consecutive zeros, in the output of the OFDM modulator, do not correspond to real subcarriers. Pilot tones are transmitted for synchronization or channel-estimation purposes. These pilot tones are generally scattered among the information ones. Our approach is to use these pilot tones as syndromes, in order to correct impulsive noise. We show that the correction capacity is conditioned by the position of these pilot tones in the transmitted sequence. A protection subsystem based on hypotheses tests is introduced after the decoding operation in order to detect malfunctions of this decoder. The efficiency of this technique is corroborated with simulations in the slightly modified Hiperlan2 context. Other extensions are then provided in order to increase the practical usefulness of the method.

The similarity between Reed Solomon codes in the complex field and multicarrier (OFDM) systems can be useful to correct impulse noise. This similarity is best seen when the input of the IFFT in the OFDM modulator has some consecutive zeros. However, this case is merely of theoretical interest, since consecutive zeros, in the OFDM modulator, do not correspond to real subcarriers. However in many cases, pilot tones are generally scattered among the information subcarriers. Our approach is to use these pilot tones as syndromes in order to correct impulse noise. This paper presents a number of interesting results relating on the distribution of pilot tones in the emitted sequence, where we have a necessary condition under which a maximal correction capacity is guaranteed. This necessary condition is also sufficient in the two simple cases, where the correction capacity is 2 or 3. Efficiency of this technique is illustrated by simulations in the practical context of Hiperlan2.

In this contribution, we propose a cascade structure to improve the impulse noise cancellation algorithm that we have already presented in F. Abdelkefi, P. Duhamel and F. Alberge [2002]. The new structure of this decoding algorithm is easy to implement and reliable (several parameters can be obtained theoretically rather than tuned experimentally). We also show that this decoding algorithm can be used for eliminating impulse noise and for reducing the peak-to-average power ratio (PAPR) level. The efficiency of this technique is corroborated by simulations in the practical context of Hiperlan2.

In OFDM systems, pilot tones are emitted for synchronization or channel estimation purposes. These pilot tones are generally scattered among the information ones. Our approach is to use these pilot tones as syndromes, in order to correct impulse noise. We previously proposed (see Abdelkefi, F. et al., ISSPA, 2001) a decoding algorithm in three steps: (1) estimate the amount of impulse noise; (2) seek the location; (3) correct the errors. A protection subsystem was introduced after the decoding operation in order to detect malfunction. Indeed, we added a control step which is able to estimate carefully whether the decoding procedure has worked correctly. We now explain this a posteriori control which is based on the hypothesis test. This approach is new in impulse noise cancellation in multicarrier transmission. The efficiency of this technique is also corroborated with simulations in the practical context of HIPERLAN/2.

A parallel between Reed Solomon codes in the complex field and multicarrier transmission using OFDM is first presented. This shows that when the signal is sent over some channel composed of Gaussian plus impulse noise, the impulse noise can be removed by a procedure similar to channel decoding, using information carried by the "syndrome". These results are first derived in a simple situation (oversampled DMT, additive channel), which is merely of theoretical interest. Several extensions are then provided in order to increase the practical usefulness of the method. Simulations combining classical convolutive codes with the above mentioned approach are provided.