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In this paper, we introduce a newly developed MMSE-based digital precoder, the called Tunable MMSE (T-MMSE), to address cross-interference (CI) among user equipments (UEs) in a multi-user (MU) massive multiple-input multiple-output (mMIMO) downlink (DL) communication scenario. Compared to the conventional MMSE precoder, our approach adds a tunable constraint that enables the base station (BS) to regulate CI affecting specific UEs. After deriving the theoretical expression for the proposed optimal T-MMSE, we evaluate the influence of the tuning parameter on the performance of the communication. On top of our proposal, we also introduce a sub-optimal version with significantly reduced computational complexity. Simulation results show its strong flexibility in CI regulation, making it a superior solution to MMSE in various real-world communication scenarios.

Direction of arrival (DoA) estimation is a common sensing problem in radar, sonar, audio, and wireless communication systems. It has gained renewed importance with the advent of the integrated sensing and communication paradigm. To fully exploit the potential of such sensing systems, it is crucial to take into account potential hardware impairments that can negatively impact the obtained performance. This study introduces a joint DoA estimation and hardware impairment learning scheme following a model-based approach. Specifically, a differentiable version of the multiple signal classification (MUSIC) algorithm is derived, allowing efficient learning of the considered impairments. The proposed approach supports both supervised and unsupervised learning strategies, showcasing its practical potential. Simulation results indicate that the proposed method successfully learns significant inaccuracies in both antenna locations and complex gains. Additionally, the proposed method outperforms the classical MUSIC algorithm in the DoA estimation task.

This paper introduces the theoretical derivations for establishing the bit error rate (BER) expressions of distributed antenna systems (DAS) over partially blocked Rayleigh fading channels. Clustered delay line models from 3GPP are considered with a subset of blocked propagation components. Assuming the receiver cannot update its equalizer during blockage events, a statistical analysis of the erroneously equalized channel gains is performed to provide the probability density functions of the received symbols depending on the blockage. BER derivations are then obtained and validated through simulations. The provided expressions allow predicting the performance of DAS and accurately analyze the impact of various blockage scenarios.

This paper presents theoretical derivations for predicting the bit error rate (BER) of distributed antenna systems (DAS) in 3GPP clustered delay line channels with partial blockage accounting for typical millimeter wave (mmWave) propagation conditions. Assuming that the receiver equalizer is not updated during sudden blockage events, a statistical analysis is led to provide the probability density functions for received symbols under such blockage conditions. Three beamforming techniques—maximum ratio transmission (MRT), beamsteering (BS), and a proposed combination of BS with phase compensation (PC)—are considered in line-of-sight scenarios. Analytical BER predictions of the proposed PC-BS are validated through simulations, offering insights for optimizing DAS in mmWave environments. In particular, we conclude that PC-BS performs very close to MRT while being much simpler to implement and much more suited to mmWave electronics.

This paper investigates the impact of Line-of-Sight (LoS) path misalignment in distributed Multiple-Input Single-Output (MISO) systems, particularly in millimeter-wave (mmWave) bands where phase synchronization and timing precision are critical. The goal is to validate a bit error rate model under practical OFDM transmission scenarios involving multiple access points communicating with user equipment. We highlight how time misalignment between LoS paths can degrade system performance and evaluate the effectiveness of various compensation strategies under such conditions. A key contribution of this work is the proposed compensation technique for LoS path misalignment. By applying a frequency-dependent linear phase shift to each subcarrier—an operation that is both low in complexity and easy to implement—we induce a circular rotation of the OFDM time-domain symbol. This rotation effectively aligns the various LoS contributions in time, as long as the path delays remain within the cyclic prefix duration. Notably, the method is fully compatible with analog beamforming architectures, which are essential in mmWave systems to reduce the number of costly RF chains. As a result, the proposed strategy enables efficient time compensation with minimal computational and hardware overhead, making it particularly attractive for distributed Multiple-Input Multiple-Output (MIMO) deployments at mmWave frequencies.

Channel charting (CC) consists in learning a mapping between the space of raw channel observations, made available from pilot-based channel estimation in multicarrier multiantenna system, and a low-dimensional space where close points correspond to channels of user equipments (UEs) close spatially. Among the different methods of learning this mapping, some rely on a distance measure between channel vectors. Such a distance should reliably reflect the local spatial neighborhoods of the UEs. The recently proposed phase-insensitive (PI) distance exhibits good properties in this regards, but suffers from ambiguities due to both its periodic and oscillatory aspects, making users far away from each other appear closer in some cases. In this paper, a thorough theoretical analysis of the said distance and its limitations due to ambiguities is provided. Consequently, a new channel distance especially designed to remove ambiguities is proposed. Guidelines for designing systems capable of learning quality charts with the proposed distance are also derived. Experimental validation is then conducted on synthetic and realistic data in different scenarios.

In this paper, we study the behavior of a multiple-input multiple-output (MIMO) full-duplex (FD) system according to two different models of the self-interference (SI) channel inherent to the FD communication strategy: the spherical wave model (SWM) and the planar wave model (PWM). More precisely, we evaluate the received SI power at the receiver antenna array by changing the relative geometrical position of the transmitter antenna array in respect to the latter. Our study shows a significant difference between the two models. In particular we theoretically show as well as through simulation that the SWM for the SI channel is more precise than the PWM, and should then be considered for practical applications of the FD concept.

Massive MIMO systems are highly efficient but critically rely on accurate channel state information (CSI) at the base station in or-der to determine appropriate precoders. CSI acquisition requires sending pilot symbols which induce an important overhead. In this paper, a method whose objective is to determine an appropriate precoder from the knowledge of the user’s location only is proposed. Such a way to determine precoders is known as location based beamforming. It allows to reduce or even eliminate the need for pilot symbols, depending on how the location is obtained. the proposed method learns a direct mapping from location to pre-coder in a supervised way. It involves a neural network with a specific structure based on random Fourier features allowing to learn functions containing high spatial frequencies. It is assessed empirically and yields promising results on realistic synthetic channels. As opposed to previously proposed methods, it allows to handle both line-of-sight (LOS) and non-line-of-sight (NLOS) channels.

In this paper, we provide new blind spectrum sensing (SS) methods based on a machine learning (ML) model to overcome the effects of multipath channels. We introduce three ML methods in order to improve the detection of the primary user (PU) in a cognitive radio network in severe multipath environment. The ML approaches proposed here are the Naive Bayes Classifier (NBC), the Support Vector Machine (SVM) and the Artificial neural network (ANN). The non-linear separation of the training samples provided by ML features is a good alternative to avoid miss-detection or false alarm obtained with classical fixed threshold detection. Simulations shows that the proposed algorithms outperform classical non-cooperative SS algorithms based on the eigenvalues of the covariance matrix of the received signal. The proposed SS detectors based on ML algorithms are concluded to be good candidates for PU detection over multipath channels as in indoor scenarios, especially in low signal to noise ratios (SNR).

In this paper, we investigate the effects of Phase Noise (PN) on the Array Factor (AF) and beamforming gain of massive MIMO mmWave systems. We present different PN models based on the Local Oscillators (LO) architecture. We then study the impact of those PN models on the Array Factor and beamforming gain. We introduce novel analytical bounds for the asymptotic AF Mean Squared Error (MSE) and asymptotic Gain Loss (GL) due to PN in a MIMO system. We then show the validity of our bounds through simulations. We also provide a statistical study on the underlying probability distributions for both the GL and the effective beam steering direction. The parametric study of the fitted distribution parameters with the number of antennas of the Base Station (BS) provides new overviews on how to model the massive MIMO array factor under PN effects.

Millimeter wave communication systems define a new paradigm for wireless communications. At such high frequencies, multi-input multi-output (MIMO) processing is done on the radio-frequency signals to limit the hardware complexity and the energy consumption. Consequently, the channel experienced by the receiver directly depends on the transmitter and receiver antenna array responses, making the determination of the analog precoder and combiner an intertwined problem. In this paper, we propose a procedure capable of calculating analog weights at the transmitter and at the receiver, which allows the maximization of the wideband spectral efficiency for single stream transmission single user MIMO (SU-MIMO). While solely relying on partial channel state information (CSI), our procedure has close performance to full CSI-dependent schemes.

Many millimeter wave systems embed phased array antennas to overcome the large path loss that is experienced at such high frequencies. Digital Fourier Transform based beam-forming (DFT-BF) is often implemented as a low-complexity and very limited feedback technique. Although DFT-BF is optimal in pure Line-of-Sight scenarios, it is substantially outperformed in richer scattering environments by more advanced approaches such as Eigenvector-based beamforming (Eigen-BF). The latter is harder to implement in practical scenarios due to its computational complexity and amount of feedback. In this paper, we propose several solutions to alleviate those drawbacks and analyze various performance-complexity trade-offs in the perspective of a practical usage of Eigen-BF solutions.

In this paper, we analyze the impact of reducing the Peak to Average Power Ratio (PAPR) of a time domain Orthogonal Frequency Division Multiplexing (OFDM) signal before its compression, as required for the transmission of IQ samples in a Centralized Radio Access Network architecture. The analysis is performed considering a clipping function for PAPR reduction. First, the distribution of the clipped OFDM IQ samples is obtained which in turn allows to derive the threshold and codebook levels of a non-uniform quantizer optimized for clipped IQ samples and the number of representation bits for each quantized levels in the entropy coding stage. Then, we provide a closed-form expression for the Modulation Error Ratio of the compressed and clipped OFDM signal. The simulation results show that the Gaussian quantizer applied to a clipped signal is not quite robust compared to a quantizer that has been optimized w.r.t. the distribution of clipped IQ samples, especially in the low-rate quantization region.

This paper presents a new blind spectrum sensing (SS) algorithm based on a machine learning model: the radial basis function support-vector machines (RBF-SVM). As features, the introduced approach uses statistical tests that are based on the eigenvalues of the received signals covariance matrix. Since the decision on the frequency resource occupancy is in fact an issue of labeling binary data, SVM is intended as a potential technique for SS paradigm. The flexibility of SVM for linearly non-separable and high dimensional data makes it a good candidate for our issue, particularly that we consider low signal to noise ratios (SNR). Computer simulations shows that the proposal outperforms classical non-cooperative SS algorithms.

Channel extrapolation is a promising technique to estimate the Channel State Information (CSI) in multi-input-multi-output (MIMO) systems operating in frequency division duplex (FDD) without relying on costly terminal feedback. In this paper we analyze the limits that can achieve the extrapolation of the frequency response of a propagation channel from its cluster-based representation. This method consists in measuring all the clusters characteristics (angle of departure, gain, delay) on the uplink and then extrapolating the downlink channel from those measurements. We propose a framework in which the limits of a cluster-based extrapolation process are studied taking into account delay and angular spread derived from the Saleh-Valenzuela model. We evaluate the performance of the optimal linear estimator hereby quantifying the extrapolation residual error bound in terms of Mean-Square Error and Reduction of the Beamforming Gain.

In this work, we present a novel strategy aiming at obtaining higher energy efficiency in mm-wave digital massive MIMO systems. The proposed approach consists in a joint optimization of time-domain digital beamforming and Tone-Reservation based Peak-to-average Power Ratio (TR-PAPR) reduction. The main idea is to perform broadband beam-steering by adding progressive time delays to the reduced PAPR signals fed to the antennas. These time delays are implemented in digital baseband through time-domain fractional delay filter banks (TDFDFBs). Simulation results show that the increment in MER due to PAPR reduction is maintained for the progressively delayed signals for beam-steering generated by interpolation at the output of the filter bank. As a result, the required power amplifiers (PAs) can all be biased with a lower input back-off (IBO) operation point, leading to significant energy savings while keeping low levels of in-band distortion.

In this paper, we provide a theoretical analysis on the performance of the famous Gradient-based Tone-Reservation PAPR reduction algorithm. To that end, we study the amplitude statistical distribution of the time domain OFDM signals to which PAPR reduction has been applied. Such distribution is then integrated into a generic EVM expression in order to provide a closed form expression of this latter, which is validated and analyzed through numerical simulations. Thanks to this work, we provide theoretical tools to analytically assess the performance of the Gradient method relatively to the optimal TR algorithm, and hence allow further analysis about the complexity-PAPR reduction efficiency trade-off of TR PAPR reduction algorithms, which could be useful for the optimization of the power efficiency of any multicarrier system.

The main goal of this article is to accurately quantity the gain in energy efficiency that can be obtained by combining PAPR reduction techniques with beamforming in the context of massive MIMO communications. To this purpose, we first derive and analyze the expressions of sum capacity, power consumption, and energy efficiency for hybrid, digital and analog beamforming for massive MIMO systems in the millimeter wave frequency range. Then, we use these results to derive and quantity the gain in energy efficiency at system level that can be obtained by combining PAPR reduction for improved power amplifier efficiency with beamforming in massive MIMO systems. In addition, we derive the expressions allowing to determine the optimal amount of antennas M that should be connected to each RF chain in a partially connected hybrid beamforming scheme in order to maximize the systems energy efficiency. Evaluation of the derived expressions clearly show that a noticeable gain in the systems energy efficiency is obtained when PAPR reduction is added, and allows to analyze the advantages and disadvantages of each approach from an energy efficiency point of view.

In this study, the authors propose a novel architecture based on the combination of peak‐to‐average power ratio (PAPR) reduction with digital beamforming (BF) for mm‐wave massive multiple‐input multiple‐output (MIMO) systems. In order to keep the power amplifiers (PAs) working at the same input back‐off thus maximising the system power efficiency, they propose to perform time‐domain transmit beam‐steering by adding progressive time delays to the signals at each antenna element, while keeping the amplitude weights unitary. They show that these time delays can be obtained with a finite impulse response filter implementation of time‐domain fractional delay filter structures such as Lagrange interpolation polynomials. They also introduce an analysis on the PAPR of the interpolated signals, where they derive an upper bound to it and show that its value is similar to that of the signal at the input of the interpolation filters, showing the feasibility of the proposed method. In addition, they present a detailed analysis where they show that a significant reduction in computational complexity is obtained when compared to frequency‐domain BF. Simulation results validate that the novel proposed scheme combining PAPR reduction and digital BF offers high‐precision beam‐steering maintaining reduced PAPR in the delayed signals fed to the antennas.

Peak to average power ratio (PAPR) reduction of OFDM signals has extensively been studied in the literature. Tone Reservation (TR) is one of the most famous algorithms and has already been included in some digital television standards such as DVB-T2 and ASTC3.0. However, the literature is still lacking theoretical analysis and performance bounds for the PAPR reduction of OFDM signals, especially using TR algorithms. For the first time, this paper provides fundamental results establishing the links between TR-PAPR reduction and the remaining signal distortions at the output of a non-linear high power amplifier (HPA) with and without memory effects. We first derive a generic EVM expression relying on the statistical characteristics of the samples composing the time domain signal and for any PAPR reduction technique. Computing these moments in the case of the quadratically constrained quadratic problem (QCQP) algorithm known as the optimal solution to the TR-PAPR reduction problem allows us to get the lower bound of the EVM of OFDM signals after TR-PAPR reduction and non-linear HPA. As a reference, we also provide the EVM expression using a clipping-based PAPR reduction method. The obtained EVM expressions have direct practical meaning since they are in function of the input power back-off (IBO) applied to the signal before the HPA. They also consist in a general analytical framework for OFDM PAPR reduction since they can be further exploited to analyze the performance of sub-optimal TR-based PAPR reduction algorithms.

In this paper we analyze the number of degrees of freedom needed to accurately capture and model wideband MIMO-OFDM channels. Two modeling approaches are considered, either examining each coefficient of the conventional input-output MIMO channel matrix or investigating the components constituting the physical ray-based propagation between the antenna arrays. As our analysis accounts for wideband channels, a time domain decomposition of MIMO channels into tapped delay lines is performed in each case. The efficiency of each approach is then evaluated in terms of number of taps to determine the most appropriate representation between either the conventional antenna-based one or the propagation-based one. This analysis is performed analytically using the Saleh-Valenzuela model which is recognized for its consistency for wideband as well as spatial modeling. We exploit the second-order statistics of the Channel Impulse Response to derive the taps weights.

In this paper, we investigate the impact of the covariance matrix (CM) size of the received signal on the performance of spectrum sensing methods. Our analysis is based on two well-known methods of spectrum sensing (SS), one based on the eigenvalues called maximum-to minimum eigenvalue (MME) and the other is based on the beamforming technique called maximum-to-minimum beam energy (MMBE). From an analytical development, we provide an explanation about the gap of detection performance between the two algorithms according to the size of the CM. Finally, we provide some simulations results to show the impacts of the smoothing factor and the number of antennas on the detection performance for both methods. These two parameters define the size of the CM of the received signal.

The shared superframe multihop nature of wireless personal area networks (WPAN s) encounters fundamental challenges to the design of effective and optimal resource allocation algorithms with respect to resource utilization and fairness across different network devices. In this paper, we propose a distributed optimization framework for resource allocation scheme for IEEE 802.15.5 hop-2 for fairly sharing the channel time resources granted by the reference Mesh Piconet Coordinator (MPNC) to the hop-1 MNPC among hop-2 devices. A NUM based optimization approach is proposed for optimal resource allocation with differentiation between real-time (RT) and non-real time (NRT) devices. Simulation results for studying satisfaction and fairness indexes are conducted.

Analog Beamsteering (ABS) has emerged as a low complexity and power efficient solution for Wave (mmWave) massive Multiple Input Multiple Output (Massive-MIMO) systems. Driven by the ability to exploit the low spatial correlation between the User Terminals (UTs) when a high number of transmit antennas is available at the Base Station (BS), ABS can be used to support Multi User (MU) MIMO scenarios instead of digital or Hybrid Beamforming (HBF) approaches. In this paper, we analytically characterize the Spectral Efficiency (SE) of MU-Massive-MIMO systems relying on ABS and theoretically define the asymptotic saturation level of the SE at high SNR. On the other hand, we provide a tight theoretical approximation for the SE of the system when implementing HBF with ABS at the analog stage and Zero Forcing precoding at the digital layer.

Receive Antenna Shift Keying (RASK) is a MIMO transmission scheme that is based on the Spatial Modulation (SM) concept applied at the receiver. In this scheme, the so-called spatial symbol is mapped to the index of one receive antenna that will be targeted during the symbol duration. In this paper, the performance of RASK is studied when the Maximum Ratio Transmission (MRT) precoding is used at the transmitter to focus toward the targeted antenna using coherent or non-coherent detection with different detection algorithms at the receiver. For coherent detection, the ML- based detector, and the Maximum Real Amplitude (MR) detector are studied, and we propose a specific detector called Maximum Real Minimum Imaginary (MRMI). For non-coherent detection, the ML-based detector and the Maximum Received Power (MP) are studied. The expressions of the Pairwise Error Probability for the coherent ML, MR and MP are derived and validated by simulations, and the performance of all detectors are compared by simulations. Finally, the computation complexity of the detectors is compared.

In this paper, we propose a new spectrum sensing (SS) algorithm called unified sensing algorithm (USA). This method exploits the results of different algorithms developed in the literature. The considered methods are especially those based on the covariance matrix of the received signal and those which further compute the eigenvalue decomposition of such matrix. More precisely, the USA algorithm implements some covariance matrix based methods, and in the case where the primary user is miss-detected, the eigenvalue decomposition is performed. This approach fully exploits all detection methods and avoids computational costs, as eigenvalue decomposition, when it is not necessary. Finally, the performance of the proposed method is provided and compared with existing state of the art algorithms. Simulation results show the performance improvement obtained with this new approach, namely the contribution in term of detection under very low signal-to-noise ratio (SNR).

Video streaming and mobile TV services have recently gained great research interest with the advances in mobile hardware technologies and the development of single frequency networks (SFN). However, the analysis of the coverage probability of these services in SFN has been and remains a complicated task due to the specific behavior of the received SFN signal and its effect on the useful signal. In this framework, we propose a new approach to model and evaluate the coverage probability for such network configuration. More particularly, using stochastic geometry, we propose a suitable approximation of the problem based on the closest SFN base stations. The resulted expressions represent a lower bound for the probability of coverage of the SFN. The proposed approximation leads to a good trade-off between accuracy and tractability. Numerical simulation results prove the validity of the proposed approach and related theoretical results, especially in a high path loss environment.

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.

In this paper, we study the statistical distribution of the OFDM time-domain signal amplitude to which the optimal tone reservation (TR) PAPR reduction solution is applied. This study comes as a major step towards the derivation of the analytical expression of the error vector magnitude (EVM) metric on OFDM waveforms when non-linear amplification is used. We demonstrate through simulations that this distribution has a bimodal behavior and can be tightly modeled as a superposition of two probability density functions whose expressions are given and whose parameters are obtained through proper estimation. From such analysis, we provide the complete distribution expression of the PAPR-reduced OFDM signal, which can be further exploited for the derivation of performance bounds of the TR PAPR reduction strategy.

Millimeter-Wave (mmWave) channels are characterized as being sparse and Line of Sight (LoS) dominated. Applying hybrid beamforming in mmWave systems guarantees Multi-User (MU) transmission with low hardware requirements. Zero Forcing (ZF) precoding can be utilized at the digital layer of the hybrid beamformer to mitigate the Inter User Interference (IUI). However, due to the sparse nature of the mmWave channels, a ZF precoder may provide limited performance due to the highly correlated MU channel matrix. The aim of this paper is hence to address the interference mitigation problem in the analog domain before handling it at the ZF digital level. Signal to Leakage and Noise Ration (SLNR) based users selection algorithm is introduced for maximizing the Spectral Efficiency (SE) of the system with low complexity requirements. We finally highlight by simulations the potential gains achieved by the introduced interference aware users selection approach.

Linear services such as mobile TV are witnessing an increasing demand, creating challenges for conventional delivery methods in both broadcast and broadband networks. To overcome this problem, a hybrid delivery approach combining both networks has recently emerged. Using stochastic geometry and a Poisson point process distribution of the users and access points, this paper discusses a hybrid broadcast/unicast network model where an analytical approach was undertaken, deriving a new expression for the probability of coverage. The model is then used to assess the feasibility of the proposed hybrid scheme and then extended to numerically find the optimal operation point in terms of key design parameters including user density in the network.

Spatial modulation (SM) schemes use the index of the transmit (resp. the receive) antenna to transmit additional data, and therefore allow for a new exploitation of the space dimension to increase the spectral efficiency of MIMO systems. The baseline of the proposed study relies on the so-called extended receive antenna shift keying (ERASK) concept consisting in transmitting the spatial bits by focusing the transmit energy towards subsets of receive antennas. With ERASK, the subsets of targeted antennas can be of any size leading to an amount of additional spatial bits directly equal to the number of receive antennas. However, an ON/OFF keying is used to carry the spatial symbols meaning that a zero power level is associated with non targeted antennas. Consequently, the transmission of additional IQ symbols in ERASK is not compatible with every spatial symbol configurations. In this paper, we propose a novel scheme referred to as Extended RSM (ERSM) that sends additional IQ modulated signals in ERASK, in order to increase the overall spectral efficiency. The key idea is to associate a non zero power levels for all spatial symbols. Two power levels are used to transmit the spatial and the IQ symbols, and an optimal ratio of the power is calculated. The theoretical performance of the proposed ERSM scheme is derived and then validated through simulations.

Millimeter-Wave (mmWave) systems offer extremely large Band-Width (BW) and highly Line-of-Sight (LOS) dominant channels. Many beamforming and power allocation techniques have recently emerged to leverage such channel characteristics in order to enhance the sum capacity and the coverage for multi-user transmissions. However, most of the existing algorithms are practically limited due to full channel knowledge and high complexity requirements. In this paper we introduce a novel, low complexity, angular based beamforming and power allocation framework, that requires the knowledge of the main contributive Directions of Arrival/Departure (DoAs/DoDs) of the propagation channel only. Exploiting the fact that propagation conditions are highly driven by the geometrical structure of the channel in mmWave scenarios, our method relies on the estimation of the leakage caused by each User Equipment (UE) on all the other UEs, approximated from the DoAs contributions. We prove with the simulation results that this approach, in addition to be practically plausible, can enhance the network Spectral Efficiency (SE) alongside with maintaining acceptable data rates for the cell edge UEs.

Spatial modulations (SM) use the index of the transmit (or the receive) antennas to allow for additional spectral efficiency in MIMO systems by transmitting spatial data on top of classical IQ modulations. Extended Receive Antenna Shift Keying (ERASK) exploits the SM concept at the receiver side and yields the highest overall spectral efficiency in terms of spatial bits compared to the conventional SM schemes. To perform efficiently, ERASK may use zero-forcing precoding to target spatial streams towards the selected receive antennas, therefore requiring the Channel State Information CSI at the transmitter. In this paper, we evaluate the theoretical performance degradation of the ERASK scheme under imperfect CSI. In addition, correlation between antennas at the transmitter and the receiver using the Kronecker correlation model is integrated in our analysis. Analytical approach for the Bit Error Rate performance is provided and validated through simulations.

This paper presents a novel Tone Reservation (TR) Peak to Average Power Ratio (PAPR) algorithm for the American digital video broadcasting (ATSC 3.0) standard. As any multicarrier communication systems, ATSC 3.0 transmitters suffer from high peaks of the transmitted signal. The high signal fluctuations constitute a major disadvantage of these systems. Indeed, they constraint the high power amplifiers to operate in their linear region which leads to poor spectral efficiency. To reduce the amplitude of the signal peaks, a TR gradient based algorithm has been proposed as an option within the ATSC 3.0 standard. Although TR-based algorithms have been intensively investigated these last years, very few today's transmitters implement these algorithms as they do not offer a high performance/complexity trade-off. This paper presents a novel TR-based algorithm, named as Grouped Carrier Peak Windowing (GCPW), which offers higher performance than the standard TR gradient-based algorithm while being implementable and compatible with the ATSC 3.0 standard. We also show through simulations that the proposed algorithm highly outperforms the gradient-based standard algorithm in terms of both in-band and out-of-band distortions. Results show that the novel algorithm offers very promising performance in terms of both modulation error rate and shoulder attenuation.

In a multiple-input-multiple-output (MIMO) communication system, the multipath fading tends to vanish with increasing number of radio links. This well-known channel hardening phenomenon plays a central role in the design of massive MIMO systems. It is quantified by the coefficient of variation of the channel gain. The aim of this paper is to study channel hardening using a physical channel model in which the influences of propagation rays and antenna array topologies are highlighted. Our analyses and closed form results extend the hardening properties beyond the classical Rayleigh fading models and offer further insights on the relationship with channel characteristics.

The new MIMO schemes commonly referred to as spatial modulations (SM) use the index of the transmit (resp. the receive) antenna to transmit additional data and hereby increase the spectral efficiency of digital communication systems. Most of proposed SM schemes allow for simultaneously transmitting two types of symbols, the classical IQ-symbols of a M-order modulation, and a spatial information related to the index of the transmit or targeted receive antenna(s). In this paper, we propose a complete uplink and downlink transmission system between a Base Station and a Connected Device for Internet-of-Things application based on SM. We thus concentrate on SM schemes only conveying spatial information for both downlink (from a base station to a connected device) and uplink (from a connected device to a base station) transmissions and leading to low complexity at the device. For the downlink we propose the use of an existing receive SM, the ERASK that is an extension of a very simple receive spatial modulation known as RASK (Receive Antenna Shift Keying) which aims at increasing the spectral efficiency. For the uplink, we firstly propose a new scheme which analogy with ERASK is highlighted. Both ERASK and ESSK can be efficiently used in the global system while keeping very low complexity at the device side. All complexity is reported at the base station with pre-processing function used to concentrate the signal energy towards the device targeted antenna(s). The channel estimation is also only needed at the base station for pre-processing of the ERASK and detection process of the ESSK.

The increasing popularity of linear services such as mobile TV, broadcasting live and sports events using mobile and portable devices, has led to a dramatic growth of the mobile data traffic. To deal with this traffic explosion, future networks have to increase the capacity offered to mobile communications, while at the same time trying to reduce their energy consumption. Actually, recent studies have shown that network cooperation is a promising candidate to deal with such issues. Based on these facts, this paper addresses the optimization of the energy efficiency of a hybrid network in which a broadcast and a unicast networks cooperate to deliver linear type of services to mobile and portable devices. Two optimization methods have been proposed to analytically find the optimal broadcast coverage area that maximizes the energy efficiency of the hybrid network. Simulation results show that using such a hybrid approach improves the overall energy efficiency.

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.

Wireless heterogeneous networks are usually characterized by the integration of different types of radio access technologies (RATs) to enhance system capacity and meet user requirements. In this context, we formulate a user association and downlink resource allocation optimization problem to maximize the overall user-centric profit in the system. The context-awareness is based on the user preferences, the data rate requested by each user equipment (UE), and the RAT characteristics and constraints. The user preference is based on a normalized weighted profit function that considers both the received signal quality and the power consumption at UEs. To approximate the formulated optimization problem, a greedy heuristic algorithm with polynomial-time complexity is proposed. It is shown through persuasive simulations that the proposed heuristic algorithm, when compared to the trivial profit-function-based solution, enhances the average user satisfaction in the system and lowers the percentage of blocked data rate. In fact, the performance of the proposed heuristic algorithm comes close to the optimal solution while requesting a lower number of handovers (HOs).

The aim of this paper is to analytically evaluate the spectral regrowth at the output of a transmitter due to the nonlinear components such as the power amplifier (PA). Therefore, we propose a generalization of existing closed-form expression for the Power Spectral Density (PSD) of nonlinear amplified multicarrier signals to be valid for any type of modulation. Then, we derive the PSD of the amplified multicarrier signal taking into account the predistortion technique. To the best of our knowledge, no analytical PSD expression of the transmitted signal taking into account the predistortion technique exists in the literature. Such analytical expression could be of particular interest to those involved in the design of cellular communications systems. In fact, this analytical expression is very useful to determine the optimal configuration of the PA and the predistortion technique that allows to obtain the maximum PA efficiency while satisfying the linearity requirements.

Hybrid broadcast broadband TV (HbbTV) is a technique providing Push-VOD services over an interactive hybrid TV. These services are broadcast using File Delivery Protocol (FDP) characterized by three levels of data represen- tation and give rise to three loss distribution that may result in QoS degradation and poor Forward Error Correction (FEC) recovery capabilities (if FEC is used within FDP). In this paper, we address for the first time the issue of depth analysis of loss propagation within FDP system to understand and foretell the perceptual VOD quality and the FEC behavior at receiver side. We first propose analytical models based on Markov chains to accurately predict the losses and the burstiness along the FDP system levels allowing to avoid the analysis by experimental NP-hard method. Then, based on simulation, we validate the proposed models for all tested average loss rates and average burst loss lengths. Finally, we show that the proposed Markov models allow to guess ahead effectively VOD QoS and FEC behavior.

This paper discusses the problem of user association and downlink resource allocation in heterogeneous wireless networks (HWNs) where a mobile node (MN) can associate to a single network at a time. A context-aware optimization problem is formulated to maximize the aggregate user-centric profit in the system while taking into consideration the network constraints, user preferences, and the amount of data rate requested by each MN. To achieve its purpose, the formulated problem employs contextual information related to the MN measurements and requirements, the HWN architecture, and the available resources at each network. The user-centric profit is based on the quality of the received signal and the power consumption at the MN. The formulated optimization problem is discrete (binary) with high complexity; based on the continuous relaxation of the problem, a solution with polynomial-time complexity is proposed. It is shown through simulations that the proposed solution achieves a near-optimal performance in terms of average user-centric profit and percentage of blocked data rate. Moreover, the proposed solution requests lower number of handovers.

The Internet of Things (IoT), describing the Machine Type Communications (MTC), is in the center of many new technical studies and industrial projects. It is also a central topic for the future 5G technologies standardization. Pending the new generation of cellular networks, the 3rd Generation Partnership Project (3GPP) has already standardized in May 2016, an evolution of the 2G and 4G networks to include IoT features. EC-GSM-IoT, the standard for the 2G technologies including the MTC, uses several technical evolutions to obtain a 20 dB improvement of the legacy Maximum Coupling Loss (MCL) of GPRS. One of them is the use of blind repetitions, and of combination techniques in the receiver. In a previous work [1], the Bit Error Rate (BER) performance of several time diversity combining mechanisms in a classical GSM receiver were studied in simulation. The present paper focuses on two of these combination techniques and leads a novel analytical study of their performances under a time variant multipath Rayleigh fading channel. The impact of the time correlation of the channels on the average Signal to Noise and Interference Ratio (SINR) is enlightened. Simulation results are compared to the theoretical curves and confirm the analytical work. This analytical investigation allows us to foresee the consequences on the final BER of the system. To the best of our knowledge, this is the first analytical study of the performance of such time diversity combining mechanisms under time variant multipath Rayleigh fading channels.

Integrating different types of wireless access technologies in heterogeneous networks provides flexible choices for users to handover to a more preferable network that satisfies their needs. In this paper, we discuss the recent 802.21.1 Software Defined Radio Access Network (SDRAN) architecture that couples the Software Defined Networking (SDN) mechanisms by the IEEE 802.21 Media Independent Handover Services. Based on this architecture, we propose a centralized handover algorithm that manages user association and downlink capacity resource allocation. The algorithm is formulated as a Generalized Assignment Problem (GAP) which maximizes the overall profit of mobile nodes which is studied in terms of power consumption and Received Signal Strength (RSS). Comprehensive simulation has been conducted; It is shown that the formulated algorithm reduces the overall consumed power and increases the average relative received signal strength while demanding an extra number of HOs.

Orthogonal Frequency Division Multiplexing (OFDM) systems are extremely sensitive to nonlinear distortions brought by the Power Amplifier (PA) because of the inherent high peak-to-average power ratio (PAPR) of the signal. In this paper, we analyze the impact of the non-linearities on the output signal, assuming that the transmitter is equipped with a linearization stage before the PA. Therefore, the expression of the Error Vector Magnitude (EVM) of the output signal is analytically derived with or without the use of the linearization process. We provide analytical expressions of the EVM in the form of a series expansion that depends on the transition factors of the PA and predistortion characteristics. Simulations results confirm the accuracy of our analytical expressions, even when limiting the series expansion to an order of 4.

Multiple algorithms have been proposed to deal with the high Peak to Average Power Ratio (PAPR) of Orthogonal Frequency Division Multiplexing (OFDM) signals. The second generation of Digital Video Broadcasting for Terrestrial transmission (DVB-T2) has adopted the Tone Reservation (TR) technique. It is based on an iterative process where, at each iteration, a predefined kernel is used to reduce one peak in time domain. In this paper, we first assess the performance of the power control schemes adopted by TR algorithms. Then, we analyze their complexity and show that their kernels are complex to generate, hence practically, difficult to implement. Secondly, we propose a novel kernel signal, simple to implement yet compatible with the DVB-T2 standard to reduce the PAPR value. The proposed kernel is defined to deal with the reduction of multiple peaks at a time. We show that the proposed PAPR reduction outperforms the TR algorithm adopted in DVB-T2 in terms of CCDF and Modulation Error Rate (MER) and then offers a better performance-complexity tradeoff.

Orthogonal Frequency Division Multiplexing (OFDM) systems are characterized by a high Peak to Average Power Ratio (PAPR), which results in performance degradation due to High Power Amplifiers' nonlinearities. Multiple algorithms have been proposed to deal with this problem, among them the Tone Reservation (TR) technique adopted in the second generation of Digital Video Broadcasting for Terrestrial transmission (DVB-T2). In this paper we analyze the power control schemes used in TR algorithms by assessing both their performance and complexity. We then propose two novel solutions to improve the performance without requiring additional complexity. The first is based on an enhanced selection of the peaks to be processed by the TR algorithm, and the second is based on a dynamic computation of the threshold used. We show that the proposed techniques outperform the TR algorithm adopted in DVB-T2 by 0.77 dB in terms of CCDF gain at 10-3and by 0.33 dB in terms of Input Back Off (IBO) gain for an MER of -40dB.

In this paper, we focus on the behavior of the Belief Propagation (BP) algorithm when decoding the Low-Density Parity-Check (LDPC) code of rate 3/4 in the DVB-S2 standard. By studying the topological structure of its Tanner graph, we raise properties inherent to the degree distribution that turns out to be strongly correlated with the decoding failures. The irregularity of the degrees seriously damages the performance, visible by an abrupt error floor. We accordingly propose a novel model of the error events based on the degree distribution which helps simulate typical error events and observing the flaws of the DVB-S2 code. This work could be used as a good basis to design future codes with a better decoding behavior, especially in the error floor region.

The DVB-S2 standard has been revealed a reliable standard for data transmission thanks to the LDPC codes. The waterfall of the bit-error rate is very abrupt to reach low values of order 10^(-10) in the error floor. In this paper, we propose a novel investigation on the iterative decoding of these codes by the Belief Propagation algorithm on Gaussian channels. Introducing definitions of persistent and created errors, we analyze them according to the degrees of the Tanner graph nodes and the noise power of the channel. We show that the two-degree bits used to accelerate the encoding process of the DVB-S2 are responsible for most decoding errors. This result could help design DVB-S2 codes in a more appropriate way, for instance avoiding the use of BCH codes to tackle the error floor.

In this paper we study the Time Reversal (TR) technique in a large MISO-OFDM system. This technique has been proven to provide good beamforming gains at a price of a channel estimation availability at the transmitter side. Moreover, the greater the number of transmit antennas, the better the spatial and temporal focusing gains, which makes TR a good candidate for large MISO systems while keeping a low complexity. The capacity of the system and the bit error rate (BER) performances are first derived and simulated and compared with systems applying the maximum ratio transmission technique. The time focusing gain of the TR technique is then exploited to show that the equivalent channel is shortened when the number of antennas increases, allowing a reduction of the guard interval and an increase of the spectral efficiency of the system. Finally, the robustness of the system to channel estimation errors is evaluated by adding simple channel estimation techniques in the system and evaluating the BER performance.

In this work, a new fast-decodable space-time block code (STBC) is proposed. The code is full-rate and full-diversity for 4 × 2 multiple-input multiple-output (MIMO) transmission. Due to the unique structure of the codeword, the proposed code requires a much lower computational complexity to provide maximum-likelihood (ML) decoding performance. It is shown that the ML decoding complexity is only O(M4,5) when M-ary square QAM constellation is used. Finally, the proposed code has highest minimum determinant among the fast-decodable STBCs known in the literature. Simulation results prove that the proposed code provides the best bit error rate (BER) performance among the state-of-the-art STBCs.

Traditionally, cellular radio communication systems define a spectrum mask to avoid inter-channel interference between services operated in adjacent frequency bands. In this paper, we intend to optimize the spectrum efficiency of wireless systems by frequency band reused, which is performed by partial channel overlapping of adjacent bands. The impact of interchannel interference is studied for both single and multicarrier modulations. Then time reversal (TR) with multiple-input-single-output (MISO) is applied to depress the inter-channel interference thanks to the TR focusing properties. The spectral efficiency of the system is evaluated according to the overlap ratio τ and the number of transmitting antennas. The optimal τmaxis identified and, as a result, channel overlapping is proved to be interesting at low SNR regime in a range depending on the number of antennas.

The 3D MIMO code is a robust and efficient spacetime coding scheme for the distributed MIMO broadcasting. However, it suffers from the high computational complexity if the optimal maximum-likelihood (ML) decoding is used. In this paper we first investigate the unique properties of the 3D MIMO code and consequently propose a simplified decoding algorithm without sacrificing the ML optimality. Analysis shows that the decoding complexity is reduced from O(M8) to O(M4.5) in quasi-static channels when M-ary square QAM constellation is used. Moreover, we propose an efficient implementation of the simplified ML decoder which achieves a much lower decoding time delay compared to the classical sphere decoder with Schnorr-Euchner enumeration.

This paper investigates the distributed space-time (ST) coding proposals for the future Digital Video Broadcasting-Next Generation Handheld (DVB-NGH) standard. We first theoretically show that the distributed MIMO scheme is the best broadcasting scenario in terms of channel capacity. Consequently we evaluate the performance of several ST coding proposals for DVB-NGH with practical system specifications and channel conditions. Simulation results demonstrate that the 3D code is the best ST coding solution for broadcasting in the distributed MIMO scenario.

Mobile network operators are confronted to an exponential growth of their traffic. One of the causes of this growth is the delivery of video services, including mobile television. Using a broadcast component like MBMS or DVB-H for the provision of the most popular mobile television channels can minimize their impact on the mobile network traffic. Such a component can also be investigated for other types of popular services and open the door to hybrid broadcast/unicast networks. The key factor for the efficiency of this approach is the choice of the services to be transmitted through the broadcast component. In this article, we introduce an energy criterion to make this choice. We use a simplified model of an hybrid network combining a DVB-T2 broadcast component to a LTE unicast component. Through the statistical study of the reception conditions of the users in this network, we evaluate the power gain brought by the use of the broadcast component for the delivery of a service as a function of the number of users that are using this service.

In this paper, we investigate spectrum sharing and multiple access problems for the high-rate ultra-wideband (UWB) systems. Based on the use of the linear precoded orthogonal frequency division multiplexing (LP-OFDM) proposed as an evolution of the well known multi-band OFDM (MB-OFDM) solution supported by the WiMedia Alliance for future high-rate UWB systems, the objective of this paper is to study a multiuser optimization spectrum sharing scheme for LP-OFDM UWB systems. This optimization study leads to a novel multiple access solution for the high-rate UWB systems. Simulation results demonstrate the efficiency of the use of the LP-OFDM transmission technique in the multiuser spectrum sharing scheme. Besides, the novel LP-OFDM multiuser spectrum sharing solution shows its capacity to provide a good tradeoff between the QoS support of the high-priority users and the fairness between the competing users.

In contrast to the classical cyclic prefix (CP)-OFDM, the time domain synchronous (TDS)-OFDM employs a known pseudo noise (PN) sequence as guard interval (GI). Conventional channel estimation methods for TDS-OFDM are only based on the PN sequence and consequently suffer from intersymbol interference. This paper proposes a novel two-stage channel estimation method which combines the estimation results from the PN sequence and, most importantly, the estimation results obtained from the OFDM data symbols. A simple feedback loop that excludes the channel decoder is employed for the OFDM data based estimation. The MMSE criteria is used to obtain the best combination results and an iterative process is proposed to progressively refine the estimation. Both MSE and BER simulations are carried out to prove the effectiveness of the proposed algorithm in the DTMB system which is based on TDS-OFDM signalling.

In this paper, we investigate the spectrum scheduling problem for next generation multiband orthogonal frequency division multiplexing (MB-OFDM) ultra-wideband (UWB) systems under QoS and interference constraints. Based on a constrained optimization problem formulation, we propose a cross-layer scheduling solution that takes into account the unlicensed UWB users channel and QoS conditions as well as the interference impact on primary users sharing the same bandwidth. The cross-layer scheduling scheme is based on a priority approach that gives advantage to users having strict QoS requirements while avoiding or reducing the interference effect on primary users. Simulation results demonstrate the efficiency of the proposed scheme in terms of QoS support and interference reduction.

This paper considers the problem of impulse response shortening for discrete multitone (DMT) transceivers. The proposed channel shortening filter shortens the effective channel impulse response (CIR) while concentrating energy in a predetermined window. This approach is based on convolution operation and filter coefficients decomposition which over constraint the effective CIR and allows achieving better performance. Simulation results show that the proposed algorithm outperforms the classical channel shortening approaches in terms of achievable bit rate and computational complexity.

In this paper, we propose a multiuser spectrum allocation scheme for high-rate UWB systems under QoS requirements. This scheme comes as a solution to the coexistence of multiple users sharing the three sub-bands of the same channel as defined in the WiMedia solution adopted for multiband UWB systems. Indeed, WiMedia solution does not allow more than three users to coexist in the same channel. Based on a constrained multiuser optimization problem, the proposed allocation algorithm allows multiple users to access the medium following a mixed sub-band assignment and priority-based scheduling approach in order to ensure an efficient differentiated spectrum sharing. The resulting time-frequency scheduling algorithm relies on the combination of two main metrics available at PHY and MAC levels: the channel quality of each user provided by the exploitation of the effective SINR method, and the QoS constraint represented by a simple weighting parameter that differentiates between two service classes. Simulation results show the efficiency of the proposed scheme and how it guarantees a good performance level for users having strict QoS requirements.

In this paper, we investigate the use of a cross-layer allocation mechanism for the high-rate ultra-wideband (UWB) systems. The aim of this paper is twofold. First, through the cross-layer approach that provides a new service differentiation approach to the fully distributed UWB systems, we support traffic with quality of service (QoS) guarantee in a multi-user context. Second, we exploit the effective SINR method that represents the characteristics of multiple sub-carrier SINRs in the multi-band WiMedia solution proposed for UWB systems, in order to provide the channel state information needed for the multi-user sub-band allocation. This new approach improves the system performance and optimizes the spectrum utilization with a low cost data exchange between the different users while guaranteeing the required QoS. In addition, this new approach solves the problem of the cohabitation of more than three users in the same WiMedia channel.

In this paper, we propose a novel and simple MIMO channel estimation technique based on 2D spread pilots. Taking advantage of the simplicity and flexibility of 2D spread pilot channel estimation, we easily combine the Alamouti code with the Walsh-Hadamard codes to obtain a space code block code (SCBC) MIMO scheme. We demonstrate that our proposed system is much more efficient in high mobility scenario than the classical STBC scheme. The performance evaluated over a realistic channel model shows the efficiency of this technique which turns out to be a promising MIMO channel estimation technique for the future mobile video broadcasting systems.

This article investigates the effect of equal and unequal received powers on the performances of different MIMO-OFDM schemes for terrestrial digital TV. More precisely, we focus on three types of non-orthogonal schemes: the BLAST scheme, the linear dispersion (LD) code and the Golden code, and we compare their performances to that of Alamouti scheme. Using two receiving antennas, we show that for moderate attenuation on the second antenna and high spectral efficiency, Golden code outperforms other schemes. However, Alamouti scheme presents the best performance for low spectral efficiency and equal received powers or when one antenna is dramatically damaged. When three antennas are used, we show that Golden code offers the highest robustness to power unbalance at the receiving side.

In this paper, we investigate a new waveform for UWB systems obtained by the combination of orthogonal frequency division multiplex (OFDM) and coded division multiple access (CDMA). The proposed system, called spread spectrum multi-carrier - multiple access (SS-MC-MA) turns out to be a judicious solution to combat frequency selectivity and narrowband interferers, and to manage the coexistence of several users and piconets. It is shown that the addition of a degree of freedom brought by the spreading component of SS-MC-MA allows to optimize jointly the assignment of the number of used codes and coding rates in order to make the system more robust. Through simulations, it is demonstrated that the new system can outperform multi-band OFDM alliance (MBOA) for low data rates and is able to provide wider range of rates.

In this paper, we propose to apply adaptive loading principles to linear precoded digital multitone (LP-DMT). This new approach can especially be exploited in the powerline context, since it requires the knowledge of the channel at the transmitter. We first show that maximal waveform capacity is achieved when orthogonal matrices are used to linearly precode the multitone signal. A practical loading algorithm based on tone clustering is then developed to handle the configuration of the system. This algorithm assigns tones, size of preceding matrices, bits and energies in order to maximize the total throughput of the system. The optimization procedure is led under power spectral density (PSD) limitations and finite order modulations constraint. Through simulations over power line channels, it is shown that the new adaptive LP-DMT system takes advantage of the carrier merging effect offered by the precoding function and then outperforms the non-precoded DMT system.

In this paper, we investigate the dynamic resource allocation adapted to spread-spectrum multicarrier multiple-access (SS-MC-MA) systems in a multiuser power line communication (PLC) context. The developed adaptive system is valid for uplink, downlink, as well as for indoor and outdoor communications. The studied SS-MC-MA system is based on classical multicarrier modulation like digital multitone (DMT), combined with a spread-spectrum (SS) component used to multiplex several information symbols of a given user over the same subcarriers. The multiple-access task is carried out using a frequency-division multiple-access (FDMA) approach so that each user is assigned one or more subcarrier sets. The number of subcarriers in each set is given by the spreading code length as in classical SS-MC-MA systems usually studied in the wireless context. We derive herein a new loading algorithm that dynamically handles the system configuration in order to maximize the data throughput. The algorithm consists in an adaptive subcarrier, code, bit, and energy assignment algorithm. Power-spectral density constraint due to spectral mask specifications is considered, as well as finite-order modulations. In that case, it is shown that SS-MC-MA combined with the proposed loading algorithm achieves higher throughput than DMT in a multiuser PLC context. Because of the finite granularity of the modulations, some residual energy is indeed wasted on each subcarrier of the DMT spectrum. The combining of a spreading component with DMT allows to merge these amounts of energy so that one or more additional bits can be transmitted in each subcarrier subset leading to significant throughput gain. Simulations have been run over measured PLC channel responses and highlight that the proposed system is all the more interesting than the signal-to-noise ratio is low.