This paper studies the coexistence between a geosynchronous Equatorial orbit (GEO) satellite at nadir and a low Earth orbit (LEO) satellite. Both satellites operate in the Q/V frequency band, identified as potential candidate for the service link of 6G non-terrestrial communications. The two satellites on different orbits use either the same communication channel or adjacent channels. As a consequence, communications between the satellites and their associated user equipment on Earth are subject to interference in both downlink (DL) and uplink (UL), thus reducing the throughput. The level of experienced interference depends on the LEO satellite elevation, and on the adjacent channel interference ratio (ACIR) in case of adjacent channel interference. The coexistence results obtained for both DL and UL of the two considered orbits provide guidelines regarding the maximum elevation for the LEO satellite at which the 3GPP requirements are fulfilled. For instance, the required value of ACIR with respect to the maximum acceptable throughput loss is hereby evaluated.

This paper presents a packet scheduler for managing multiple links with varying channel capacities, where each link carries multiple data flows with finite buffers and strict delay constraints. Packet loss can result from buffer overflow or delay violations. We propose a deep reinforcement learning scheduler based on an encoder only transformer architecture, capable of handling a variable number of links without dedicated training. Using deep Q-learning, the scheduler minimizes the packet loss rate. Simulations show that our approach outper-forms a state-of-the-art fully connected scheduler, delivering better performance under diverse configurations of links, packet arrival rates, and channel capacities.

In this paper, we tackle the problem of the signal-to-interference-plus-noise ratio (SINR) distribution estimation under flat Rayleigh fading with a single interferer. Assuming that we collect a set of SINRs’ values from the receiver, the distribution is parametrized by the direct and interfering channel magnitude that need to be estimated. To that purpose, we propose here two new estimators: the maximum likelihood estimator (MLE) and a method of moments (MoM) estimator. For both estimators we derive the equations and propose a numerical implementation scheme based on Newton’s algorithm. The MoM estimator is less complex but also less accurate, whereas the MLE is more accurate but requires careful initialization. Thus, we propose to use the MoM’s estimates to initialize the MLE algorithm. In addition, we derive the Cramer-Rao lower bound (CRLB) associated to this estimation problem and propose an efficient computation of it. We provide simulations to assess the performance of our proposed estimators and verify that the mean square error of the MLE is close to the CRLB.

This paper considers the problem of fully distributed channel allocation in clustered wireless networks when the propagation medium is random. We extend here the existing Trial and Error (TE) framework developed in the deterministic case and for which strong convergence properties hold. We prove that using directly this solution in the random context leads to unsatisfactory solutions. Then we propose an adaptation of the original Trial and Error Learning (TEL) algorithm, called Robust TEL (RTEL), assuming that the random channel effects translate into a bounded stochastic disturbance of the utility function. The solution consists in introducing thresholds in the transitions of the TEL’s Finite State Controller (FSC). We prove that this new solution restores the good convergence property inherited from the TEL. Furthermore, we provide analysis of the stochastic utilities in the Rayleigh fading case in order to check the bounded assumption. Finally, we develop an online algorithm that dynamically estimates the optimal threshold values to adapt to the instantaneous disturbance. Numerical results corroborate our theoretical claims.

In this paper, we propose a method to predict the average packet error rate (PER) of a coded single carrier frequency domain equalization (SC-FDE) transmission scheme after minimum mean square error (MMSE) equalization when statistical channel state information (SCSI) is available. We assume that the encoded bits are spread over several blocks (which may correspond to a frequency hopping system for instance) which are transmitted under independent multipath random fading channel realizations. The PER prediction technique used here is based on the effective SNR mapping approach that gathers the signal to noise ratios (SNR)s of the different blocks into one single value. The novelty of this contribution resides in the fact that we propose a new expression for the effective SNR that allows us to approximate its statistical distribution with a beta random variable whose parameters depend on the SCSI. This approach enables us to compute the PER prediction with a lower complexity that the one required by conventional approaches. Moreover, we show by simulations that the accuracy of our solution is very close to the conventional ones, typically within 1 dB of error for PER of the order of 10-2.

Model-free decentralized optimizations and learning are receiving increasing attention from theoretical and practical perspectives. In particular, two fully decentralized learning algorithms, namely Trial and Error Learning (TEL) and Optimal Dynamical Learning (ODL), are very appealing for a broad class of games. Indeed, ODL has the property to spend a high proportion of time in an optimum state that maximizes the sum of the utilities of all players, whereas, TEL has the property to spend a high proportion of time in an optimum state that maximizes the sum of the utilities of all players if there is a pure Nash equilibrium, otherwise, it spends a high proportion of time in a state that maximizes a trade-off between the sum of the utilities of the players and a predefined stability function. On the other hand, estimating the mean fraction of time spent in the optimum state (as well as the mean time duration to reach it) is challenging due to the high complexity and dimension of the inherent Markov chains. In this article, under some specific system model, an evaluation of the above performance metrics is provided by proposing an approximation of the considered Markov chains, which allows overcoming the problem of high dimensionality. A comparison between the two algorithms is then performed which allows a better understanding of their performance.

This paper addresses the per-link power and bandwidth allocation problem with the objective of maximizing energy efficiency (EE) related metrics under a per-link minimum goodput constraint when only statistical channel state information is available. We consider a parallel (i.e., without multiuser interference) Rician channel model, which encompasses both Rayleigh and additive white Gaussian noise channels as special cases. We also consider Type-I hybrid automatic repeat request with practical modulation and coding schemes. The addressed problems are the maximization of the sum of the user's EE, the maximization of the EE of the user with the lowest EE, and the maximization of the EE of the network. We derive the optimal solutions of these problems in closed form using fractional programming and a convex optimization framework. We show that substantial gains can be achieved by taking into account the line of sight between the transmitter and the receiver instead of only considering the average channel power.

We address the problem of energy efficient power and bandwidth allocation for hybrid automatic repeat request (HARQ) in multiuser ad hoc networks with statistical channel state information (CSI) and practical modulation and coding schemes (MCS) under quality of service (QoS) constraints. Using an upper-bound of the packet error rate, we propose an algorithm to maximize the sum of the energy efficiency (SEE) of the different users. We also propose two suboptimal less-complex algorithms, one based on alternating optimization and the other on a high signal-to-noise ratio (SNR) approximation. It is shown that the proposed algorithms allow a substantial gain in term of SEE compared with conventional algorithms.

This paper considers an orthogonal frequency division multiplexing system where the Effective Exponential SNR Mapping (EESM) is applied. We first present an approximate model in which the subcarriers grouped into one block are assumed to have the same channel coefficient and, subcarriers in different blocks have independent and identically distributed channel coefficients. Then, we present an algorithm based on a goodness of fit test to estimate the number of subcarriers to be grouped into one block. Building on this approximation model, we provide an approach to compute the statistics of the effective SNR obtained from the EESM mapping. This method is based on convolution technique. The approach presented in the paper is then validated through simulations.

In the context of wireless mobile ad hoc networks, node clustering is a well-known solution for handling the scalability issue. While existing work focused on unstructured (i.e., flat) networks, this paper investigates a clustering algorithm to handle stable size-restricted clusters for structured (i.e., group-based) networks. In addition, we have identified that the ad hoc network clustering literature lacks a theoretical framework. This paper fills this gap by proposing to use coalition game theory, identifying coalitions to clusters and players to nodes. This theoretical framework allows us to derive a novel generic distributed node clustering algorithm. The algorithm is proved to converge to Nash-stable partitions. It is based on the concept of switch operations, where nodes take decision whether to leave or not their current coalition based on the coalition values. These decisions are made independently on any node individual payoff, meaning that the coalition formation game has a transferable utility. This generic algorithm is then tailored to both structured and unstructured networks, by defining judiciously the value functions and the heuristics dedicated to selecting suitable switch operations. Based on extensive simulations, we show that our proposed solutions outperform the existing ones especially in terms of cluster size and stability.

We address multiuser power and bandwidth allocation for Orthogonal Frequency Division Multiple Access (OFDMA) networks employing a Type-II Hybrid Automatic Repeat reQuest (HARQ) mechanism, practical Coding and Modulation Schemes (MCSs) and Bit Interleaved Coded Modulation (BICM). The problem is formulated as minimizing the sum power required to satisfy a goodput constraint for each link while its transmit power does not exceed a certain level. Assuming statistical Channel State Information (CSI), we propose an algorithm to compute the corresponding optimal resource allocation and a practical selection of the MCSs that significantly boosts the proposed algorithm.

Many wireless public safety and military networks are ad hoc networks, for which clustering is a well-known strategy to improve scalability. In addition these networks are structured according to a hierarchical organization, i.e. nodes belong to specific operational groups which implies that the traffic is mainly intra-group. So far, clustering algorithms are built using metrics such as node identifiers, node mobility, etc., and thus do not take into account the network hierarchical structure. The goal of this paper is therefore twofold: i) specify a way to benchmark clustering solutions from a system point of view, and ii) thanks to this benchmark determine the importance of using operational group information to build clusters. Therefore we define a novel network cost function based on additive metrics (e.g. delay) incorporating the traffic structure and the inter-clusters communications costs. Thanks to this function we show that the clustering solutions providing the best QoS to the end user depend on the group structure.

We address the problem of multiuser power and bandwidth allocation for Orthogonal Frequency Division Multiple Access (OFDMA) networks employing a Type-II Hybrid Automatic Repeat reQuest (HARQ) mechanism, practical Coding and Modulation Schemes (MCSs) and Bit Interleaved Coded Modulation (BICM). The problem is formulated as minimizing the sum power required to satisfy a goodput constraint for each link while its post-HARQ Packet Error Rate (PER) does not exceed a certain threshold. Assuming statistical Channel State Information (CSI), we propose a computationally-efficient algorithm to compute the corresponding optimal resource allocation. We finally provide a practical selection of the MCSs that significantly boosts the performance of the proposed resource allocation algorithm.

We address the problem of multiuser power and bandwidth allocation for a general class of OFDMA-based wireless networks that employ a Type-II hybrid automatic repeat request (HARQ) mechanism along with practical modulation and coding schemes (MCSs). This problem is formulated as minimizing the sum transmit power required to satisfy individual goodput constraints without exceeding maximum allowable per-link or per-node transmit power levels. We assume that the resource manager has only statistical knowledge of the channel state information (CSI) of the Rayleigh-distributed fast-fading links of the network. Using a tight approximation of the goodput, we propose an algorithm allowing computation of the corresponding optimal resource allocation. We finally provide an efficient selection of the different MCSs that can be coupled with the proposed resource allocation algorithm to significantly boost its performance.

In this paper, the problem of channel selection and power control is jointly analyzed in the context of multiple-channel clustered ad-hoc networks, i.e., decentralized networks in which radio devices are arranged into groups (clusters) and each cluster is managed by a central controller (CC). This problem is modeled by game in normal form in which the corresponding utility functions are designed for making some of the Nash equilibria (NE) to coincide with the solutions to a global network optimization problem. In order to ensure that the network operates in the equilibria that are globally optimal, a learning algorithm based on the paradigm of trial and error learning is proposed. These results are presented in the most general form and therefore, they can also be seen as a framework for designing both games and learning algorithms with which decentralized networks can operate at global optimal points using only their available local knowledge. The pertinence of the game design and the learning algorithm are highlighted using specific scenarios in decentralized clustered ad hoc networks. Numerical results confirm the relevance of using appropriate utility functions and trial and error learning for enhancing the performance of decentralized networks.

In this paper, a decentralized iterative algorithm, namely the optimal dynamic learning (ODL) algorithm, is analysed. The ability of this algorithm of achieving a Pareto optimal working point exploiting only a minimal amount of information is shown. The algorithm performance is analysed in a clustered ad hoc network, where radio devices are assumed to operate above a minimal signal to interference plus noise ratio (SINR) threshold while minimizing the global power consumption. Sufficient analytical conditions for ODL to converge to the desired working point are provided, moreover through numerical simulations the ability of the algorithm to configure an interference limited network is shown. The performances of ODL and of a Nash equilibrium reaching algorithm are numerically compared, and their performance as a function of available resources is studied. The gain of ODL is shown to be larger when the amount of available radio resources is scarce.

We investigate several types of Stop and Wait HARQ schemes under imperfect feedback conditions. Performance are measured through the usual metrics, i.e., packet error rate, delay, and efficiency. The main novelties of this paper are twofold: i) the considered feedback undergoes the random arrival time of the acknowledgment. ii) the analysis is done at the network level (IP) which enlarges the vision of practical systems performance. In particular, our analysis enables us to consider a recent cross-layer MAC-IP allocation strategy. Finally our results provide a way to design the feedback link.

In this paper, we address the problem of global transmit power minimization in a self-configuring network where radio devices are subject to operate at a minimum signal to interference plus noise ratio (SINR) level. We model the network as a parallel Gaussian interference channel and we introduce a fully decentralized algorithm (based on trial and error) able to statistically achieve a configuration where the performance demands are met. Contrary to existing solutions, our algorithm requires only local information and can learn stable and efficient working points by using only one bit feedback. We model the network under two different game theoretical frameworks: normal form and satisfaction form. We show that the converging points correspond to equilibrium points, namely Nash and satisfaction equilibrium. Similarly, we provide sufficient conditions for the algorithm to converge in both formulations. Moreover, we provide analytical results to estimate the algorithm's performance, as a function of the network parameters. Finally, numerical results are provided to validate our theoretical conclusions.

In this paper we derive performance metrics closed-form expressions of retransmission schemes such as Automatic Repeat reQuest (ARQ) and Hybrid ARQ (HARQ) in the case of memoryless block fading channels. As performance metrics, we consider the Packet Error Rate (PER), the efficiency, and the packet delay. The novelty of the paper is twofold: i) the metrics are considered at the Network level; ii) we introduce a new general framework which enables us to derive analytically the considered performance metrics for most retransmission schemes, including recent cross-layer strategies with the Network layer. The metrics at the Medium Access Control (MAC) level are obtained as a byproduct. Among the considered retransmission schemes, we especially consider the Incremental Redundancy HARQ scheme with different lengths redundancy packets.

In order to improve the reliability of any HARQ technique at the IP level, a cross-layer strategy between the MAC and the IP levels has been recently developed in. This strategy consists in replacing a retransmisssion credit per MAC packet with a retransmission credit per IP packet. In other words, the transmission credit is shared by the MAC packets belonging to the same IP packet. Packet Error Rate, throughput, delay and jitter for this new approach have been extensively analyzed in. In this paper, we remark and theoretically prove that the first MAC packets are better protected than the last ones. This leads to a natural "unequal packet loss protection" that can be useful in many applications, such as video streaming, compressed image transmission, audio and protocols (TCP/IP). Exploiting this novel manner of protecting packets unequally may not exclude the use of the standard manners, such as different feedforward error correcting codes (FEC), modulation size, or hybrid ARQ scheme per required quality of protection. Finally, our claims are supported by numerical simulations.

We aim to study a specific cross-layer optimized Hybrid Automatic Retransmission reQuest (HARQ) introduced in [1] and called early-drop HARQ. We remind that in [1], instead of giving a transmission credit per MAC packet (as usually done), it is proposed to share the transmission credit among all the MAC packets belonging to the same IP packet. The early-drop version stops the retransmission as soon as the number of remaining MAC packets is higher than the number of possible transmission attempts. As the early-drop has never been analyzed neither through simulations nor analytical derivations, the purpose of this paper is to fill this gap. As the packet error rate and the delay are not modified, we only focus on the efficiency which is expressed in closed-form.

New ARQ or HARQ schemes taking into account the link between the MAC and IP layers have been recently introduced. In this paper, we analyze these new schemes in terms of delay and jitter by deriving these metrics in closed-form expressions at the IP level. As the framework developed for obtaining such terms in closed-form is generic, we show that the proposed expressions hold for any standard ARQ or HARQ scheme (ARQ, Incremental Redundancy HARQ, Chase Combining HARQ without cross-layer optimization) at any level (MAC or IP).

In Impulse Radio Ultra Wide Band (IR-UWB) based systems, we show that the Multi-User Interference (MUI) assuming fixed spreading codes can be well approximated by a Generalized-Gaussian Distribution (GGD). Then, we derive an accurate closed-form expression of the approximation for the Average Error Probability (AEP) in both Direct-Sequence (DS) and time-hopping (TH) multiple access context. From this approximation, we are able to characterize and to select the set of codes minimizing the AEP for both multiple access techniques. The merit of each multiple access technique is then analyzed: we especially prove that the probability to find an optimal pair of codes goes to one when increasing the number of chips per symbol with TH technique whereas this probability goes to zero with DS technique. Numerical illustrations confirm our claims.

An approximation for the Average Error Probability (AEP) of the Pulse Amplitude Modulation (PAM) Impulse Radio Ultra Wide Band (IR-UWB) systems in the presence of Multi-User Interference (MUI) is derived assuming that the spreading codes are fixed in time. The comparison of the proposed theoretical expression and the empirical result shows the accuracy of our approximation for both Direct-Sequence (DS) and Time-Hopping (TH) multiple access techniques. From this approximation, we deduce criterion that enable us to select the set of codes optimizing the performance in terms of the AEP.

This paper presents the project ldquourban planning for radio communicationsrdquo which is part of ldquoSystem@ticrdquo Paris-Region Cluster, one of the French Lt pole of competitiveness Gt initiative. We present first an overview of the project which deals with spectrum scarcity issues in crowded cities. We browse the different technical aspects addressed in the project and the corresponding challenges. We then present, as an example, the recent results of two particular topics studied in the project: one related to the system architecture dealing with the radio enabler concept and the other one related to radio access about hybrid ARQ.

In the context of PAM time-hopping/direct sequence impulse radio ultra wide band (IR-UWB), a residual interference occurs at the output of the Rake receiver when realistic multipath propagation channel is considered even if a large guard-time interval is used. As a consequence, the performance is limited and exhibits BER floor. In this paper, we explicitly explains what causes such a residual interference. Secondly, we propose a simple way to modify the Rake receiver in order to totally remove this residual interference. The results are illustrated by simulations that validate the proposed method.

In this work we tackle the problem of mitigating the multi-user interference by optimizing the time-hopping codes, in an asynchronous impulse radio multiple access scheme. We derive the expression of the multi-user interference variance at the output of a Rake receiver assuming that the codes are deterministic, for both pulse position modulation and pulse amplitude modulation formats, when propagating through multipath channels. The result shows that the code contribution is independent of the other parameters. We derive from this expression a practical criterion that enables us to find a set of optimal codes that ensures minimal multi-user interference variance at the receiver output. We check through simulations, that the set of optimal codes found using the criterion, leads to bit error rate improvement

Impulse radio is an ultrawideband system with attractive features for baseband asynchronous multiple-access, multimedia services, and tactical wireless communications. Implemented with analog components, the continuous-time impulse radio multiple-access model utilizes pulse-position modulation and random time-hopping codes to alleviate multipath effects and suppress multiuser interference. We introduce a novel continuous-time impulse radio transmitter model and deduce from it an approximate one with lower complexity. We also develop a time-division duplex access protocol along with orthogonal user codes to enable impulse radio as a radio link for wireless cellular systems. Relying on this protocol, we then derive a multiple-input/multiple-output equivalent model for full continuous-time model and a single-input/single-output model, for the approximate one. Based on these models, we finally develop design composite linear/nonlinear receivers for the downlink. The linear step eliminates multiuser interference deterministically and accounts for frequency-selective multipath while a maximum-likelihood receiver performs symbol detection. Simulations are provided to compare performance of the different receivers.

A novel multiuser-interference (MUI)-free code division multiple access (CDMA) transceiver for frequency-selective multipath channels is developed. Relying on chip-interleaving and zero padded transmissions, orthogonality among different users' spreading codes is maintained at the receiver even after frequency-selective propagation. As a result, deterministic multiuser separation with low-complexity code-matched filtering becomes possible without loss of maximum likelihood optimality. In addition to MUI-free reception, the proposed system guarantees channel-irrespective symbol detection and achieves high bandwidth efficiency by increasing the symbol block size. Filling the zero-gaps with known symbols allows for perfectly constant modulus transmissions. Important variants of the proposed transceivers are derived to include cyclic prefixed transmissions and various redundant or nonredundant precoding alternatives. (Semi-) blind channel estimation algorithms are also discussed. Simulation results demonstrate improved performance of the proposed system relative to competing alternatives.

Impulse radio (IR) is an ultra-wideband system with attractive features for baseband asynchronous multiple-access (MA), multimedia services, tactical wireless communications and networking. Implemented with analog components, the continuous-time IRMA model utilizes pulse-position modulation (PPM) and random time-hopping codes to alleviate multipath effects and suppress multiuser interference (MUI). We develop here a novel all-digital IRMA scheme and its discrete-time equivalent model that relies on pulse-amplitude modulation (PAM) and judiciously designed orthogonal user codes to eliminate MUI deterministically and account for frequency-selective multipath in the downlink. We also design a time-division-duplex access protocol and low-complexity linear multichannel receivers that we compare and test both analytically and by simulation.

In this paper we propose two new totally blind block equalizers for linear modulations using approximated maximum likelihood criteria. Totally means here that we assume we don't know the emitted symbols or the constellation (the modulation type). The coefficient update equations turn out to be functions of the equalizer output score function (SF). Because of our assumptions we have no closed form expression for the probability density function (PDF) and we propose to estimate the SF using the equalizer output samples. The performance of the equalizers is compared with the constant modulus algorithm (CMA). It shows that for a small number of symbols the proposed equalizers can remove all the inter symbol interference (ISI) while the CMA performs poorly. For severe channels the CMA appears to be more robust (our equalizers may not converge) but in this case our equalizers can be used after the CMA with very good results. Lastly when the algorithms converge, performance of our equalizers is similar to the decision directed one but in a totally blind way and without its drawbacks.

This paper deals with modulation classification. First, a state of the art is given which is separated into two classes: the pattern recognition approach and the maximum likelihood (ML) approach. Then we propose a new classifier called the general maximum likelihood classifier (GMLC) based on an approximation of the likelihood function. We derive equations of this classifier in the case of linear modulation and apply them to the MPSK/M'PSK problem. We show that the new tests are a generalisation of the previous ones using the ML approach, and don't need any restriction on the baseband pulse. Moreover the GMLC provides a theoretical foundation for many empirical classification systems including those systems that exploit the cyclostationary property of modulated signals.

A multiple hypothesis modulation QAM classification task is addressed. The classifier is designed within the rigorous framework of decision theory. A characteristic feature is extracted from the signal, and is compared to the possible theoretical features in the maximum likelihood sense. This feature is composed of a combination between fourth-order and squared second-order cyclic temporal cumulants. No assumption about the power of the signal is made. It is shown that this uncertainty about the power of the signal does not affect the decision rule. As an application, we present simulated performance in the context of 4-QAM vs 16-QAM vs 64-QAM classification.