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Wake steering is a technique that optimizes the energy production of a wind farm by employing yaw control to misalign upstream turbines with the incoming wind direction. This work highlights the important dependence between wind direction variations and wake steering optimization. The problem is formalized over time as the succession of multiple steady-state yaw control problems interconnected by the rotational constraints of the turbines and the evolution of the wind. Then, this work proposes a reformulation of the yaw optimization problem of each time step by augmenting the objective function by a new heuristic based on a wind prediction. The heuristic acts as a penalization for the optimization, encouraging solutions that will guarantee future energy production. Finally, a synthetic sensitivity analysis of the wind direction variations and wake steering optimization is conducted. Because of the rotational constraints of the turbines, as the magnitude of the wind direction fluctuations increases, the importance of considering wind prediction in a steady-state optimization is empirically demonstrated. The heuristic proposed in this work greatly improves the performance of controllers and significantly reduces the complexity of the original sequential decision problem by decreasing the number of decision variables. [ABSTRACT FROM AUTHOR]

A new method is developed for designing optimum training sequences (TS) that have efficiently accounted for the errors due to channel and carrier frequency offset estimation. This new method is based on the minimization of the mean square error on data estimation at the output of the Wiener-type equalizer averaged over the channel statistics.

The paper deals with design and performance analysis of orthogonal frequency-division multiple-access (OFDMA)based downlink cellular wireless communications. Due to a high degree of user mobility, the base station is assumed to have only a statistical knowledge of the users' channels. Relying on the ergodic capacities connected to the user rates, a subcarrier and power allocation that minimizes the total transmitted power is proposed. The allocation strategy requires only the knowledge of the channel statistics and the rate requirements for all users. An extension and a performance analysis of this allocation algorithm in a multicell environment working with a frequency re-use factor equal to one is also conducted. A condition for the multicell network to be able to satisfy all rate requirements is derived. Index Terms--Ergodic capacity, frequency-hopping (FH), multicell interference (MCI), orthogonal frequency-division multiple access (OFDMA), power and subcarrier allocation.

We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems. We study the performance of a standard CFO estimate, which consists of first raising the received signal to the M th power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of samples required in the CFO estimation procedure, in order to ensure that the MSE on estimation is not significantly affected by the outliers. Index Terms--Blind estimation, frequency-offset synchronization, outlier effect, performance at low signal-to-noise ratio (SNR), quadrature amplitude modulation (QAM) constellation.

A study considers the issue of joint sampling clock offset estimation and channel estimation for orthogonal-frequency-division multiplex (OFDM) modulation used in wireline transmissions. The estimation performance is studied through the Cramer-Rao bound (CRB) analysis.

A new decision-directed (DD) synchronization scheme is proposed for joint estimation of carrier frequency offset (CFO) and sampling clock frequency offset (SFO) in orthogonal frequency-division multiplexing (OFDM) systems. By exploiting the hard decisions, we report accurate estimators of residual CFO and small SFO. The performance analysis and simulation results indicate that the proposed novel DD scheme achieves much better performance than the conventional pilot-based schemes in both additive white Gaussian noise and frequency-selective channels. Index Terms--Carrier frequency offset (CFO), fast Fourier transform (FFT), orthogonal frequency-division multiplexing (OFDM), sampling clock frequency offset (SFO), synchronization.

A new blind carrier frequency offset estimator is developed for OFDM/OQAM signal. The proposed estimator appears to be very well adapted for a tracking mode rather than for an acquisition mode.

This paper introduces and analyzes the asymptotic (large sample) performance of a family of blind feedforward nonlinear least-squares (NLS) estimators for joint estimation of carrier phase, frequency offset, and Doppler rate for burst-mode phase-shift keying transmissions. An optimal or "matched" nonlinear estimator that exhibits the smallest asymptotic variance within the family of envisaged blind NLS estimators is developed. The asymptotic variance of these estimators is established in closed-form expression and shown to approach the Cramer-Rao lower bound of an unmodulated carrier at medium and high signal-to-noise ratios (SNR). Monomial nonlinear estimators that do not depend on the SNR are also introduced and shown to perform similarly to the SNR-dependent matched nonlinear estimator. Computer simulations are presented to corroborate the theoretical performance analysis. Index Terms--Burst transmission, carrier phase, Doppler rate, frequency offset, M-ary phase-shift keying (MPSK), synchronization.

Recently, Lee has proposed a blind feedforward symbol timing estimator that exhibits low computational complexity and requires only two samples per symbol. In this paper, Lee's estimator is analyzed rigorously by exploiting efficiently the cyclostationary statistics present in the received oversampled signal, and its asymptotic (large sample) bias and mean-square error (MSE) are derived in closed-form expression. A new blind feedforward timing estimator that requires only two samples per symbol and presents the same computational complexity as Lee's estimator is proposed. It is shown that the proposed new estimator is asymptotically unbiased and exhibits smaller MSE than Lee's estimator. Computer simulations are presented to illustrate the performance of the proposed new estimator with respect to Lee's estimator and the existing conventional estimators. Index Terms--Asymptotic performance analysis, blind feedforward estimation, cyclostationarity, symbol timing estimation.

The problem of nondata-aided frequency offset estimation for noncircular transmissions via frequency-selective channels in linear precoder-based communications contexts is investigated and discussed.

This paper investigates the decoding of a remarkable set of lattices: We treat in a unified framework the Leech lattice in dimension 24, the Nebe lattice in dimension 72, and the Barnes-Wall lattices. A new interesting lattice, named $L_{3\cdot 24}$ , is constructed as a simple application of the single parity check on the Leech lattice. The common aspect of these lattices is that they can be obtained via a single parity check or via the $k$ -ing construction. We exploit these constructions to introduce a new efficient paradigm for decoding. This leads to efficient list decoders and quasi-optimal decoders on the Gaussian channel. Both theoretical and practical performance (point error probability and complexity) of the new decoders are provided. [ABSTRACT FROM AUTHOR]

We characterize the complexity of the lattice decoding problem from a neural network perspective. The notion of Voronoi-reduced basis is introduced to restrict the space of solutions to a binary set. On the one hand, this problem is shown to be equivalent to computing a continuous piecewise linear (CPWL) function restricted to the fundamental parallelotope. On the other hand, it is known that any function computed by a ReLU feed-forward neural network is CPWL. As a result, we count the number of affine pieces in the CPWL decoding function to characterize the complexity of the decoding problem. It is exponential in the space dimension $n$ , which induces shallow neural networks of exponential size. For structured lattices we show that folding, a technique equivalent to using a deep neural network, enables to reduce this complexity from exponential in $n$ to polynomial in $n$. Regarding unstructured MIMO lattices, in contrary to dense lattices many pieces in the CPWL decoding function can be neglected for quasi-optimal decoding on the Gaussian channel. This makes the decoding problem easier and it explains why shallow neural networks of reasonable size are more efficient with this category of lattices (in low to moderate dimensions). [ABSTRACT FROM AUTHOR]

The asymptotic performance of blind carrier frequency offset and timing delay estimators, derived from previous research, are analyzed. The estimators rely on second-order cyclostationary statistics obtained by oversampling the output of the receive filter.

This paper considers the problem of blind symbol rate estimation of signals linearly modulated by a sequence of unknown symbols. Oversampling the received signal generates cyclostationary statistics that are exploited to devise symbol-rate estimators by maximizing in the cyclic domain a (possibly weighted) sum of modulus squares of cyclic correlation estimates. Although quite natural, the asymptotic (large sample) performance of this estimator has not been studied rigorously. The consistency and asymptotic normality of this symbol-rate estimator is established when the number of samples N converges to infinity. It is shown that this estimator exhibits a fast convergence rate (proportional to [N.sup.-3/2]), and it admits a simple closed-form expression for its asymptotic variance. This asymptotic expression enables performance analysis of the rate estimator as a function of the number of estimated cyclic correlation coefficients and the weighting matrix. A justification for the high performance of the unweighted estimator in high signal-to-noise scenarios is also provided. Index Terms--Cumulant, cyclostationary, estimation, frequency, spectrum estimation, symbol rate.

Performance of a frequency offset estimator is examined, assuming an unknown frequency-selective channel and noncircularly distributed symbols. It is shown that the estimator is consistent and asymptotically normal, and a closed-form expression of its asymptotic variance is established.

Research describing carrier phase synchronization for quadrature amplitude constellations is presented. In particular a performance analysis of blind carrier phase estimator algorithms is carried out and their relative merits compared.

The alpha-repetition/modulation scheme is considered.

In this letter, we develop some generic power allocation strategies in an uplink multiband satellite communications system when nonlinear impairments on the High-Power Amplifier onboard satellite occur. Based on the capacity closed-form expression related to receivers seeing nonlinear interference as a noise, we propose practical and scalable algorithms for three power allocation problems: i) sum-power minimization, ii) maximization of minimum per-user data rate, iii) sum-rate maximization. We show that the solutions mainly rely on Geometric Programming and/or Successive Convex Approximation approaches. The proposed solutions outperform naive approaches while enabling user scalability contrary to optimal brute-force grid search algorithms. [ABSTRACT FROM AUTHOR]

In order to improve the transmission reliability in current wireless communication systems, the Hybrid Automatic ReQuest (HARQ) protocol is employed to manage the unknown time-varying channel. The acknowledgments are fed back with delay on the return link. To fill up the idle time between a transmission and its acknowledgment, parallel HARQ streams associated with different messages are carried out. In this paper we improve on parallel HARQ by proposing a multi-layer HARQ protocol (also called superposition coding or multi-packet HARQ), where a single transmission may carry information on multiple messages. The multi-layer HARQ protocol works in presence of delay on the return link as parallel HARQ does, and does not require additional feedback such as the channel state information. It aims at improving the accuracy as well as the user’s delay distribution, thus achieving throughput increase. Assuming capacity-achieving codes, we show that the proposed protocol outperforms parallel HARQ in throughput, message error rate, and delay distribution. Using practical codes and decoding algorithms the gains are as well significant, at the expense of the receiver’s complexity. [ABSTRACT FROM AUTHOR]

We address the estimation of the Ricean $K$ factor when the available complex channel samples are noisy and subject to Nakagami- $m$ shadowing, i.e., the line-of-sight component is modeled as a Nakagami- $m$ random variable. We propose two estimators: one based on the expectation-maximization (EM) procedure, and a second one based on the method of moment (MoM). The MoM estimator can be used to initialize the EM procedure. We show by simulations that the two proposed estimators outperform the existing ones. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper addresses the resource allocation (RA) problem for orthogonal frequency division multiple access and single carrier frequency division multiple access based networks using hybrid automatic repeat request (HARQ) when considering energy efficiency (EE) as the metric to optimize. The RA is performed considering the Rayleigh channel, and assuming that only statistical channel state information is available, which fits well device-to-device (D2D) communications setup. Moreover, the use of practical modulation and coding schemes is taken into account. We formulate several RA problems with different EE criteria, subject to constraints on the minimum goodput and the maximum transmit power per-link. Based on a packet error probability approximation, we provide a framework which allows us to derive algorithms maximizing most of the common EE criteria, namely the sum of the EE of the links, the product of the EE, the EE of the link with the worst EE, and the EE of the whole network. The complexity of the proposed algorithms is also provided. The performance related to each criterion are evaluated through simulations and ranked according to the network configurations. We also illustrate on a practical example the real effectiveness of the EE criterion to achieve a better user experience than other common criteria such as the maximum sum rate and the minimum transmit power. [ABSTRACT FROM AUTHOR]

High-fidelity, real-time interactive applications are envisioned with the emergence of the Internet of Things and tactile Internet by means of ultra-reliable low-latency communications (URLLC). Exploiting time diversity for fulfilling the URLLC requirements in an energy efficient manner is a challenging task due to the nontrivial interplay among packet size, retransmission rounds and delay, and transmit power. In this paper, we study the fundamental energy-latency tradeoff in URLLC systems employing incremental redundancy (IR) hybrid automatic repeat request (HARQ). We cast the average energy minimization problem with a finite blocklength (latency) constraint and feedback delay, which is non-convex. We propose a dynamic programming algorithm for energy efficient IR-HARQ optimization in terms of number of retransmissions, blocklength, and power per round. Numerical results show that our IR-HARQ approach could provide around 25% energy saving compared with one-shot transmission (no HARQ). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

For long-haul Nyquist-wavelength division multiplexing superchannel transmission, an inter-subcarrier nonlinear and linear interference canceler (INIC) is proposed. This approach consists in detecting the adjacent subcarriers, regenerating them thanks to the Volterra series model of optical fiber, and removing them from the subcarrier of interest. Different ways to implement the INIC are described and compared with the well-known techniques, such as digital backpropagation (DBP) and Volterra-based nonlinear equalizer (VNLE) implemented in a subcarrierwise manner. Significant performance gain (on either the $Q$ factor or transmission distance) is observed. In the context of 400 Gbps scheme, the transmission distance gain is up to 500 km compared with the DBP and VNLE. [ABSTRACT FROM PUBLISHER]

We investigate the primary user emulation (PUE) attack, which is a serious security problem in cognitive radio (CR) networks. There exist three types of PUE attackers: 1) a selfish one, which aims at maximizing its selfish usage of channel resource; 2) a malicious one, which points for obstructing the operation of CR network; and 3) a mixed one, which is between a selfish and malicious PUE attacker. For combating a selfish PUE attacker, a channel surveillance process has to be implemented in order to determine active user's identification and so selfish PUE attacker. An extra-sensing process has to be implemented for observing new opportunities to access the channel and so for mitigating the malicious PUE attacker's effect. Relevant strategies for deploying the above processes are obtained through a game theory-based analysis and the exhibition of Nash equilibrium (NE). We show the NE strongly depends on the network demand, the availability of the spectrum resource, and the type of the attacker. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

Distributed estimation of the average value over a Wireless Sensor Network has recently received a lot of attention. Most papers consider single variable sensors and communications with feedback (e.g., peer-to-peer communications). However, in order to use efficiently the broadcast nature of the wireless channel, communications without feedback are advocated. To ensure the convergence in this feedback-free case, the recently-introduced Sum-Weight-like algorithms which rely on two variables at each sensor are a promising solution. In this paper, the convergence towards the consensus over the average of the initial values is analyzed in depth. Furthermore, it is shown that the squared error decreases exponentially with the time. In addition, a powerful algorithm relying on the Sum-Weight structure and taking into account the broadcast nature of the channel is proposed. [ABSTRACT FROM PUBLISHER]

In this paper, we address the problem of estimating the maximal value over a sensor network using wireless links between them. We introduce two heuristic algorithms and analyze their theoretical performance. More precisely, i) we prove that their convergence time is finite with probability one, ii) we derive an upper-bound on their mean convergence time, and iii) we exhibit a bound on their convergence time dispersion. [ABSTRACT FROM PUBLISHER]

In this pair of papers (Part I and Part!! in this issue), we investigate the issue of power control and subcarrier assignment in a sectorized two-cell downlink OFDMA system impaired by multicell interference. As recommended for WiMAX, we assume that the first part of the available bandwidth is likely to be reused by different base stations (and is thus subject to multicell interference) and that the second part of the bandwidth is shared in an orthogonal way between the different base stations (and is thus protected from multicell interference). Although the problem of multicell resource allocation is nonconvex in this scenario, we provide in Part I the general form of the global solution. In particular, the optimal resource allocation turns out to be "binary" in the sense that, except for at most one pivot-user in each cell, any user receives data either in the reused bandwidth or in the protected bandwidth, but not in both. The determination of the optimal resource allocation essentially reduces to the determination of the latter pivot-position. [ABSTRACT FROM AUTHOR]

In a companion paper (see "Resource Allocation for Downlink Cellular OFDMA Systems-Part I: Optimal Allocation," IEEE Trans. Signal Process., vol. 58, no. 2, pp. 720-734, Feb. 2010), we characterized the optimal resource allocation in terms of power control and subcarrier assignment, for a downlink sectorized OFDMA system impaired by multicell interference. In our model, the network is assumed to be one dimensional (linear) for the sake of analysis. We also assume that a certain part of the available bandwidth is likely to be reused by different base stations while that the other part of the bandwidth is shared in an orthogonal way between these base stations. The optimal resource allocation characterized in Part I is obtained by minimizing the total power spent by the network under the constraint that all users' rate requirements are satisfied. It is worth noting that when optimal resource allocation is used, any user receives data either in the reused bandwidth or in the protected bandwidth, but not in both (except for at most one pivot-user in each cell). We also proposed an algorithm that determines the optimal values of users' resource allocation parameters. As a matter of fact, the optimal allocation algorithm proposed in Part! requires a large number of operations. In the present paper, we propose a distributed practical resource allocation algorithm with low complexity. We study the asymptotic behavior of both this simplified resource allocation algorithm and the optimal resource allocation algorithm of Part I as the number of users in each cell tends to infinity. Our analysis allows to prove that the proposed simplified algorithm is asymptotically optimal, i.e., it achieves the same asymptotic transmit power as the optimal algorithm as the number of users in each cell tends to infinity. As a byproduct of our analysis, we characterize the optimal value of the frequency reuse factor. Simulations sustain our claims and show that substantial performance improvements are obtained when the optimal value of the frequency reuse factor is used. [ABSTRACT FROM AUTHOR]

Carrier frequency offset (CFO) estimation is a key challenge in wireless systems employing orthogonal frequency-division multiplexing (OFDM) modulation. Often, CFO estimation is carried out using a pre- amble made of a number, say J, of repetitive slots (RS). We here focus on the issue of optimal RS preamble design using the Cramér-Rao bound (CRB) averaged over the channel, which is assumed to be Rayleigh. We show that the optimal value of J is a tradeoff between the multipath diversity gain and the number of unknowns to be estimated. In the case of correlated channel taps, we also show that uniform power loading of the active subcarriers is not optimal (in contrast with the uncorrelated case) and better power loading schemes are proposed. The proposed power loading schemes consist of allocating more power to activated carriers with higher signal-to-noise ratios. Simulation-based performance results of the maximum likelihood estimator support the CRB-based theoretical results. [ABSTRACT FROM AUTHOR]

A new decision-directed (DD) synchronization scheme is proposed for joint estimation of carrier frequency offset (CFO) and sampling clock frequency offset (SFO) in orthogonal frequency-division multiplexing (OFDM) systems. By exploiting the hard decisions, we report accurate estimators of residual CFO and small SFO. The performance analysis and simulation results indicate that the proposed novel DD scheme achieves much better performance than the conventional pilot-based schemes in both additive white Gaussian noise and frequency-selective channels. [ABSTRACT FROM AUTHOR]

This paper introduces and analyzes the asymptotic (large sample) performance of a family of blind feedforward nonlinear least-squares (NLS) estimators for joint estimation of carrier phase, frequency offset, and Doppler rate for burst-mode phaseshift keying transmissions. An optimal or "matched" nonlinear estimator that exhibits the smallest asymptotic variance within the family of envisaged blind NLS estimators is developed. The asymptotic variance of these estimators is established in closed-form expressrun and shown to approach the Cramèr-Rao lower hound of an unmodulated carrier at medium and high signal-to-noise ratios (SNR). Monomial nonlinear estimators that do not depend on the SNR are also introduced and shown to perform similarly to the SNR-dependent matched nonlinear estimator. Computer simulations are presented to corroborate the theoretical performance analysis. [ABSTRACT FROM AUTHOR]

Recently, Lee has proposed a blind feedforward symbol timing estimator that exhibits low computational complexity and requires only two samples per symbol. In this paper, Lee's estimator is analyzed rigorously by exploiting efficiently the cydostationary statistics present in the received oversampled signal, and its asymptotic (large sample) bias and mean-square error (MSE) are derived in dosed-form expression. A new blind feedforward timing estimator that requires only two samples per symbol and presents the same computational complexity as Lee's estimator is proposed. It is shown that the proposed new estimator is asymptotically unbiased and exhibits smaller MSE than Lee's estimator. Computer simulations are presented to illustrate the performance of the proposed new estimator with respect to Lee's estimator and the existing conventional estimators. [ABSTRACT FROM AUTHOR]

Deals with a study which examined the problem of non data-aided carrier frequency offset estimation of non circular modulations transmitted through unknown frequency-selective channels. Background on the growth of mobile wireless communication systems; Proposed estimators; Simulations.

In this work, a static relaying protocol, called Decode or Quantize and Forward (DoQF), is introduced for half duplex single-relay networks, and its performance is studied in the context of communications over slow fading wireless channels. The proposed protocol is inspired by the so-called Compress-and-Forward (CF) but only needs statistical Channel State Information at the Transmitter (CSIT). First, we analyze the behavior of the outage probability P_o of the proposed protocol as the SNR ? tends to infinity. In this case, we prove that ?^2 P_o converges to a constant ?. We refer to this constant as the outage probability gain and we derive its closed-form expression for a general class of wireless channels that includes Rayleigh and Rice. We furthermore prove that the DoQF protocol has the best achievable outage gain in the wide class of half-duplex static relaying protocols and we minimize ? w.r.t the power allocation to the source and the relay and the durations of the slots. Next, we focus on Rayleigh channels to derive the Diversity-Multiplexing Tradeoff (DMT) of the DoQF. Our results show that the DoQF achieves the 2 by 1 MISO DMT upper-bound for multiplexing gains r<0.25. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, we propose a resource allocation algorithm for the downlink of sectorized two-dimensional (2-D) OFDMA cellular networks assuming statistical Channel State Information (CSI) and fractional frequency reuse. The proposed algorithm can be implemented in a distributed fashion without any central controlling units. Its performance is analyzed assuming fast fading Rayleigh channels and Gaussian distributed multicell interference. We show that the transmit power of this simple algorithm tends, as the number of users grows to infinity, to the same limit as the minimal power required to satisfy all users' rate requirements i.e., the proposed resource allocation algorithm is asymptotically optimal. As a byproduct of this asymptotic analysis, we characterize a relevant value of the reuse factor that only depends on an average state of the network. [ABSTRACT FROM PUBLISHER]

• Contrastive learning based approach for learning powerful nodes' representation. • Self-supervised learning of graph representations using contrastive approaches. • Graph based negative sampling strategies for contrastive learning methods. Contrastive learning has become a successful approach for learning powerful text and image representations in a self-supervised manner. Contrastive frameworks learn to distinguish between representations coming from augmentations of the same data point (positive pairs) and those of other (negative) examples. Recent studies aim at extending methods from contrastive learning to graph data. In this work, we propose a general framework for learning node representations in a self supervised manner called Graph Constrastive Learning (GraphCL). It learns node embeddings by maximizing the similarity between the nodes representations of two randomly perturbed versions of the same graph. We use graph neural networks to produce two representations of the same node and leverage a contrastive learning loss to maximize agreement between them. We investigate different standard and new negative sampling strategies as well as a comparison without negative sampling approach. We demonstrate that our approach significantly outperforms the state-of-the-art in unsupervised learning on a number of node classification benchmarks in both transductive and inductive learning setups. [ABSTRACT FROM AUTHOR]