Search

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.

Abstract: The emerging trend to provide users with ubiquitous seamless wireless access leads to the development of multi-mode terminals able to smartly switch between heterogeneous wireless networks. This switching process known as vertical handoff requires the terminal to first detect the surrounding networks it is compatible with. In the context where these networks are cognitive, this can be challenging since the carrier frequency of their access point may change over the time. One solution to overcome this challenge is to embed network specific signatures in the PHY layer. We here focus on cognitive OFDM systems and advocate to embed signatures onto pilot tones since (i) it makes possible to discriminate systems with the same modulation parameters (ii) it creates easy to intercept signatures implying short detection latency (iii) it avoids adding any side information dedicated to detection that would reduce systems capacity. We propose two complementary signature/detection schemes based on second and third-order statistics, respectively. The first scheme relies on redundancy between pilot symbols and the second is based on the use of maximum-length sequences. Detailed numerical examples demonstrate the efficiency of the two detection criteria in realistic environments. [ABSTRACT FROM AUTHOR]

In the context of cooperative wireless networks that convey data on slow fading channels, outage probability Po is the relevant performance index from the point of view of information theory. Derivation and minimization of this probability with respect to the relaying protocol parameters is of central importance. However, it is often hard to derive its expression, let alone to find its exact minimum for all possible values of the signal-to-noise ratio (SNR). This problem can be simplified by studying the behavior of Po in the asymptotic regime where the SNR p converges to infinity. In this regime, usually ρN+1 Po converges to a constant ~ where N is the number of relays. In this paper, a simple and general method for deriving and minimizing ξ with respect to the power distribution between the source and the relays, and with respect to the durations of the slots specified by the relaying protocol, is developed. While the proposed approach is designed for the high SNR regime, simulations show that outage probability is reduced in a similar proportion at moderate SNR. The method applies to a general class of radio channels that includes the Rayleigh and the Rice channels as particular cases. Convexity of ξ with respect to the design parameters is shown. Decode-and-forward, as well as amplify-and-forward protocols are considered in the half duplex mode. [ABSTRACT FROM AUTHOR]

• 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]

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 reuse factor equal to one is also conducted. A condition for the multicell network to be able to satisfy all rate requirements is derived. [ABSTRACT FROM AUTHOR]

This paper considers the problem of sampling clock synchronization and channel estimation for orthogonal-frequency-division multiplex (OFDM) systems. In such systems, when the number of subcarriers is large, a sampling clock frequency mismatch between the transmitter and the receiver dramatically degrades the performance. So far, the literature proposes ad hoc estimation algorithms. However, a complete performance analysis, especially the Cramér-Rao bound (CRB) derivation, remains to be done. Obviously, the channel-impulse response is unknown at the receiver and also needs to be estimated. Therefore, the CRB associated with this joint estimation is theoretically evaluated. When the number of subcarriers and the channel degree are large, very compact closed-form expressions for the CRB are obtained. Furthermore, along with the maximum-likelihood (ML) estimator, suboptimal estimation algorithms are introduced and compared with some existing approaches and with the CRB. [ABSTRACT FROM AUTHOR]

Cognitive satellite communication (SatCom) is rapidly emerging as a promising technology to overcome the scarcity of the exclusive licensed band model in order to fulfill the increasing demand for high data rate services. The paper addresses power allocation methods for multi-operator multi-beam uplink satellite communication systems co-existing with a Ka-band terrestrial network, using cognitive radio paradigm. Such a scenario is especially challenging because of (i) the coexisting multiple SatCom operators over the cognitive band need to coordinate the use of their resources under limited inter-operator information exchange, and (ii) nonlinear onboard high power amplifier (HPA) which leads to nonlinear interference between users and beams. In order to tackle the first challenge, we propose distributed power allocation algorithms including the standard Alternate Direction Multiplier Method (ADMM); Regarding the HPA nonlinear impairment, we propose nonlinear-aware power allocation based on Signomial Programming. The proposed solutions outperform state-of-the-art in both cases., Competing Interests: Conflict of interestsThe authors declare that they have no competing interests., (© The Author(s) 2023.)