In this paper, we explore the calibration of a machine learning (ML)-based outage predictor aimed at optimizing resource allocation to minimize outages in communication systems. We model the wireless channel using an auto-correlated time series with samples distributed in accordance with a Rayleigh fading process. Our novel contribution concerns proposing histogram-based reliability plots that employ logarithmic binning to assess its impact on the model calibration compared to the traditional linear binning technique. We train our ML model using an outage loss function (OLF) tailored to this system and the well-known binary cross entropy (BCE). Additionally, we analyze the effect of different model parameters on the calibration performance of this outage predictor. Our findings demonstrate that logarithmic binning reveals nuanced calibration traits ignored by linear binning, particularly at lower confidence levels. This finding is crucial for wireless systems for which understanding behavior at very low probabilities is essential. Additionally, we observe that our ML model trained with OLF becomes more overconfident as the classification threshold increases and in scenarios characterized with rare events, namely outages. This observation serves as a tool for improving the calibration properties of OLF.

We study amplify-and-forward (AF) relay networks operating with source and relay amplifier distortion, where the distortion dominates the noise power. The diversity order is shown to be 0 for fixed-gain (FG) and 1 for variable-gain (VG) if distortion occurs at the relay; if distortion occurs only at the source, the diversity order will be 1 for both. With εβ= N0/ηβ(N0the noise power, ηβthe distortion power at node β ϵ {S, R}, the source or relay), we demonstrate the emergence of what we call an ε-critical signal-to-noise plus distortion ratio (SNDR) threshold (a threshold that emerges when min{εβ} becomes small) for both forwarding protocols. We show that crossing this threshold in distortion limited regions will cause a phase transition (a dramatic drop) in the network's outage probability. Thus, small reductions in the required end-to-end transmission rate can have significant reductions in the network's outage probability.

In this paper, we analyze capacity and power scaling in multihop cooperative AF relay networks. An analytical framework for this task is developed by drawing a correspondence between random Fibonacci sequences and the end-to-end multihop system model. It turns out, the exponential growth rate of these interesting sequences can be employed to establish scaling laws, from which we conclude that it is possible to construct multihop cooperative AF networks that simultaneously avoid 1) exponential capacity decay and 2) exponential transmit power growth across the network. This is done by ensuring the network's Lyapunov exponent (a key observable studied in random dynamical system theory) is zero, which can be achieved by appropriately selecting the amplification factors at each of the relay nodes. Our results apply to both fixed-gain and variable-gain relaying. To conclude our work, we demonstrate the presented theory through numerical simulations.

In recent years, Bussgang's theorem has proven useful when studying and optimizing peak-power constrained OFDM-based amplify-and-forward (AF) networks. For the variable-gain (VG) scenario, Bussgang's theorem can be applied at the relay without taking into consideration the instantaneous behavior of the channel. This significantly improves the mathematical tractability of performance evaluation. For fixed-gain (FG) relaying, this is not necessarily the case, and we must also ensure that a sufficient number of significant channel taps are present in the channel response if we wish to ignore the channel's instantaneous behavior. In this paper, we determine conditions that the power-decay profile of the channel's l tap response must satisfy so that, in the limit of large l the FG Bussgang parameters become independent of the channel's instantaneous behavior. We conclude our analysis by considering some examples (exponential and power-law decay profiles). For exponential profiles we find that exact calculation of the Bussgang parameters always requires instantaneous channel knowledge, regardless of the number of channel taps present; while for power-law profiles this is not necessarily the case, provided the decay is not too steep.

In this work, we analyze the distance statistics corresponding to points in a Matern cluster (offspring points) and points that do not belong to that cluster (non-offspring points). We first derive the probability density function (PDF) of the distance between an offspring point and a non-offspring point of a Matern cluster. We then formulate the probability generating functional based on this PDF. Since many wireless networks (e.g., device-to-device (D2D) networks and cognitive radio systems) exhibit device clustering, this formalism enables us to efficiently formulate and evaluate expressions that describe the interference statistics and connection probability in clustered networks. We validate our theoretical analysis with numerical simulations, and illustrate that traditional methods of evaluating similar performance metrics (based on point process statistics instead of distance statistics) are unsuitable for use in such complex scenarios.

In this paper, we analyze the outage performance of two multicarrier relay selection schemes, i.e. bulk and per-subcarrier selections, for two-hop orthogonal frequency-division multiplexing (OFDM) systems. To provide a comprehensive analysis, three forwarding protocols: decode-and-forward (DF), fixed-gain (FG) amplify-and-forward (AF) and variable-gain (VG) AF relay systems are considered. We obtain closed-form approximations for the outage probability and closed-form expressions for the asymptotic outage probability in the high signal-to-noise ratio (SNR) region for all cases. Our analysis is verified by Monte Carlo simulations, and provides an analytical framework for multicarrier systems with relay selection.

In this paper, we obtain novel analytical formulations for the outage probability (OP) in scenarios with α-μ or κ-μ faded signals of interest (SoI), and κ-μ or α-μ faded co-channel interference (CCI). Both single and multiple interfering scenarios have been considered, and exact formulations are provided when the SoI experiences α-μ fading and the CCI experiences κ-μ fading. When the SoI is subject to κ-μ fading and the CCI is subject to α-μ fading, exact and highly accurate approximate OP expressions have been derived for the single and multiple interfering cases, respectively. We also analyze the asymptotic behavior of the OP when the average signal-to-noise-ratio (SNR) of the SoI is significantly larger or smaller than that of the interferers. Monte-Carlo simulations are performed to verify the derived results. It is worth highlighting that these general expressions are important as they unify the CCI for a number of previously disjoint fading scenarios.

We present a novel data programming scheme for flash memory. In each word-line, exactly k out of n memory cells are programmed while the rest are kept in the erased state. Information is then conveyed by the index set of the k programmed cells, of which there are (kn) possible choices k (also called activation patterns). In the case of multi-level flash, additional information is conveyed by the threshold-voltage levels of the k programmed cells (similar to traditional programming). We derive the storage efficiency of the new scheme as a function of the fraction of programmed cells and determine the fraction that maximizes it. Then, we analyze the effect of this scheme on cell-to-cell interference and derive the conditions that ensure its reduction compared with the traditional programming. Following this, we analyze the performance of our new scheme using two detection methods: fixed reference detection and dynamic reference detection, and conclude that using dynamic reference detection will result in page error performance improvements that can reach orders of magnitude compared with that attainable by the fixed reference approach. We then discuss how logical pages can be constructed in the index programming similarly to traditional programming. Finally, we discuss the results and tradeoffs between storage efficiency and error resilience proposed by the scheme along with some future directions.

A novel framework is presented that can be used to study the capacity and power scaling of linear multiple-input multiple-output (MIMO) d×d antenna amplify-and-forward (AF) relay networks. In particular, we model these networks as random dynamical systems (RDS) and calculate their d Lyapunov exponents. Our framework can be applied to systems with any per-hop channel fading distribution provided the expected logarithm of the channel matrices' norms are finite; in this contribution all of our results relate specifically to Rayleigh fading. Our main results are twofold: 1) the total transmit power at the nth node will follow a deterministic trajectory through the network governed by the network's maximum Lyapunov exponent, 2) the capacity of the ith eigenchannel at the nth node will follow a deterministic trajectory through the network governed by the network's ith Lyapunov exponent. Before concluding, we present some numerical examples to highlight the theory.

In this paper, we apply the concept of combined bulk/per-subcarrier selection to two-hop relay selection systems employing OFDM. The outage probability of the proposed strategy is analyzed in the high SNR regime when decode-and-forward, fixed-gain amplify-and-forward and variable-gain amplify-and-forward are employed at the relays. Meanwhile, a generalized situation without specifying the relaying protocol is also analyzed. We mathematically prove that the combined selection strategy is able to achieve an optimal outage probability equivalent to conventional per- subcarrier selection in the high SNR regime without using the full set of available relays for selection. Moreover, we demonstrate through numerical simulations that this performance advantage holds when channels are spatially correlated.

In this paper, we consider the transmission of confidential information over a κ-μ fading channel in the presence of an eavesdropper who also experiences κ-μ fading. In particular, we obtain novel analytical solutions for the probability of strictly positive secrecy capacity (SPSC) and a lower bound of secure outage probability (SOPL) for independent and non-identically distributed channel coefficients without parameter constraints. We also provide a closed-form expression for the probability of SPSC when the μ parameter is assumed to take positive integer values. Monte-Carlo simulations are performed to verify the derived results. The versatility of the κ-μ fading model means that the results presented in this paper can be used to determine the probability of SPSC and SOPL for a large number of other fading scenarios, such as Rayleigh, Rice (Nakagamin), Nakagami-m, One-Sided Gaussian, and mixtures of these common fading models. In addition, due to the duality of the analysis of secrecy capacity and co-channel interference (CCI), the results presented here will have immediate applicability in the analysis of outage probability in wireless systems affected by CCI and background noise (BN). To demonstrate the efficacy of the novel formulations proposed here, we use the derived equations to provide a useful insight into the probability of SPSC and SOPL for a range of emerging wireless applications, such as cellular device-to-device, peer-to-peer, vehicle-to-vehicle, and body centric communications using data obtained from real channel measurements.

In this paper, we present a novel framework that can be used to study the capacity and power scaling properties of linear multiple-input multiple-output d×d antenna amplify-and-forward relay networks. In particular, we model these networks as random dynamical systems and calculate their d Lyapunov exponents. Our analysis can be applied to systems with any perhop channel fading distribution; although in this contribution, we focus on Rayleigh fading. Our main results are twofold: 1) the total transmit power at the nth node will follow a deterministic trajectory through the network governed by the network's maximum Lyapunov exponent and 2) the capacity of the ith eigenchannel at the nth node will follow a deterministic trajectory through the network governed by the network's ith Lyapunov exponent. Before concluding, we concentrate on some applications of our results. In particular, we show how the Lyapunov exponents are intimately related to the rate at which the eigenchannel capacities diverge from each other, and how this relates to the amplification strategy and the number of antennas at each relay. We also use them to determine the extra cost in power associated with each extra multiplexed data stream.

We describe a novel technique that can be used to allow two parties to exchange a secret key over an orthogonal frequency division multiplexing (OFDM) channel with perfect secrecy, provided subcarriers are subject to independent fading and a malicious attacker is passively eavesdropping. Our approach is shown to be robust against the eavesdropper's channel being correlated with that of the legitimate users, and also active attacks in which the eavesdropper injects fraudulent messages into the system. For the active attack, we show that when the eavesdropper injects fraudulent messages into the system, they will also inadvertently allow the legitimate users to calculate a lower bound on the secrecy capacity of the channel. This allows them to establish whether secrecy has been achieved. A consequence of our approach is that the degrees of freedom within the channel are halved.