Learning End-to-End Codes for the BPSK-constrained Gaussian Wiretap Channel

Finite-length codes are learned for the Gaussian wiretap channel in an end-to-end manner assuming that the communication parties are equipped with deep neural networks (DNNs), and communicate through binary phase-shift keying (BPSK) modulation scheme. The goal is to find codes via DNNs which allow a pair of transmitter and receiver to communicate reliably and securely in the presence of an adversary aiming at decoding the secret messages. Following the information-theoretic secrecy principles, the security is evaluated in terms of mutual information utilizing a deep learning tool called MINE (mutual information neural estimation). System performance is evaluated for different DNN architectures, designed based on the existing secure coding schemes, at the transmitter. Numerical results demonstrate that the legitimate parties can indeed establish a secure transmission in this setting as the learned codes achieve points on almost the boundary of the equivocation region

Low spatial peak-to-average power ratio transmission for improved energy efficiency in massive mimo systems

A significant portion of the operating power of a base station is consumed by power amplifiers (PAs). Much of this power is dissipated in the form of heat, as the overall efficiency of currently deployed PAs is typically very low. This is because the structure of conventional precoding techniques typically results in a relatively high variation in output power at different antennas in the array, and many PAs are operated well below saturation to avoid distortion of the transmitted signals. In this work, we use a realistic model for power consumption in PAs and study the impact of power variation across antennas in the array on the energy efficiency of a massive MIMO downlink system. We introduce a family of linear precoding matrices that allow us to control the spatial peak-to-average power ratio by projecting a fraction of the transmitted power onto the null space of the channel. These precoding matrices preserve the structure of conventional precoders; e.g., they suppress multiuser interference when used together with zeroforcing precoding and bring advantages over these precoders by operating PAs in a more power-efficient region and reducing the total radiated distortion. Our numerical results show that by controlling the power variations between antennas in the array and incorporating the nonlinearity properties of PA into the precoder optimization, significant gains in energy efficiency can be achieved over conventional precoding techniques

An extended kalman filter framework for joint phase noise, CFO and sampling time error estimation

We present a framework for joint estimation and compensation of three major oscillator impairments, namely sampling time error (STE), carrier frequency offset (CFO) and phase noise (PN). In particular, we model these impairments as Wiener processes and introduce a pilot-aided approach which facilitates their joint estimation. The proposed solution is carried out in two steps: first, an initial estimation of the transmitted symbols is acquired by applying an extended Kalman filter (EKF) on the pilot symbols and then, a second EKF is applied on the estimated symbols which yields an accurate tracking of STE, PN and CFO over an additive white Gaussian noise channel. Our numerical results demonstrate the efficacy of the proposed solution

An additive noise modeling technique for accurate statistical study of residual RF hardware impairments

Hardware impairments are the inevitable limiting factors in radio frequency communication systems, and in particular in mm-wave, the impairments can severely affect system performance. In this paper, we propose an additive noise modeling technique for modeling and analyzing the residual hardware impairments, more accurately than previously done in the literature. We analyze the effects of joint residual phase noise and IQI in both transmitter and receiver by using additive noise modeling as a representation method and indicate how other impairments can be described in the same framework. We derive the signal to distortion plus noise ratio (SDNR) for both the joint and the individual effects of impairments and validate the formulations with simulations which also acknowledge the usefulness of the additive noise modeling as a mean for accurate hardware impairments study

Statistical analysis of antenna array systems with perturbations in phase, gain and element positions

In this paper, we statistically analyze the effect of hardware impairments on power pattern of antenna array systems. We consider a linear array and formulate the stochastic beam pattern as a function of variations in phase, gain and element positions. By deriving a closed-form expression for the variance of the power pattern, we express how the performance of antenna array can be degraded in each angle, allowing for investigation of the role of each parameter in the final power pattern variations. The proposed closed-form expression serves as a tractable tool for analyzing the effect of perturbations in different settings

An Overview of Physical Layer Security with Finite-Alphabet Signaling

Providing secure communications over the physical layer with the objective of achieving perfect secrecy without requiring a secret key has been receiving growing attention within the past decade. The vast majority of the existing studies in the area of physical layer security focus exclusively on the scenarios where the channel inputs are Gaussian distributed. However, in practice, the signals employed for transmission are drawn from discrete signal constellations such as phase shift keying and quadrature amplitude modulation. Hence, understanding the impact of the finite-alphabet input constraints and designing secure transmission schemes under this assumption is a mandatory step towards a practical implementation of physical layer security. With this motivation, this article reviews recent developments on physical layer security with finite-alphabet inputs. We explore transmit signal design algorithms for single-antenna as well as multi-antenna wiretap channels under different assumptions on the channel state information at the transmitter. Moreover, we present a review of the recent results on secure transmission with discrete signaling for various scenarios including multi-carrier transmission systems, broadcast channels with confidential messages, cognitive multiple access and relay networks. Throughout the article, we stress the important behavioral differences of discrete versus Gaussian inputs in the context of the physical layer security. We also present an overview of practical code construction over Gaussian and fading wiretap channels, and we discuss some open problems and directions for future research.Comment: Submitted to IEEE Communications Surveys & Tutorials (1st Revision

Statistical Study of Hardware Impairments Effect on mmWave 77 GHz FMCW Automotive Radar

In this paper, we analyze the effects of hardwareimpairments on 77GHz FMCW automotive radar performance.Joint in-phase/quadrature imbalance (IQI) and phase noise effects on frequency-modulated continuous-wave (FMCW) radar transceiverfront-end is modeled through statistical analysis of distortionand noise. We derive the signal to distortion plus noise ratio,constant false alarm rate, and range-Doppler sensitivity analysisfor both the joint and the individual effects of impairmentsand validate the formulations with simulations. The representedmodeling and analysis can be used in millimeter wave (mmWave) FMCW automotiveradar signal processing algorithms for optimum transceiverdesign

Privacy-Preserving Wireless Federated Learning Exploiting Inherent Hardware Impairments

We consider a wireless federated learning system where multiple data holder edge devices collaborate to train a global model via sharing their parameter updates with an honest-but-curious parameter server. We demonstrate that the inherent hardware-induced distortion perturbing the model updates of the edge devices can be exploited as a privacy-preserving mechanism. In particular, we model the distortion as power-dependent additive Gaussian noise and present a power allocation strategy that provides privacy guarantees within the framework of differential privacy. We conduct numerical experiments to evaluate the performance of the proposed power allocation scheme under different levels of hardware impairments