Arsenia Chorti

Spectrally Efficient FDM Signals: Bandwidth Gain at the Expense of Receiver Complexity

This paper investigates the transmission of Frequency Division Multiplexed (FDM) signals, where carrier orthogonality is intentionally violated in order to increase bandwidth efficiency. In analogy to conventional OFDM, signal generation relies on an Inverse Fractional Fourier Transform (IFRFT) that can be implemented with O(N log2 N) algorithmic complexity. Optimal Maximum Likelihood (ML) detection is overly complex due to the presence of substantial Intercarrier Interference (ICI). Consequently, we investigate an alternative detection mechanism based on the Generalized Sphere Decoding (GSD) algorithm. We examine the bandwidth efficiency and the error performance in Additive White Gaussian Noise (AWGN), for various FDM signal parameters. In particular, we show that it is possible to detect optimally and efficiently FDM signals, with 25% bandwidth gain with respect to analogous OFDM signals. This indicates that the transmission of spectrally efficient non orthogonal FDM signals is tangible.

A Spectral Model for RF Oscillators With Power-Law Phase Noise

In this paper, we apply correlation theory methods to obtain a model for the near-carrier oscillator power-spectral density (PSD). Based on the measurement-driven representation of phase noise as a sum of power-law processes, we evaluate closed form expressions for the relevant oscillator autocorrelation functions. These expressions form the basis of an enhanced oscillator spectral model that has a Gaussian PSD at near-carrier frequencies followed by a sequence of power-law regions. New results for the effect of white phase noise, flicker phase noise and random walk frequency modulated phase noise on the near-carrier oscillator PSD are derived. In particular, in the case of 1/f phase noise, we show that despite its lack of stationarity it is possible to derive a closed form expression for its effect on an oscillator PSD and show that the oscillator output can be considered to be wide-sense stationary

On the Resilience of Wireless Multiuser Networks to Passive and Active Eavesdroppers

Physical layer security can provide alternative means for securing the exchange of confidential messages in wireless applications. In this paper, the resilience of wireless multiuser networks to passive (interception of the broadcast channel) and active (interception of the broadcast channel and false feedback) eavesdroppers is investigated under Rayleigh fading conditions. Stochastic characterizations of the secrecy capacity (SC) are obtained in scenarios involving a base station and several destinations. The expected values and variances of the SC along with the probabilities of secrecy outages are evaluated in the following cases: (i) in the presence of passive eavesdroppers without any side information; (ii) in the presence of passive eavesdroppers with side information about the number of eavesdroppers; and (iii) in the presence of a single active eavesdropper with side information about the behavior of the eavesdropper. This investigation demonstrates that substantial secrecy rates are attainable on average in the presence of passive eavesdroppers as long as minimal side information is available. On the other hand, it is further found that active eavesdroppers can potentially compromise such networks unless statistical inference is employed to restrict their ability to attack. Interestingly, in the high signal to noise ratio regime, multiuser networks become insensitive to the activeness or passiveness of the attack.

Nonparametric Identification of Anisotropic (Elliptic) Correlations in Spatially Distributed Data Sets

Random fields are useful models of spatially variable quantities, such as those occurring in environmental processes and medical imaging. The fluctuations obtained in most natural data sets are typically anisotropic. The parameters of anisotropy are often determined from the data by means of empirical methods or the computationally expensive method of maximum likelihood. In this paper, we propose a systematic method for the identification of geometric (elliptic) anisotropy parameters of scalar fields. The proposed method is computationally efficient, nonparametric, noniterative, and it applies to differentiable random fields with normal or lognormal probability density functions. Our approach uses sample-based estimates of the random field spatial derivatives that we relate through closed form expressions to the anisotropy parameters. This paper focuses on two spatial dimensions. We investigate the performance of the method on synthetic samples with Gaussian and Matern correlations, both on regular and irregular lattices. The systematic anisotropy detection provides an important preprocessing stage of the data. Knowledge of the anisotropy parameters, followed by suitable rotation and rescaling transformations restores isotropy thus allowing classical interpolation and signal processing methods to be applied.

Joint channel equalization and detection of Spectrally Efficient FDM signals

This paper investigates the transmission in time dispersive channels of Spectrally Efficient Frequency Division Multiplexed (SEFDM) signals, where carrier orthogonality is intentionally violated in order to increase bandwidth efficiency. Sufficient statistics of the transmitted SEFDM signal can be obtained by projecting the received signal onto an orthonormal base generated at the receiver using an Iterative Modified Gram Schmidt (IMGS) procedure. In order to reduce the computational complexity resulting from Inter-Carrier Interference (ICI), detection has been implemented based on a Regularized Sphere Decoding (RSD) algorithm. The proposed scheme was previously tested in Additive White Gaussian Noise (AWGN) for various SEFDM signal parameters. In the present work, these results are extended to account for the effect of time dispersive channels. Randomly generated SEFDM symbols are used as pilots to provide estimates of the channel impulse response in systems with or without cyclic prefixes. A joint equalization-detection is subsequently performed in a RSD stage. We show that it is possible to detect optimally SEFDM signals of small dimensionality (e.g. N = 32), with up to 20% bandwidth gain with respect to OFDM systems of the same symbol-rate. This indicates that the wireless transmission of non orthogonal SEFDM signals is tangible.

On the effects of memoryless nonlinearities on M-QAM and DQPSK OFDM signals

In the design of RF up-conversion and down-conversion communication links, an issue of special interest is presented by the nonlinear characteristic of analog devices. In this paper, we deal with the effect of memoryless nonlinear distortion on orthogonal frequency-division multiplexing (OFDM) transceivers. We tackle the issue of calculation of the number of intermodulation products with methods from combinatorics theory and derive closed-form expressions for the signal-to-noise ratio (SNR). We deal with third-order nonlinearities alone though the methodology used can be extended to cover higher order nonlinear phenomena. We then proceed to deriving SNR expressions in the presence of a high adjacent channel of the same service and predict the generation of in-band tonal interference. Finally, we generalize to the case of a multichannel OFDM transceiver. In each case, bit-error-rate estimations for differential quadrature phase-shift keying and symbol-error-rate estimations for M-quadrature amplitude-modulation constellations are presented and a mapping between circuit characteristics and OFDM performance is outlined

Physical layer security in wireless networks with passive and active eavesdroppers

Security is becoming an increasingly important issue in wireless communications, to which physical layer approaches can contribute by providing addition resources for securing confidential messages. In this paper, the resilience of multi-user networks to passive and active eavesdropping is investigated. In particular, average secrecy capacities are evaluated in scenarios involving a base station and several terminals, some of which constitute passive or active eavesdroppers. Network resources (e.g. power) are allocated by the base station based on the available channel state information. The average secrecy capacity of such a network is evaluated in the following cases: (i) in the presence of passive eavesdroppers when no side information is available to the base station; (ii) in the presence of passive eavesdroppers with side information available; and (iii) in the presence of a single active eavesdropper with side information available. This investigation demonstrates that substantial secrecy rates are attainable in the presence of passive eavesdroppers as long as minimal side information, e.g. a statistical characterization of the number of potential eavesdroppers, is available to the base station. On the other hand, it is further found that active eavesdroppers can potentially compromise such networks unless statistical inference is employed to restrict their ability to attack.

A Fast Constrained Sphere Decoder for Ill Conditioned Communication Systems

This letter proposes a fast constrained sphere decoder for ill conditioned communications systems that exhibits less complexity than but similar performance to the generalised sphere decoder. The operational principle is based on i) the reduction of the search space by setting the hypersphere initial radius to be equal to the distance to a semidefinite program (SDP) estimate; and ii) the introduction of a heuristic pruning rule to limit the GSD spanning tree. The new algorithm achieves significant reduction in the required computational effort at the expense of a small error penalty for large dimensional systems in low signal to noise ratio (SNR) regimes.

Helping interferer physical layer security strategies for M-QAM and M-PSK systems

Physical layer security encompasses information theoretic approaches that could guarantee perfect secrecy in wireless communication systems. In this framework, helping interferer strategies rely on intentionally creating confusion at a potential eavesdropper by injecting a jamming signal. In cases where the information signal has a Gaussian probability density function (pdf) it has been demonstrated that the optimal jamming signal, under an overall power constraint, should also be Gaussian. However, in practical communication systems where data symbols are typically drawn from discrete uniform probability mass functions (pmf), commonly M-ary Quadrature Amplitude and M-ary Phase Shift Keying modulation schemes, the structure of the optimal jamming signal is still an open question. In the present work we aim at shedding light into this question. Our approach is based on formulating a secrecy capacity maximization problem by expressing the optimal arbitrary helping interferer pdf as a mixture of unknown Gaussians. The proposed approximation is well-suited for jamming signals of practical interest, i.e. Gaussian or M-QAM interferers and reveals that in certain scenarios it is advantageous to use jamming signals whose statistical structure resembles the data rather than the noise.

A multigrid method for the estimation of geometric anisotropy in environmental data from sensor networks

This paper addresses the estimation of geometric anisotropy parameters from scattered spatial data that are obtained from environmental surveillance networks. Estimates of geometric anisotropy improve the accuracy of spatial interpolation procedures that aim to generate smooth maps for visualization of the data and for decision making purposes. The anisotropy parameters involve the orientation angle of the principal anisotropy axes and the anisotropy ratio (i.e., the ratio of the principal correlation lengths). The approach that we employ is based on the covariance Hessian identity (CHI) method, which links the mean gradient tensor with the Hessian matrix of the covariance function. We extend CHI to clustered CHI for application in data sets that include patches of extreme values and clusters of varying sampling density. We investigate the impact of CHI anisotropy estimation on the performance of spatial interpolation by ordinary kriging using a data set that involves both real background radioactivity measurements and a simulated release of a radioactive plume.