Andreas M. Maras

A Bayesian State–Space Approach to Combat Inter-Carrier Interference in OFDM Systems

Orthogonal frequency division multiplexing (OFDM) is an emerging multi-carrier modulation scheme, which has been adopted for several wireless standards such as IEEE 802.11a and HiperLAN2. A well-known problem of OFDM is its sensitivity to frequency offset between the transmitted and received carrier frequencies. This frequency offset introduces inter-carrier interference (ICI) in the OFDM symbol. In this letter, we investigate two methods for combating the effects of ICI: the extended Kalman filter (EKF) method and a form of the sequential Monte Carlo (SMC) method called sequential importance sampling (SIS). Through simulations, we explore the efficiency of these two methods for various frequency offsets and different signal-to-noise ratios (SNRs). Our estimates of the frequency offset are very satisfactory, especially in the latter case, resulting in performance improvement of the OFDM modulation scheme.

On the Correlated

The correlated bivariate K-distribution with arbitrary and not necessarily identical parameters is introduced and analyzed. Novel infinite series expressions for the joint probability density function and moments are derived for the general case where the associated bivariate distributions, i.e., Rayleigh and gamma, are both arbitrary correlated. These expressions generalize previously known analytical results obtained for identical parameter cases. Furthermore, considering independent gamma distributions, the cumulative distribution and characteristic functions are analytically obtained. Although the derived expressions can be used in a wide range of applications, this letter focuses on the performance analysis of dual branch diversity receivers. Specifically, the outage performance of dual selection diversity receivers operating over correlated K fading/shadowing channels is analytically evaluated. Moreover, for low normalized outage threshold values, closed-form expressions are obtained.

K

Secrecy capacity is a fundamental information-theoretic performance metric to predict the maximum data rate of reliable communication, while the intended message is not revealed to the eavesdropper. Motivated by this consideration in this paper, a unified communication-theoretic framework for the analysis of the probability of nonzero secrecy capacity, the secrecy outage probability, and the secrecy capacity of multiple-antenna systems over fading channels is proposed. Specifically, a powerful frequency-domain approach is first developed in which the integrals involved in the evaluation of the probability of nonzero secrecy capacity and secrecy outage probability are transformed into the frequency domain, by employing Parsevals theorem. A generic approach for the evaluation of the asymptotic secrecy outage probability at high signal-to-noise ratio (SNR) region is also introduced, thus providing useful insight as to the parameters affecting the secrecy performance. Finally, a unified numerical approach for computing the average secrecy capacity of multiple-antenna systems under arbitrary fading environments is developed. The proposed framework is general enough to accommodate any well-known multiantenna transmission technique and fading model. Finally, the secrecy performance of several multiple-antenna system setups is assessed, in the presence of generalized fading conditions and arbitrary antenna correlation, while various numerical and computer simulation results are shown and compared to substantiate the proposed mathematical analysis.

-Distribution With Arbitrary Fading Parameters

The circular cylindrical antenna is a simple, inexpensive, versatile, and very popular antenna type, which has received much attention due its wide range of applications. The exact values of the radiated near and far electromagnetic fields have recently been analytically evaluated, in terms of complex series involving Legendre functions of the second kind and half-integral order. The inverse problem of determining the loop antenna parameters (radius and current) causing specific field levels at one or more points of interest is even more complex. In order to find the solution, avoiding the associated lengthy and time-demanding mathematical analysis, we apply artificial neural network modeling. The proposed models consist of a feedforward back-propagation and a radial basis neural network trained with theoretical data. The results obtained are found to be in perfect agreement with the exact theoretical data.

Physical Layer Security for Multiple-Antenna Systems: A Unified Approach

Orthogonal frequency division multiplexing (OFDM) is a multi-carrier modulation scheme, which has been adopted for several wireless standards. In order to fully exploit the benefits of an OFDM system, estimation of the channel state information must be performed. Moreover a well-known problem of OFDM is its sensitivity to frequency offset between the transmitted and received carrier frequencies. This frequency offset introduces inter-carrier interference in the OFDM signal. In this paper we address the problem of jointly tracking the channel and frequency offset based on a Sequential Monte Carlo filtering approach. The proposed algorithm works in a decision-directed way, thus does not require the use of pilot symbols, providing a worth-mentioned increase in the useful data rate. Through simulations we demonstrate the efficiency of this approach against a similar approach where the Extended Kalman Filter is used. Moreover our method is compared with two recently proposed pilot-based methods.

Neural network solution of the circular loop antenna radiation problem

This work presents an alternative method, based on artificial techniques, to manipulate the direct and inverse problems of circular loop antenna radiation, using data extracted from their analytical solutions. The adaptive network fuzzy inference system (ANFIS) has been used, as a basis for constructing a set of fuzzy rules with appropriate membership functions in order to obtain the theoretical data. The numerical results for both problems are found to be in excellent agreement with the exact theoretical values.

Blind Sequential Monte Carlo Joint Tracking of Channel State and Frequency Offset in OFDM Systems

In this paper we address the problem of joint tracking the channel state and the multiple frequency offsets in MIMO-OFDM systems based on a Sequential Monte Carlo filtering approach. In contrast to most of the existing approaches, a separate frequency offset for each MIMO branch is considered and furthermore the proposed tracking procedure is blind.

Solving the inverse loop antenna radiation problem using a hybrid neuro-fuzzy system

This paper deals with the effect of the Doppler spread in a mobile communication system. The Doppler effect in a moving mobile is computed by predicting the mobile velocity via particle filtering, an instance of Sequential Monte Carlo (SMC) filtering. By calculating the Doppler spread in the receiver and adjusting the transmitter in the appropriate frequency, the performance of communication systems, such as Orthogonal frequency division multiplexing (OFDM) which suffer from loss of orthogonality due to frequency offset, can be improved. Moreover, it is shown that, via performance comparison of OFDM between the compensated and un-compensated for Doppler shift cases, a substantial improvement (O(10−1)) can be achieved in terms of Bit-Error-Rate (BER) for expectedly large values of Signal to Noise Ratio (SNR)