Zaharias D. Zaharis

Bio: Zaharias D. Zaharis is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Antenna (radio) & Computer science. The author has an hindex of 17, co-authored 128 publications receiving 1179 citations. Previous affiliations of Zaharias D. Zaharis include Kongu Engineering College & Alexander Technological Educational Institute of Thessaloniki.

A Novel Adaptive Beamforming Technique Applied on Linear Antenna Arrays Using Adaptive Mutated Boolean PSO

Abstract: The present work introduces a new optimization technique suitable for adaptive beamforming of linear antenna arrays. The proposed technique is a new PSO variant called Adaptive Mutated Boolean PSO (AMBPSO) where the update formulae are implemented exclusively in Boolean form by using an e-ciently adaptive mutation process. The AMBPSO aims at estimating the excitation weights applied on the array elements considering that a desired signal and several interference signals are received by the array at respective directions of arrival. In order to exhibit the robustness of the technique, the optimization process does not take into account the interference correlation matrix. A certain power level of additive Gaussian noise is also considered by the technique. The AMBPSO has been applied in several cases of uniform linear antenna arrays with difierent spacing between adjacent elements and difierent noise power level and therefore seems to be quite promising in the smart antenna technology.

Design of a Novel Antenna Array Beamformer Using Neural Networks Trained by Modified Adaptive Dispersion Invasive Weed Optimization Based Data

Abstract: A new antenna array beamformer based on neural networks (NNs) is presented. The NN training is performed by using optimized data sets extracted by a novel invasive weed optimization (IWO) variant called modified adaptive dispersion IWO (MADIWO). The trained NN is utilized as an adaptive beamformer that makes a uniform linear antenna array steer the main lobe toward a desired signal, place respective nulls toward several interference signals, and suppress the side lobe level (SLL). Initially, the NN structure is selected by training several NNs of various structures using MADIWO-based data and by making a comparison among the NNs in terms of training performance. The selected NN structure is then used to construct an adaptive beamformer, which is compared to MADIWO-based and ADIWO-based beamformers, regarding the SLL and the ability to properly steer the main lobe and the nulls. The comparison is made, considering several sets of random cases with different numbers of interference signals and different power levels of additive zero-mean Gaussian noise. The comparative results exhibit the advantages of the proposed beamformer.

Thinned Planar Array Design Using Boolean PSO With Velocity Mutation

Abstract: The design of thinned planar microstrip arrays under specific constraints concerning the impedance-matching condition of the array elements and the radiation pattern is presented. The radiation characteristics of the structure are extracted by applying the method-of-moments. The array design is based on a novel optimization method, which is a modified version of the boolean particle swarm optimization that employs velocity mutation (BPSO-vm). Apart from the optimization of the array geometry, the proposed method is applicable to other discrete-variable optimization problems. Moreover, the planar array design is coped with by means of other techniques, namely, a binary coded Genetic Algorithm, the binary Particle Swarm Optimization, and the Boolean PSO. The comparison of the above methods and the BPSO-vm shows the efficiency of the proposed technique.

Improved Antenna Array Adaptive Beamforming with Low Side Lobe Level Using a Novel Adaptive Invasive Weed Optimization Method

Abstract: An improved adaptive beamforming technique of antenna arrays is introduced. The technique is implemented by using a novel Invasive Weed Optimization (IWO) variant called Adaptive Dispersion Invasive Weed Optimization (ADIWO) where the seeds produced by a weed are dispersed in the search space with standard deviation specifled by the fltness value of the weed. The adaptive seed dispersion makes the ADIWO converge faster than the conventional IWO. This behavior is verifled by applying both the ADIWO and the conventional IWO on well-known test functions. The ADIWO method is utilized here as an adaptive beamformer that makes a uniform linear antenna array steer the main lobe towards the direction of arrival (DoA) of a desired signal, form nulls towards the respective DoA of several interference signals and achieve low side lobe level (SLL). The proposed ADIWO based beamformer is compared to a Particle Swarm Optimization (PSO) based beamformer and a well known beamforming method called Minimum Variance Distortionless Response (MVDR). Several cases have been studied with difierent number of interference signals and difierent power level of additive zero-mean Gaussian noise. The results show that the ADIWO provides su-cient steering ability regarding the main lobe and the nulls, works faster than the PSO and achieves better SLL than the PSO and MVDR.

Comparison of Longley-Rice, ITU-R P.1546 and Hata-Davidson propagation models for DVB-T coverage prediction

Abstract: This paper compares precision field-strength measurements taken by a Rohde & Schwarz FSH-3 portable spectrum analyzer with simulation results derived from the ITM coverage prediction model (Irregular Terrain Model), also known as NTIA-ITS Longley-Rice model, in conjunction with the 3-arc-second SRTM (Satellite Radar Topography Mission) geographical data, the propagation predictions of ITU-R Recommendation P.1546 and those of the empirical Hata-Davidson model using HAAT. ITU-R P.1546 and Hata-Davidson models exhibit higher errors at longer distances and therefore necessary corrections should be introduced in the models in order to increase propagation prediction accuracy. Especially, measurements results show that ITU-R P.1546, on average, underestimates the field strength at distances longer than 50 km. The Longley-Rice model using the terrain digital elevations is more accurate, as expected, and its results are closer to the measurement data.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

American Society for Testing and Materials

Abstract: The American Society for Testing and Materials (ASTM) is an independent organization devoted to the development of standards.

A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions

Abstract: The fifth generation (5G) wireless network technology is to be standardized by 2020, where main goals are to improve capacity, reliability, and energy efficiency, while reducing latency and massively increasing connection density. An integral part of 5G is the capability to transmit touch perception type real-time communication empowered by applicable robotics and haptics equipment at the network edge. In this regard, we need drastic changes in network architecture including core and radio access network (RAN) for achieving end-to-end latency on the order of 1 ms. In this paper, we present a detailed survey on the emerging technologies to achieve low latency communications considering three different solution domains: 1) RAN; 2) core network; and 3) caching. We also present a general overview of major 5G cellular network elements such as software defined network, network function virtualization, caching, and mobile edge computing capable of meeting latency and other 5G requirements.

UAV Communications for 5G and Beyond: Recent Advances and Future Trends

Abstract: Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.