5G Based on Cognitive Radio

Both the cognitive radio (CR) and the fifth generation of cellular wireless standards (5G) are considered to be the future technologies: on one hand, CR offers the possibility to significantly increase the spectrum efficiency, by smart secondary users (CR users) using the free licensed users spectrum holes; on the other hand, the 5G implies the whole wireless world interconnection (WISDOM—Wireless Innovative System for Dynamic Operating Megacommunications concept), together with very high data rates Quality of Service (QoS) service applications. In this paper, they are combined together into a “CR based 5G”. With this aim, two novel ideas are advanced: the 5G terminal is a CR terminal and the CR technology is chosen for WISDOM concept. Thus, the 5G takes CR flexibility and adaptability and makes the first step through a commercial and tangible form.     

Single step synthesis of GdAlO3 powder

A novel method for preparation of nano-crystalline gadolinium aluminate (GdAlO₃) powder, based on combustion synthesis, is reported. It was observed that aluminium nitrate and gadolinium nitrate exhibit different combustion characteristics with respect to urea, glycine and β-alanine. While urea was proven to be a suitable fuel for direct formation of crystalline α-Al₂O₃ from its nitrate, glycine and β-alanine are suitable fuels for gadolinium nitrate for preparation of its oxide after combustion reaction. Based on the observed chemical characteristics of gadolinium and aluminium nitrates with respect to above mentioned fuels for the combustion reaction, the fuel mixture composition could be predicted that could lead to phase pure perovskite GdAlO₃ directly after the combustion reaction without any subsequent calcination step. The use of single fuel, on the other hand, leads to formation of amorphous precursor powders that call for subsequent calcination for the formation of crystalline GdAlO₃. The powders produced directly after combustion reactions using fuel mixtures were found to be highly sinterable. The sintering of the powders at 1550 °C for 4 h resulted in GdAlO₃ with sintered density of more than 95%. T.D.     

Adaptive epileptic seizure prediction system

Current epileptic seizure "prediction" algorithms are generally based on the knowledge of seizure occurring time and analyze the electroencephalogram (EEG) recordings retrospectively. It is then obvious that, although these analyses provide evidence of brain activity changes prior to epileptic seizures, they cannot be applied to develop implantable devices for diagnostic and therapeutic purposes. In this paper, we describe an adaptive procedure to prospectively analyze continuous, long-term EEG recordings when only the occurring time of the first seizure is known. The algorithm is based on the convergence and divergence of short-term maximum Lyapunov exponents (STLmax) among critical electrode sites selected adaptively. A warning of an impending seizure is then issued. Global optimization techniques are applied for selecting the critical groups of electrode sites. The adaptive seizure prediction algorithm (ASPA) was tested in continuous 0.76 to 5.84 days intracranial EEG recordings from a group of five patients with refractory temporal lobe epilepsy. A fixed parameter setting applied to all cases predicted 82% of seizures with a false prediction rate of 0.16/h. Seizure warnings occurred an average of 71.7 min before ictal onset. Similar results were produced by dividing the available EEG recordings into half training and testing portions. Optimizing the parameters for individual patients improved sensitivity (84% overall) and reduced false prediction rate (0.12/h overall). These results indicate that ASPA can be applied to implantable devices for diagnostic and therapeutic purposes.     

HEALTH Growth with Active Transformation of Mind and Body Through Abundant Natural Methods

Wireless Personal Communications - The ongoing technological developments have totally transformed the lives of human beings. With the emergence of the smart era and the smart city concept, a few...     

Energy-Efficient and Improved eWALL: e2WALL

eWALL framework, under development in the European eWALL project (project no. 610658: “eWALL for Active Long Living”) is meant for care of population with age related impairments, mild dementia and COPD. Expanded eWALL (e2WALL) is planned to be an integrated quality framework for long-term care services which will cover very different types of care: all healthcare (both preventive and rehabilitative), societal services, care for cognitive diseases, services delivered at home as well as support for caregivers as an integral part of the quality improvement process. Thus, we present e2WALL home system that would encompass installation (setup) of e2WALL in homes (flats, houses and aging homes) and their management and maintenance across Europe, starting from the partners involved in eWALL (Austria, Bulgaria, Croatia, Denmark, Former Yugoslav Republic of Macedonia, Germany, Greece, Italy, Montenegro, The Netherlands and Romania) and expanding the partnership to the most of Europe (e.g. United Kingdom, Poland, Czech Republic…). This would be a direct application of the developed e2WALL platform and should be done through a network of collaborating small-to-medium sized enterprises (SMEs), each of whom would lead the process of setting up e2WALL system and continuing to provide support services to homes in their respective country. In this way, the growth of high tech and innovative SMEs will be ensured at pan European level, which will enable growth over restricted national market and stimulate European investments in SMEs and startups. Actually, the bigger platform will enable e2WALL European Ecosystem (e4WALL), which can then expand into other non-European markets (e.g. Asia, USA) and means sustainability beyond the life of the project. e2WALL will lead to connected tech start-up hubs to the larger European business ecosystem and will contribute to increased access of country-specific and customized new product to the pan European market, which will lead to increase of employed qualified individuals. Another important focus would be creating an energy efficient environment for a new social network where registered users would provide on-demand services.     

Two Tier Cluster Based Data Aggregation (TTCDA) for Efficient Bandwidth Utilization in Wireless Sensor Network

Wireless Sensor Networks are often used for monitoring and control applications where sensor nodes collect data and send it to the sink. Direct transmission of data packets to the sink from nodes in the network causes increased communication costs in terms of energy, network lifetime and bandwidth utilization. In this context, this paper proposes Two Tier Cluster-based Data Aggregation (TTCDA) algorithm for the randomly distributed nodes in the network to minimize computation and communication cost. The TTCDA effectively considers the packet and data aggregation using additive and divisible aggregation functions at cluster head and sink. The aggregation functions are applied according to spatial and temporal correlation of packets and data generated by each node. It also prevents transmission of redundant data by improving energy consumption and bandwidth utilization as compared with state-of-the-art solution. The performance of the algorithm is validated using examples and simulations. Also, it is seen that packet aggregation in TTCDA is better for the bandwidth utilization as it reduces average energy consumption by 3.13 % as compared to data aggregation.     

Multivariate ARMA modeling by scalar algorithms

An algorithm for multichannel autoregressive moving average (ARMA) modeling which uses scalar computations only and is well suited for parallel implementation is proposed. The given ARMA process is converted to an equivalent scalar, periodic ARMA process. The scalar autoregressive (AR) parameters are estimated by first deriving a set of modified Yule-Walker-type equations and then solving them by a parallel, order recursive algorithm. The moving average (MA) parameters are estimated by a least squares method from the estimates of the input samples obtained via a high-order, periodic AR approximation of the scalar process     

Effects of Rician faded and log-normal shadowed signals on spectrumefficiency in microcellular radio

An assessment of spectrum efficiency for a microcellular land mobile radio system is presented by considering the desired signal as (fast) Rician fading with (slow) log-normal shadowing and cochannel interfering signals as uncorrelated (fast) Rayleigh fading superimposed over (slow) log-normal shadowing. Spectrum efficiency is defined in terms of reuse distance, i.e., cluster size, traffic intensity, bandwidth of the system, and area of a cell by considering cochannel interference probability. The expression for cochannel interference probability is derived using appropriate path-loss law for microcells for four different cases: Rician plus log-normal desired signal and Rayleigh plus log-normal interfering signals; Rician desired signal and Rayleigh fading plus log-normal shadowing interfering signals; Rician desired signal and Rayleigh interfering signals; and both desired and interfering signals as Rician fading. The performance of a microcellular system is compared with that of a conventional macrocellular system