Future 5G wireless communication systems: A new multicarrier shemes

Current wireless communication networks and technologies are being pushed to their limits by the massive growth in demands for mobile wireless data services. We now stand at a turning point in the wireless communication domain where the technologies are being driven by applications and expected use cases. This paper presents an overview on the drivers behind the 5G evolution and presents the new waveforms candidates for future generation network; the FBMC for filter bank multicarrier and UFMC for Universal filtered multi carrier are a potential concept for 5G and replacing the famous multicarrier modulation OFDM used in different technologies 4G. So there is a new way for the 5G transition expected beyond 2020

Filter Bank based Multi-Carrier Systems in 5G Network

Most current fourth generation wireless systems use OFDM modulation technique. The success of the multi-carrier OFDM technology lies in the many benefits they offer. OFDM is robust against multipath effects, provides good spectral efficiency and better use of frequency resources compared to other conventional multi-carrier modulations. However, OFDM has some major drawbacks as a loss of spectral efficiency due to the insertion of the guard interval, a very high level of side lobes causing leakage of power between different subcarriers. OFDM technology will then be abandoned in favor of multi-carrier technology based filter bank called FBMC (Filter Bank Multicarrier). Through this article, we will see the Filter Bank multi-carriers (FBMC) based on theory of filter bank, and then we will look at FBMC/ OQAM technical, probably the most popular among FBMC techniques used in context of 5G wireless communication systems

Geometry based Optimization for inductively coupled spiral coils

Efficiency of inductive linking is an essential part in wireless power transfer WPT. In this paper, we propose an optimization to increase the efficiency of the system and reduce the size of coupled spiral coils implementable microelectronic devices based on geometrical characteristics. Moreover, an elimination of the splitting frequencies is achieved. The proposed approach provides much better results comparing error rates between the optimal mutual inductance and the mutual inductance obtained using calculated geometrical parameters of coils

Validation de quelques modèles spectraux pour la détermination du spectre solaire au sol en Algérie

In this work, we draw on the methodological approaches of the spectral models developed by Bird & Riordan and Leckner to compute the spectral components of solar radiation on the ground for different catch surface tilts. The main objective remains to make available to researchers and designers of solar energy systems, especially Algerian, a numerical tool for calculating the spectral components of solar radiation integrating different atmospheric conditions. The spectra thus obtained will make it possible to examine the spectral selectivity performances of photovoltaic devices varying a set of input parameters such as air mass, atmospheric turbidity and water vapor as well as the day of the year

Robust decentralized proof of location for blockchain energy applications using game theory and random selection

To combat the problem of illegal access to a service, several location proof strategies have been proposed in the literature. In blockchain-based decentralized applications, transactions can be issued by IoT nodes or other automated smart devices. Key pair encryption and private key signing have been defined mainly for human identification in blockchain applications, where users are personally and responsibly concerned about the confidentiality of their private key. These methods are not suitable for computing nodes whose private key is implemented in the software they run. Ensuring that transactions are issued by a legitimate sender with the proper credentials is a bigger concern in applications with financial stakes. This is the case with blockchain energy trading platforms, where prosumers are credited with tokens in exchange for their contributions of energy. The tokens are issued by smart meter nodes installed at fixed locations to monitor the energy inputs and outputs of a given prosumer and claim energy tokens on its behalf from a defined smart contract in exchange for the energy it feeds into the grid. To this end, we have developed a decentralized Proof-of-Location (PoL) system tailored to blockchain applications for energy trading. It ensures that automated transactions are issued by the right nodes by using smart contract-based random selection and a game-theoretic scenario suitable for blockchain energy trading

Energy harvesting effect on prolonging low-power lossy networks lifespan

Low-power lossy networks performance relies heavily on the wireless node battery status. Furthermore, Routing Protocol for Low-Power and Lossy Network routing protocol was not optimally designed with sustainable energy consumption in mind to suit these networks. Prolonging the lifespan of these networks is of utmost priority. This article introduces a solar energy harvesting module to power energy-constrained network devices and quantifies the effect of using harvested energy on prolonging their network lifetime when Routing Protocol for Low-Power and Lossy Network routing protocol is used. Simulation of the new developed module is conducted in three different scenarios using Contiki Cooja simulator sporting Zolertia Z1 motes. Furthermore, the harvested energy used was fed from a Cooja-based Simulation model of actual PV supercapacitor circuit design. All battery levels were set to 1% of their total capacity for all nodes in the network to speed up observing the energy harvesting effect. The performance evaluation results showed that the network with no-energy harvesting operated for time duration of 4:08:04 time units (i.e. hour:minute:second) with a dramatic decrease in connection between nodes in the network. However, the same network, when using the harvested energy to back up the battery operation, lasted for 6:40:01 in time units with improved connectivity, a total extended network lifetime of 2:31:97-time units. Furthermore, for the Routing Protocol for Low-Power and Lossy Network routing metrics, OF0 outperformed ETX in term of throughput, packet delivery ratio, energy consumption, and network connectivity. Results indicate that the developed harvested energy module fits perfectly for any Cooja-based simulation and mimics actual photovoltaic-based supercapacitor battery. It should also help researchers introduce and quantify accurately new energy consumption-based routing metrics for Routing Protocol for Low-Power and Lossy Network

A novel PTS based PAPR reduction scheme for FBMC-OQAM system without extra bits transmission of SI

In this paper, a Novel Partial Transmit Sequence-based scheme is proposed, namely (N-PTS). The aim is to solve the major hindrance of high Peak to Average Power Ratio (PAPR); as well as to combat the overlapping structure issue affecting Filter Bank Multicarrier system based on the Offset Quadrature Amplitude Modulation (FBMC-OQAM). On that note, computational complexity is also reduced. The proposed scheme uses FBMC-OQAM signal in the frequency domain. To this end, the lowest PAPR value is calculated from data located in a Storage Device (SD). Accordingly, it is properly identified through its location referred to as ’Row’ which consists of the Side Information (SI) to recover the original signal at the receiver. As a result, a substantial reduction in PAPR and computational complexity are achieved. Finally, it is found necessary to mention that SI is claimed not to require extra bits to be transmitted, using phase offset with Minimum Euclidian Distance (MED) criterion, while the Bit Error Rate (BER) performance remains very satisfactory

Partial Transition Sequence Algorithms for Reducing Peak to Average Power Ratio in the Next Generation Wireless Communications Systems

The unprecedented scientific and technical advancements along with the ever-growing needs of humanity resulted in a revolution in the field of communication. Hence, single carrier waves are being replaced by multi-carrier systems like Orthogonal Frequency Division Multiplexing (OFDM) and Generalized Frequency Division Multiplexing (GFDM) which are nowadays commonly implemented. In the OFDM system, orthogonally placed subcarriers are used to carry the data from the transmitter to the receiver end. The presence of guard band in these systems helps in dealing with the problem of intersymbol interference (ISI) and noise is minimized by the larger number of subcarriers. However, the large Peak to Average Power Ratio (PAPR) of these signals has undesirable effects on the system. PAPR itself can cause interference and degradation of Bit Error Rate (BER). To reduce High Peak to Average Power Ratio and Bit Error Rate problems, more techniques are used. Furthermore, each technique has its own disadvantages, such as complexity in-band distortion and out-of-band radiation into OFDM and GFDM signals. In this paper, the emphasis will be put on the GFDM systems as well as on the methods that are meant to reduce the PAPR problem and improve efficiency

Extending CloudSim to simulate sensor networks

With the enormous growth of sensing devices tending to the use of Internet of everything, data aggregated by these devices are the biggest data streams generated in the history of IT. Thus, aggregating such data in the cloud for leveraging powerful cloud computing processing and storage is essential, and it eventually led to the emergence of Sensor-Cloud concept. This has allowed aggregation of the sensors’ data to the cloud for further processing, storage, and visualization. Furthermore, virtualization makes the sensors accessible to other end-user applications that require such data. All of these features are expected to be provided by the Sensor-Cloud invisibly, without the end-user application developer being aware of the sensor location or hardware specifications. For these reasons, a simulation platform where Sensor- Cloud infrastructure agents and components may be modeled, scheduling policies defined, and execution time assessed is essential to assure performance and quality of service. The aim of this study is to develop such a platform by enhancing CloudSim, the most well-known and powerful simulation tool for cloud computing. A user-friendly Java Script Swingbased graphical user interface (GUI) has been carefully designed and implemented for this purpose. The user can then utilize the specific interface to define the Cloudlet type as well as the scheduling on a single virtual machine. Finally, a simulation study is carried out on the platform to demonstrate its efficiency and accuracy. We were able to fully model the needed scenarios and acquire real-time results, displaying good accuracy in terms of application response time with a mean absolute percentage error (MAPE) of 3.37%, demonstrating the increased proposed platform’s proper operation

Fully decentralized, cost-effective energy demand response management system with a smart contracts-based optimal power flow solution for smart grids

Recent advances in control, communication, and management systems, as well as the widespread use of renewable energy sources in homes, have led to the evolution of traditional power grids into smart grids, where passive consumers have become so-called prosumers that feed energy into the grid. On the other hand, the integration of blockchain into the smart grid has enabled the emergence of decentralized peer-to-peer (P2P) energy trading, where prosumers trade their energy as tokenized assets. Even though this new paradigm benefits both distribution grid operators and end users in many ways. Nevertheless, there is a conflict of interest between the two parties, as on the one hand, prosumers want to maximize their profit, while on the other hand, distribution system operators (DSOs) seek an optimal power flow (OPF) operating point. Due to the complexity of formulating and solving OPF problems in the presence of renewable energy sources, researchers have focused on mathematical modeling and effective solution algorithms for such optimization problems. However, the control of power generation according to a defined OPF solution is still based on centralized control and management units owned by the DSO. In this paper, we propose a novel, fully decentralized architecture for an OPF-based demand response management system that uses smart contracts to force generators to comply without the need for a central authority or hardware