A reconfigurable dual port antenna system for underlay/interweave cognitive radio

An antenna system that is reconfigurable in frequency is presented in this paper as a novel dual port design that serves both undelay and interweave cognitive radio. This 25×40×0.8 mm3 system is composed of two wide slot antennas: the first is designed as an ultra-wideband (UWB) antenna with controllable band rejection capabilities, while the second antenna is reconfigurable for communication purposes. Three slots are etched into the patch of the UWB antenna to obtain band notching in wireless local area network/Xband/International Telecommunication Union bands (WLAN/Xband/ITU) bands which can be controlled by a positive-intrinsic-negative (PIN) diode across each slot. The configuration states of these three diodes are all useable that produces seven band rejection modes plus the UWB operation mode. The second antenna is configured by five PIN diodes to operate either in Cband, WLAN or Xband regions which results in three interweave modes when setting the first antenna for UWB sensing. The design is simulated by computer simulation technology (CST) v.10. S21 results shows good isolation while input reflection coefficient and realized gain results prove system’s scanning, filtering and communication capabilities. This system is new that it gathers the undelay/interweave operation in a single design and when considering its large number of operation modes it looks adequate for many cognitive radio applications

DESIGN OF A DUAL-BAND REJECTION PLANAR ULTRA-WIDEBAND (UWB) ANTENNA

A novel Slotted-Decagon-Shaped (SDS) antenna is presented for Ultra Wide Band (UWB) applications. This antenna has two slots; the first one is printed on the lower side, and the second on the upper side of the conducting patch. The feeding technique used to feed this antenna is a 50Ω strip line. Return losses, bandwidth, radiation pattern, and, gain of the presented SDS antenna are tested. These characteristics denote it fitting for UWB wireless communication systems. The SDS antenna was fabricated and tested at the laboratories of the Iraqi-ministry of science and technology and the result shows a fine agreement between simulation and measured S11. The SDS antenna has a compact size of 19.3mm×36mm×1.6mm. Measured results show that the SDS antenna has favorable properties of S11 less than −10 dB and a quasi-stable gain of 2 to 4.5 dB over UWB, with the exception of the notched WiMAX (3.3-3.7 GHz) & WLAN (5.1-5.8 GHz) bands

Investigation of the Effect Different Antenna parameters (Height, Tilt, and Power) on Network Coverage and System Capacity

The, prospective of radio, mobile network, topology planning, would be to, provide a configuration, that offers the, necessary coverage, several services, as well as, simultaneously, enhances the system, coverage and capacity. This work, addresses the effect, of antenna height, antenna, tilt and  power,  on network, and network capacity. Furthermore, the effects of the above mentioned elements had been investigated using MATLAB program. Appropriately the goal of the actual investigation is always to have because high signal strength as is possible in the area in which the cell ought to be serving  traffic. Beyond the particular serving part of the cell, typically the signal power should be low so as to fight the problem associated with fluctuation within received sign strength through the mobile customers in a cellular. Results of often the investigation display that greatest coverage is actually obtained in 38m elevation, 46dB strength and 2° tilt

Improving Mobile Location Prediction Using the Grey Wolf Optimization Algorithm

The importance of locating a mobile phone has increased significantly during last decade for security and commercial reasons. Locating the mobile phone leads to locating people. This is done by using the most common propagation models in the mobile phone network design to calculate the distance between the mobile phone and the base station, in addition to using positioning algorithms to predict the location of the mobile station. In this work, three telecommunication towers that provide mobile phone service for Zain Iraq were selected, located within the Mahmudiya area in Baghdad as a case study, and a test drive was conducted to measure the signal strength received from these base stations at more than 10 points located within the coverage area of these base stations. The Okumura-HATA model, and the UMTS propagation model were used to calculate the distances. The Gray-Wolf algorithm was used to improve mobile phone position prediction

Enabling Deep Learning and Swarm Optimization Algorithm for Channel Estimation for Low Power RIS Assisted Wireless Communications

In this study, convolutional neural networks (CNN) and particle swarm optimization are used to offer a channel estimate technique for low power reconfigurable intelligent surface (RIS) assisted wireless communications (PSO). The suggested approach makes use of the RIS channels' sparsity to lower the CNN model's training complexity and uses PSO to optimize the CNN model's hyperparameters. The proposed system has been trained using 70% of dataset, 25% of data was used for testing and remaining 5% was used for cross-validation. In comparison to previous methods, simulation results demonstrate that the proposed method delivers correct channel estimate with much less computing cost. The suggested technique also exceeds current techniques in terms of bit error rate (BER) and mean squared error (MSE) performance. The research found 96.47% and 90.96% of accuracy for CNN and PSO algorithm respectively. Moverover, the network was trained using a dataset mentioned in methodology section for channel realizations, and achieved a mean squared error (MSE) value of 0.012 using CNN algorithm. Also, the study reported the proposed technique outperformed other state-of-the-art techniques. The proposed technique of PSO to optimize the channel estimation, and achieved a mean squared error (MSE) value of 0.0075

Design and Implementation Unit Cell for 6G Reconfigurable Intelligent Surface Application

This article presents a model through which the reflection coefficient amplitude as well as phase of reflective intelligent surfaces can be estimated accurately. The reconfigurability of the surface was achieved by incorporating the varactor diodes into the surface of the cell unit. The manipulation of the phase of the reflection coefficient can be achieved by making adjustments to the biasing state of the varactors. The model, which makes use of a physics-based methodology and is based on a transmission-line circuit description of the Reconfigurable Intelligent surfaces (RIS) unit cells, considers every pertinent electrical and geometrical characteristics of the proposed surface. With the method proposed in this paper, fast and accurate RIS-based communication lines can be created. The recommended accuracy of the proposed method was confirmed through the use of a CST microwave studio full-wave simulations