Algorithm to Enhance Radio Wave Propagation Strength

Algorithm to Enhance Radio Wave Propagation military unitA New Algorithm to Enhance Radio Wave Propagation Strength in Dead Spots for Cellular Mobile WiFi Downloads exercise Cloud NetworksSignal going away is a major problem for cellular radio devices, resulting in dropped calls and failure in downloading data. Our research uses a combination of contrastive interaction perplexs to provide an easy interface to replace traditional control methods for maintaining signal levels. The lossy WiFi wave university ex 10sion around and within buildings is analyse utilizing college buildings at the University of Bridgeport (UB) campus in Bridgeport CT. These buildings serve as good experimental settings because they exemplify typical signal dead spots, locations where little to no WiFi signal is available. In this paper, we investigate path loss propagation inside and outside buildings and we identify and categorize these problems. We then apply our path loss propagation algorithmic m odels to immortalize that signal strength is significantly improved when compared to existing algorithms. Finally, we show the efficiency of our model and explain the specifics of our algorithm.Cellular Mobile Communication keeps growing so desist on the market worldwide so that they become our everyday companions. Over the last twenty years, globally, Mobile Communication users have raised a specifically rich multimedia service which forces telecommunication vendors as well as the operators to set significant efforts in order to fulfill clients needs. The use of Wi-Fi for internet is widely increasing especially in mobile devices where Wi-Fi enabled, which gives results in expanding hotspots, and user acceptance also grows. Cisco Visual Networking Index (VNI) presented its research intimately global mobile data traffic, and VNI research indicated that this traffic will increase 18-fold from 2011 to 2016, and will reach 10.8 exabytes per month. Recent technologists and mobile ind ustries never viewed the roles for Wi-Fi in the new phones networks. The changes in the mobile and the offloading data traffic to Wi-Fi can and it plays the significant role to avoid clogged networks are realized by mobile operators 12. From all these we conclude that the chance on component of the information security is the data transfer and its daily importance in our life. Wireless Local Area Networks (wireless local area network) gained high acceleration, the reason of the demand to pre-evaluate signals that are transmitted under Line-of-Sight (LOS) and /or none (NLOS) radio wave propagation in the indoor environments. These transmissions have main problem which is the difficulty to foretell indoor radio wave propagations because of the invisibility between the transmitter and the receiver 15.Related workYuko MIURA, et. al. 1 proposed a propagation model which accu commitly predicts outdoor-to-indoor propagation loss this model depends on the angle dependency of the losses w ith the paths that penetrate the indoor area. Radio waves transmitted from the base pose first propagate outdoors to the buildings external wall. Next, the radio waves penetrate the structures external wall. Last, the penetration waves propagate inside the building for the receiver. Outdoor-to-indoor propagation loss is estimated by predicting the propagation losses of those three parts. The losses of those three propagation processes might be calculated individually, and the path loss between base station and mobile station is usually expressed since the amount of these losses in dB 1. Greg Durgin et. al. 2 developed measurement-based path loss for propagation prediction these measurements aided the development of outdoor-to-indoor communication systems for wireless internet access, wireless cable distribution, and wireless local loops. Iskandar et. al. 3 evaluated the propagation loss as a function of elevation and azimuth angels, and observed the link work out in the estimation to the required transmitted power at several transmission rates of IMT-2000. Gerd Wlfle et. al. 4 proposed a new concept called dominant model in which focuses on the dominant paths between transmitter and receiver for the planning of wireless networks. 4 Prepared a comparison between cellular or WLAN in urban considering indoors either direct ray or ray tracing propagation and urban city centers in multi-floor buildings. Oliver Stbler et. al. 5 presented a deterministic approach for the evaluation of 3GPP Long Term Evolution (LTE) networks in urban and indoor, beside evaluated the signal levels in the expected MIMO capacity. N. Faruk et. al. 6 conducted measurements at 203.25 MHz and 583.25 MHz frequencies along ten routes in Ilorin City, in order to fit the measured data with lognormal propagation loss, 6 used least square regression method, and investigated the behavior of the TV signals in the similar environment in building penetration loss across the routes. doubting Thomas Schwengler, et. al. 7 presented propagation at 5.725 GHz 5.825 GHz within the U.S Unlicensed National cultivation Infrastructure (U-NII) band. Measured propagation path loss in a residential area at 5.8 GHz. Separated the data sets into line of fortune (LOS) and non-line of sight (NLOS), as much as obtained noteworthy results since propagation models were designed for cellular and PCs use at lower frequency and narrow-band channels. Sheryl L. Howard et. al. 8 presented the use of error-control coding (ECC) which used in wireless sensor networks (WSNs) in order to determine the energy efficiency of ECC in WSNs. As much as derived an expression for critical maintain dCR, where the decoders energy consumption per bit equals the transmit energy savings per bit, also showed that in crowded environments and office buildings dCR dropped significantly to 3m or greater at 10 GHz without considering the interference. Alyosha Molnar, et. al. 9 presented 900 MHz, ultra-low power RF transcei ver for wireless WSNs, and demonstrated them to communicate over 16 meters through walls at a bit rate of 20 kbps. Jun Wang et. al. 10 used an adaptive back-off strategy to achieve fairly uniform cluster head distribution across the network.ReferencesYuko MIURA, Yasuhiro ODA, and Tokio TAGA, Outdoor-To-Indoor Propagation Modeling with The designation of Path Passing Through Wall Openings, Wireless Laboratories, NTT DoCoMo, Inc. 3-5 Hikari-no-oka, Yokosuka-shi, Kanagawa, 239-8536, Japan, 0-7803-7589-0/02/$17.00 2002 IEEE.Greg Durgin, Theodore S. Rappaport, Hao Xu, Measurements and Models for Radio Path Loss and Penetration Loss In and Around Homes and Trees at 5.85 GHz, IEEE Transactions on communication theory, Vol. 46, No. 11, November 1998.Iskandar and Shigeru Shimamoto, foresight of Propagation Path Loss for Stratospheric Platforms Mobile Communications in Urban Site LOS/NLOS Environment, pp. 5643-5648, 1-4244-0355-3/06/$20.00 (c) 2006 IEEE.Gerd Wlfle, Ren Wahl, Pascal Wildbol z, and Philipp Wertz, Dominant Path Prediction Model for Indoor and Urban Scenarios, AWE Communications GmbH, Otto-Lilienthal-Str. 36, 71034 Boeblingen, Germany, www.awe-communications.com.Oliver Stbler, Reiner Hoppe, Gerd Wlfle, Thomas Hager, Timm Herrmann, Consideration of MIMO in the Planning of LTE Networks in Urban and Indoor Scenarios, AWE Communications GmbH Otto-Lilienthal-Strae 36, 71034 Bblingen, Germany.N. Faruk, A. A. Ayeni, Y. A. Adediran, Characterization Of Propagation Path Loss at VHF/UHF Bands for Ilorin City, Nigeria, Nigerian Journal of Technology (NIJOTECH) Vol. 32. No. 2. July 2013, pp. 253-265Copyright Faculty of Engineering, University of Nigeria, Nsukka, ISSN 1115-8443. www.nijotech.com.Thomas Schwengler, and Mike Gilbert, Propagation Models at 5.8 GHz Path Loss Building Penetration, U S WEST Advanced Technologies, Boulder, CO 80303. Tel. e-mail respectively 303-541-6052, emailprotected and 303-541-6257, emailprotected.Sheryl L. Howard, Christian Schlegel a nd Kris Iniewski, Error Control Coding in Low- role Wireless Sensor Networks When is ECC Energy-Efcient, Dept. of Electrical Computer Engineering University of Alberta Edmonton, AB Canada T6G 2V4 Email sheryl,schlegel,emailprotected.Alyosha Molnar, Benson Lu, Steven Lanzisera, Ben W. Cook and Kristofer S. J. Pister, An Ultra-low Power 900 MHz RF Transceiver for Wireless Sensor Networks, IEEE 2004 CUSTOM INTEGRATED CIRCUITS CONFERENCE, 0-7803-8495-4/04/$20.00 02004 IEEE.Jun Wang, Yong-Tao Cao, Jun-Yuan Xie, CCF and Shi-Fu Chen, Energy Efficient Backoff Hierarchical Clustering Algorithms for Multi-Hop Wireless Sensor Networks, JOURNAL OF COMPUTER apprehension AND TECHNOLOGY 26(2) 283291 Mar. 2011. DOI 10.1007/s11390011-1131-x, 2011 Springer Science +Business Media, LLC Science Press, China. Mar. 2011, Vol.26, No.2.