IEEE 802.11n –Next Generation Wireless Standard
ABSTRACT
The newest standard in Wireless LAN is called 802.11n. 802.11 is an industry standard for high-speed networking. 802.11n is designed to replace the 802.11a, 802.11b and 802.11g standards. 802.11n equipment is backward compatible with older 802.11gab and it supports much faster wireless connections over longer distances. So-called “Wireless N” or “Draft N” routers available today are based on a preliminary version of the 802.11n. The beta version of this standard is used now in laptops and routers. 802.11n will work by utilizing multiple input multiple output (MIMO) antennas and channel bounding in tandem to transmit and receive data. It contains at least 2 antennas for transmitting data’s. 802.11n will support bandwidth greater than 100 Mbps and in theory it can have a speed of 600 Mbps.It can be used in high speed internets, VOIP, Network Attach Storage (NAS), gaming. The full version will be implemented in the laptops and in the LANs in upcoming yearsAdaptive Piezoelectric energy harvesting circuit
This paper describes an approach to harvesting electrical energy from a mechanically excited piezoelectric element. A vibrating piezoelectric device differs from a typical electrical power source in that it has a capacitive rather than inductive source impedance, and may be driven by mechanical vibrations of varying amplitude. An analytical expression for the optimal power flow from a rectified piezoelectric device is derived, and an “energy harvesting “ circuit is proposed which can achieve this optimal power flow. The harvesting circuit consists of an ac-dc rectifier with an output capacitor, an electrochemical battery, and a switch-mode dc-dc converter that controls the energy flow into the battery. An adaptive control technique for the dc-dc converter is used to continuously implement the optimal power transfer theory and maximize the power stored by the battery. Experimental result reveal that the use of the adaptive dc-dc converter increases power transfer by over 400% as compared to when the dc-dc converter is not used.ANN Based Power System Restoration
Power System Restoration (PSR) has been a subject of study for many years. In recent years many techniques were proposed to solve the limitations of predetermined restoration guidelines and procedures used by a majority of system operators to restore a system following the occurrence of a wide area disturbance. This paper discusses limitations encountered in some currently used PSR techniques and a proposed improvement based on Artificial Neural Networks (ANNs). This proposed scheme has been tested on a 162-bus transmission system and compared with a breadth search transmission system. The results indicate that, this is a feasible option that should be considered for real time applications.Artificial Neural Networks (ANNs) are computational techniques that try to obtain a performance similar to that of human’s performance when solving problems. The building block of ANN is Artificial Neuron, which has got structural & functional similarities with biological neurons. ANN is also an efficient alternative for problem solutions where it is possible to obtain data describing the problem behavior, but a mathematical description of the process is impossible. The proposed restoration scheme is composed of several Island Restoration Schemes (IRS). Each IRS is responsible for the development of an Island Restoration Plan when the power system is recovering from a wide area disturbance.
