Past Research

High-speed wireless network physical layer design

The emergence of new technologies related to the topic of the high-speed packet data of wireless internet and potential applications has been explored in this research. Multiple-input and Multiple-output, or MIMO is one of several forms of smart antenna technology. Multiuser downlink scheduling problem with n receivers and m transmits antennas, where data from different users can be multiplexed is discussed. This research provides an overview of high speed data packet access (HSDPA) and focus on the business values that such a highly-efficient access technology would bring to wireless operators, including higher capacity and newer services. Each frame is encoded using a turbo code and channel coding is done by turbo codes is the best method for transmitting information with fewer errors and lower signal power. This research presents methods for evaluating radio wave propagation, especially for cases where the base station antenna is below the rooftops, i.e. in the case of microcellular network environments. The developed microcellular propagation model has been developed for network planning purposes and it has been verified using numerous field propagation measurements, since there is often a gap between theory and practical implementation, prototyping is used to study the effects of real propagation channels, non-ideal RF equipment, and to understand complexity/speed/precision tradeoffs in algorithm implementation.

In this research we explore an antenna allocation scheme with dynamic allotment for each real-time user and optimize the number of the transmit antennas according to the user’s Qos by allocating number of transmit antennas. Alamouti’s scheme is also analyzed in addition. Bringing together transmit and receive diversity, the MIMO channel is introduced. The Alamouti-based schemes are shown to achieve full diversity, i.e., they take full advantage of both transmit and receive diversity provided by the MIMO channel.

Resource allocation algorithm for MIMO system is proposed in this research that can specify the allocation of subcarriers, power, and modulation modes for every user for exploiting the maximum capacity usage based on the data rate requested by each user. It tries to optimize the power allocation among the antenna elements, so that an optimal capacity is achieved. Scheduling performance under two different types of traffic modes is also discussed: one is voice or web-browsing and the other one is for data transfer and streaming data. It provides the antenna resource allocation issue under correlated MIMO environment and diverse scheduling policies for different optimizing targets.

In the proposed algorithm, the calculation of number of  antennas a user should use in order to satisfy user’s time-varying data rate requests provided , with the assumption that the SNR and spatial correlation are known at the transmitter and the receive antenna amounts are naturally known , as a result channel capacity as the function of the number of transmit antenna. In the simulation result it shows either the higher signal-to-noise ratio or the less correlation, offer a better environment for transmission and exploration of more capacities. In the time domain analysis, they evaluate how many transmit antennas are needed to reach certain service quality to guarantee the average indemnity under certain level. The proposed algorithm requires as many transmit antennas as that of receive antennas approximately and it would be very helpful to enhance the overall usage of channel Coapcity.

Overlay Network: QoS based Performance Analysis of EAODV Protocol in Overlay Network

An overlay network comprises overlay nodes that are responsible for routing and forwarding, connected by overlay links that correspond to paths in the underlying network. The end-nodes in overlay networks are highly connected to each other due to flexible routing. This architecture have two major components; overlay nodes with virtual links, and the native layer over which the overlay network is built, and ensure performance and availability of internet routing, multicasting, QoS guarantees. This research complements the current research on routing in Ad hoc network by proposing a new protocol EADOV. The performance of various routing protocol in mobile wireless network for UPD-based application are measured. Network Simulator NS2 on Fedora environment is used for simulation which included two mobile nodes with four types of traffic VoIP, video, CBR and FTP for creating heavy load and to simulate the protocols. QoS based performance metrics (PSNR, throughput, frame losses end-to-end delay, bandwidth utilization and Error-Resilience for both sender and receiver) under different scenario has been done and results are compared for both existing and proposed routing algorithms. Better average PSNR, throughput, minimum end to end delay and less I frame (the main key frame in video which neither regenerated at destination) losses are achieved compare to AODV. Received video was also compared for both algorithms, the EAODV give better output and more good quality frames than AODV.

Sensor Network: A Different Approach of Addressing, Energy Efficient Routing and Data Aggregation for Enhanced Tree Routing Protocol

Tree topology based sensor node deployment in a region is a common approach. The network has a root called sink node and leaves known as end-devices. The end-devices sense the environmental phenomenon and forward it to the sink by single-hopping or multi-hopping. For it, device can either follow a fixed parent-child path depicted by Tree Routing protocols, or can utilize neighbor table to identify shortest path to the destination. The Enhanced Tree Routing (ETR) protocol is such a protocol that uses a structured node address assignment scheme. It uses neighbor table to find alternative one-hop neighbors link with minimum computation, other than parent-child links, for packet forwarding. The protocol is well suited for small and static tree topology and performs well. However, it lacks in focusing some issues like, how data is forwarded to sink i.e. raw-data converge cast or aggregated-data converge cast at each node, how to resolve multiple shortest path problem if network density increases and how to deal with changeable network topology. This research resolves some of the issues related to ETR protocol by proposing some new ideas and improvements.


Office Hours

Monday 10AM-12 NOON

Thursday 9AM-11AM

Addresss

CCIS Building, Room No 024-1-20-3

College of Computer and Information Science

Majmaah University, Majmaah

Kingdom of Saudi Arabia 

Contact

Contact Numbers

6721

[email protected]


إحصائية الموقع

عدد الصفحات: 15

البحوث والمحاضرات: 3

الزيارات: 4137