Search results for "NETWORKING"
showing 10 items of 1776 documents
Joint Power Allocation and Link Selection for Multi-Carrier Buffer Aided Relay Network
2019
In this paper, we present a joint power allocation and adaptive link selection protocol for an orthogonal frequency division multiplexing (OFDM)-based network consists of one source node i.e., base station (BS), one destination node i.e., (MU) and a buffer aided decode and forward (DF) relay node. Our objective is to maximize the average throughput of the system via power loading over different subcarriers at source and relay nodes. A separate power budget is assumed at each transmitting node to make the system more practical. In order to form our solution more tractable, a decomposition framework is implemented to solve the mixed integer optimization problem. Further, less complex suboptim…
Distributed Resource Allocation for Energy Efficiency in OFDMA Multicell Networks with Wireless Power Transfer
2019
In this paper, an energy-efficient resource allocation problem is investigated for the wireless power transfer (WPT)-enabled OFDMA multicell networks. In the considered system, multiple base stations (BSs) with a large number of antennas are responsible to provide WPT in the downlink, and the users can recycle and utilize the received energy for uplink data transmission. The role of BS is to execute WPT; thus, there are no data transmissions in the downlink. A time-division protocol is considered to divide the time of downlink WPT and uplink wireless information transfer into separate time slots. With the objective to improve the energy efficiency, we propose the time, subcarrier, and power…
On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes
2010
This paper concerns the use of Prototype Reduction Schemes (PRS) to optimize the computations involved in typical k-Nearest Neighbor (k-NN) rules. These rules have been successfully used for decades in statistical Pattern Recognition (PR) applications, and have numerous applications because of their known error bounds. For a given data point of unknown identity, the k-NN possesses the phenomenon that it combines the information about the samples from a priori target classes (values) of selected neighbors to, for example, predict the target class of the tested sample. Recently, an implementation of the k-NN, named as the Locally Linear Reconstruction (LLR) [11], has been proposed. The salien…
Energy Efficient Sink Placement in Wireless Sensor Networks by Brain Storm Optimization Algorithm
2018
Wireless sensor networks represent one of the most promising technologies whose use has significantly increased in the past years. They are used in various applications such as health care monitoring, surveillance and monitoring in agriculture, industrial monitoring, habitat and underwater monitoring, etc. Deployment of the wireless sensor networks introduces number of hard optimization problems. Placement of the elements such as sensors, gateways, sinks and base stations, depend on different conditions and constraints such as signal propagation, distance, energy preservation, reliability. In this paper, we propose a method based on brain storm optimization algorithm for placing multiple si…
Energy efficient resource allocation for secure OFDMA relay systems with eavesdropper
2016
In this paper, we address the energy efficient resource allocation problem for a secure orthogonal frequency division multiple access (OFDMA) relay system. In particular, we consider there is a eavesdropper near the base station (BS) which tries to overtake the information sent by BS. We formulate the joint optimization problem with the objective to optimize the energy efficiency of the considered system by considering subcarrier pairing, secret data rate and power allocation. In addition, the system can assign different priority to different users such that the security of information transmission can be guaranteed. The proposed iterative algorithm not only maximizes the system energy effi…
Combined Elephant Herding Optimization Algorithm with K-means for Data Clustering
2018
Clustering is an important task in machine learning and data mining. Due to various applications that use clustering, numerous clustering methods were proposed. One well-known, simple, and widely used clustering algorithm is k-means. The main problem of this algorithm is its tendency of getting trapped into local minimum because it does not have any kind of global search. Clustering is a hard optimization problem, and swarm intelligence stochastic optimization algorithms are proved to be successful for such tasks. In this paper, we propose recent swarm intelligence elephant herding optimization algorithm for data clustering. Local search of the elephant herding optimization algorithm was im…
Designing Precoding and Receive Matrices for Interference Alignment in MIMO Interference Channels
2017
Interference is a key bottleneck in wireless communication systems. Interference alignment is a management technique that align interference from other transmitters in the least possibly dimension subspace at each receiver and provides the remaining dimensions for free interference signal. An uncoordinated interference is an example of interference which cannot be aligned coordinately with interference from coordinated part; consequently, the performance of interference alignment approaches are degraded. In this paper, we propose a rank minimization method to enhance the performance of interference alignment in the presence of uncoordinated interference sources. Firstly, to obtain higher mu…
Joint Spectral and Energy Efficiency Optimization for Downlink NOMA Networks
2020
Non-orthogonal multiple access (NOMA) holds the promise to be a key enabler of 5G communication. However, the existing design of NOMA systems must be optimized to achieve maximum rate while using minimum transmit power. To do so, this paper provides a novel technique based on multi-objective optimization to efficiently allocate resources in the multi-user NOMA systems supporting downlink transmission. Specifically, our unique optimization technique jointly improves spectrum and energy efficiency while satisfying the constraints on users quality of services (QoS) requirements, transmit power budget and successive interference cancellation. We first formulate a joint problem for spectrum and …
Optimization of Data Harvesters Deployment in an Urban Areas for an Emergency Scenario
2013
International audience; Since its appearance in the VANETs research community, data collection where vehicles have to explore an area and collect various local data, brings various issues and challenges. Some architectures were proposed to meet data collection requirements. They can be classified into two categories: Decentralized and Centralized self-organizing where different components and techniques are used depending on the application type. In this paper, we treat time-constrained applications in the context of search and rescue missions. For this reason, we propose a centralized architecture where a central unit plans and manages a set of vehicles namely harvesters to get a clear ove…
A Novel Multi-hop Broadcasting Method for VANETs Based on Autonomic Computing Paradigm
2014
One of the three best papers, Selected for the Annals of Telecommunications journal; International audience; Broadcasting is widely used in Vehicular Ad hoc Networks (VANETs) but it is hard to achieve efficiently since it depends on the network density, i.e. may cause network congestion if the protocols are not well designed. This paper introduces a novel Autonomic Dissemination Method (ADM) which delivers messages in accordance with given priority and density levels. The proposed approach is based on two steps: an offline optimization process and an online adaptation to the network characteristics. The aim is to make effective use of radio resources when there are many messages to send imu…