Related papers: Simulating Dense Small Cell Networks
Simulation tools are commonly used in the development and testing of new protocols or new networks. However, as satellite networks start to grow to encompass thousands of nodes, and as companies and space agencies begin to realize the…
In order to cope with the forecasted 1000x increase in wireless capacity demands by 2030, network operators will aggressively densify their network infrastructure to reuse the spectrum as much as possible. However, it is important to…
Simulators are indispensable parts of the research and development necessary to advance countless industries, including cellular networks. With simulators, the evaluation, analysis, testing, and experimentation of novel designs and…
The large number of Wireless Sensor Networks (WSN) simulators available nowadays, differ in their design, goals, and characteristics. Users who have to decide which simulator is the most appropriate for their particular requirements, are…
Network simulation is the most useful and common methodology used to evaluate different network to-pologies without real world implementation. Network simulators are widely used by the research community to evaluate new theories and…
Small cell network (SCN) offers, for the first time, a low-cost and scalable mechanism to meet the forecast data-traffic demand. In this paper, we propose a non-uniform SCN deployment scheme. The small cell base stations (BSs) in this…
Wireless sensor networks (WSNs) have emerged as one of the most promising technologies for the current era. Researchers have studied them for several years ago, but more work still needed to be made since open opportunities to integrate new…
Software development for Wireless Sensor Networks (WSNs) is challenging due to characteristics of sensor nodes and the environment they are deployed in. Testing software in a real WSN testbed allows users to get reliable test results.…
Future dense small-cell networks are one key 5G candidates to offer outdoor high access data rates, especially in millimeter wave (mmWave) frequency bands. At those frequencies, the free space propagation loss and shadowing (from buildings,…
Most popular, modern network simulators, such as ns, are targeted towards simulating low-level protocol details. These existing simulators are not intended for simulating large distributed applications with many hosts and many concurrent…
In pursuance of integrating Wireless Sensor Networks (WSNs) with other systems, the use of techniques from other fields, such as machine learning and information processing, are becoming more common. Therefore, we faced the problem of…
We experience a major paradigm change in mobile networks. The infrastructure of cellular networks becomes mobile as it is densified by using mobile and nomadic small cells to increase coverage and capacity. Furthermore, the innovative…
Dense small satellite networks (DSSN) in low earth orbits (LEO) can benefit several mobile terrestrial communication systems (MTCS). However, the potential benefits can only be achieved through careful consideration of DSSN infrastructure…
New intelligence applications are driving increasing interest in deploying deep neural networks (DNN) in a distributed way. To set up distributed deep learning involves alterations of a great number of the parameter configurations of…
Wireless sensor network (WSN) has attracted researchers worldwide to explore the research opportunities, with application mainly in health monitoring, industry automation, battlefields, home automation and environmental monitoring. A WSN is…
This paper describes NS - Network Simulator, the computer networks simulation tool. We offer an overview NS, and also analyze its characteristics and functions. Finally, we present in detail all steps for preparing a simulation of a simple…
Small-cell densification is a strategy enabling the offloading of users from macro base stations (MBSs), in order to alleviate their load and increase the coverage, especially, for cell-edge users. In parallel, as the network increases in…
Without any doubt, Machine Learning (ML) will be an important driver of future communications due to its foreseen performance when applied to complex problems. However, the application of ML to networking systems raises concerns among…
In this letter, we consider the problem of signal detection in generalized spatial modulation (GSM) using deep neural networks (DNN). We propose a novel modularized DNN architecture that uses small sub-DNNs to detect the active antennas and…
We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation…