Route Swarm: Wireless Network Optimization through Mobility

In this paper, we demonstrate a novel hybrid architecture for coordinating networked robots in sensing and information routing applications. The proposed INformation and Sensing driven PhysIcally REconfigurable robotic network (INSPIRE), consists of a Physical Control Plane (PCP) which commands agent position, and an Information Control Plane (ICP) which regulates information flow towards communication/sensing objectives. We describe an instantiation where a mobile robotic network is dynamically reconfigured to ensure high quality routes between static wireless nodes, which act as source/destination pairs for information flow. The ICP commands the robots towards evenly distributed inter-flow allocations, with intra-flow configurations that maximize route quality. The PCP then guides the robots via potential-based control to reconfigure according to ICP commands. This formulation, deemed Route Swarm, decouples information flow and physical control, generating a feedback between routing and sensing needs and robotic configuration. We demonstrate our propositions through simulation under a realistic wireless network regime.Comment: 9 pages, 4 figures, submitted to the IEEE International Conference on Intelligent Robots and Systems (IROS) 201

Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

Wireless machine-to-machine networks 2013

Editoria

New Coding/Decoding Techniques for Wireless Communication Systems

Wireless communication encompasses cellular telephony systems (mobile communication), wireless sensor networks, satellite communication systems and many other applications. Studies relevant to wireless communication deal with maintaining reliable and efficient exchange of information between the transmitter and receiver over a wireless channel. The most practical approach to facilitate reliable communication is using channel coding. In this dissertation we propose novel coding and decoding approaches for practical wireless systems. These approaches include variable-rate convolutional encoder, modified turbo decoder for local content in Single-Frequency Networks, and blind encoder parameter estimation for turbo codes. On the other hand, energy efficiency is major performance issue in wireless sensor networks. In this dissertation, we propose a novel hexagonal-tessellation based clustering and cluster-head selection scheme to maximize the lifetime of a wireless sensor network. For each proposed approach, the system performance evaluation is also provided. In this dissertation the reliability performance is expressed in terms of bit-error-rate (BER), and the energy efficiency is expressed in terms of network lifetime

Joint Data Routing and Power Scheduling for Wireless Powered Communication Networks

In a wireless powered communication network (WPCN), an energy access point supplies the energy needs of the network nodes through radio frequency wave transmission, and the nodes store the received energy in their batteries for their future data transmission. In this paper, we propose an online stochastic policy that jointly controls energy transmission from the EAP to the nodes and data transfer among the nodes. For this purpose, we first introduce a novel perturbed Lyapunov function to address the limitations on the energy consumption of the nodes imposed by their batteries. Then, using Lyapunov optimization method, we propose a policy which is adaptive to any arbitrary channel statistics in the network. Finally, we provide theoretical analysis for the performance of the proposed policy and show that it stabilizes the network, and the average power consumption of the network under this policy is within a bounded gap of the minimum power level required for stabilizing the network

Reliable and Secure Drone-assisted MillimeterWave Communications

The next generation of mobile networks and wireless communication, including the fifth-generation (5G) and beyond, will provide a high data rate as one of its fundamental requirements. Providing high data rates can be accomplished through communication over high-frequency bands such as the Millimeter-Wave(mmWave) one. However, mmWave communication experiences short-range communication, which impacts the overall network connectivity. Improving network connectivity can be accomplished through deploying Unmanned Ariel Vehicles(UAVs), commonly known as drones, which serve as aerial small-cell base stations. Moreover, drone deployment is of special interest in recovering network connectivity in the aftermath of disasters. Despite the potential advantages, drone-assisted networks can be more vulnerable to security attacks, given their limited capabilities. This security vulnerability is especially true in the aftermath of a disaster where security measures could be at their lowest. This thesis focuses on drone-assisted mmWave communication networks with their potential to provide reliable communication in terms of higher network connectivity measures, higher total network data rate, and lower end-to-end delay. Equally important, this thesis focuses on proposing and developing security measures needed for drone-assisted networks’ secure operation. More specifically, we aim to employ a swarm of drones to have more connection, reliability, and secure communication over the mmWave band. Finally, we target both the cellular 5Gnetwork and Ad hoc IEEE802.11ad/ay in typical network deployments as well as in post-disaster circumstances

The Complete Analytical Solution of the TDOA Localization Method

This article is focused on the analytical solution of a TDOA (Time Difference of Arrival) localization method, including analysis of accuracy and unambiguity of a target position estimation in 2D space. The method is processed under two conditions - sufficiently determined localization system and an overdetermined localization system. It is assumed that the TDOA localization system operates in a LOS (Line of Sight) situation and several time-synchronized sensors are placed arbitrarily across the area. The main contribution of the article is the complete description of the TDOA localization method in analytical form only. It means, this paper shows a geometric representation and an analytical solution of the TDOA localization technique model. In addition, analyses of unambiguity and solvability of the method algorithm are presented, together with accuracy analysis of this TDOA technique in analytical form. Finally, the description of this TDOA method is extended to an overdetermined TDOA system. This makes it possible to determine and subsequently optimize its computational complexity, for example increase its computational speed. It seems that such a description of the TDOA localization technique creates a simple and effective tool for technological implementation of this method into military localization systems

A Localization System for Optimizing the Deployment of Small Cells in 2-Tier Heterogeneous Wireless Networks

Due to the ever growing population of mobile device users and expansion on the number of devices and applications requiring data usage, there is an increasing demand for improved capacity in wireless cellular networks. Cell densification and 2-tier heterogeneous networks (HetNets) are two solutions which will assist 5G systems in meeting these growing capacity demands. Small-cell deployment over existing heterogeneous networks have been considered by researchers. Different strategies for deploying these small-cells within the existing network among which are random, cell-edge and high user concentration (HUC) have also been explored. Small cells deployed on locations of HUC offloads traffic from existing network infrastructure, ensure good Quality of Service (QoS) and balanced load in the network but there is a challenge of identifying HUC locations. There has been considerable research performed into techniques for determining user location and cell deployment. Currently localization can be achieved using time dependent methods such as Time of Arrival (ToA), Time Difference of Arrival (TDoA), or Global Positioning Systems (GPS). GPS based solutions provide high accuracy user positioning but suffer from concerns over user privacy, and other time dependent approaches require regular synchronization which can be difficult to achieve in practice. Alternatively, Received Signal Strength (RSS) based solutions can provide simple anonymous user data, requiring no extra hardware within the mobile handset but often rely on triangulation from adjacent Base Stations (BS). In mobile cellular networks such solutions are therefore often only applicable near the cell edge, as installing additional BS would increase the complexity and cost of a network deployment. The work presented in this thesis overcomes these limitations by providing an observer system for wireless networks that can be used to periodically monitor the cell coverage area and identify regions of high concentrations of users for possible small cell deployment in 2-tier heterogeneous networks. The observer system comprises of two collinear antennas separated by λ/2. The relative phase of each antenna was varied using a phase shifter so that the combined output of the two antennas were used to create sum and difference radiation patterns, and to steer the antenna radiation pattern creating different azimuth positions for AoA estimation. Statistical regression analysis was used to develop range estimation models based on four different environment empirical pathloss models for user range estimation. Users were located into clusters by classifying them into azimuth-range classes and counting the number of users in each class. Locations for small cell deployment were identified based on class population. BPEM, ADEM, BUEM, EARM and NLOS models were developed for more accurate range estimation. A prototype system was implemented and tested both outdoor and indoor using a network of WiFi nodes. Experimental results show close relationship with simulation and an average PER in range estimation error of 80% by applying developed error models. Based on both simulation and experiment, system showed good performance. By deploying micro-, pico-, or femto-cells in areas of higher user concentration, high data rates and good quality of service in the network can be maintained. The observer system provides the network manager with relative angle of arrival (AoA), distance estimation and relative location of user clusters within the cell. The observer system divides the cell into a series of azimuthal and range sectors, and determines which sector the users are located in. Simulation and a prototype design of the system is presented and results have shown system robustness and high accuracy for its purpose