CogCell: Cognitive Interplay between 60GHz Picocells and 2.4/5GHz Hotspots in the 5G Era

Rapid proliferation of wireless communication devices and the emergence of a variety of new applications have triggered investigations into next-generation mobile broadband systems, i.e., 5G. Legacy 2G--4G systems covering large areas were envisioned to serve both indoor and outdoor environments. However, in the 5G-era, 80\% of overall traffic is expected to be generated in indoors. Hence, the current approach of macro-cell mobile network, where there is no differentiation between indoors and outdoors, needs to be reconsidered. We envision 60\,GHz mmWave picocell architecture to support high-speed indoor and hotspot communications. We envisage the 5G indoor network as a combination of-, and interplay between, 2.4/5\,GHz having robust coverage and 60\,GHz links offering high datarate. This requires an intelligent coordination and cooperation. We propose 60\,GHz picocellular network architecture, called CogCell, leveraging the ubiquitous WiFi. We propose to use 60\,GHz for the data plane and 2.4/5GHz for the control plane. The hybrid network architecture considers an opportunistic fall-back to 2.4/5\,GHz in case of poor connectivity in the 60\,GHz domain. Further, to avoid the frequent re-beamforming in 60\,GHz directional links due to mobility, we propose a cognitive module -- a sensor-assisted intelligent beam switching procedure -- which reduces the communication overhead. We believe that the CogCell concept will help future indoor communications and possibly outdoor hotspots, where mobile stations and access points collaborate with each other to improve the user experience.Comment: 14 PAGES in IEEE Communications Magazine, Special issue on Emerging Applications, Services and Engineering for Cognitive Cellular Systems (EASE4CCS), July 201

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Application of multiple-wireless to a visual localisation system for emergency services

Abstract—In this paper we discuss the application of multiplewireless technology to a practical context-enhanced service system called ViewNet. ViewNet develops technologies to support enhanced coordination and cooperation between operation teams in the emergency services and the police. Distributed localisation of users and mapping of environments implemented over a secure wireless network enables teams of operatives to search and map an incident area rapidly and in full coordination with each other and with a control centre. Sensing is based on fusing absolute positioning systems (UWB and GPS) with relative localisation and mapping from on-body or handheld vision and inertial sensors. This paper focuses on the case for multiple-wireless capabilities in such a system and the benefits it can provide. We describe our work of developing a software API to support both WLAN and TETRA in ViewNet. It also provides a basis for incorporating future wireless technologies into ViewNet. I

Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

A survey of localization in wireless sensor network

Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

Bio-inspired algorithm for decisioning wireless access point installation

This paper presents the bio-inspired algorithms for decisioning wireless access point (AP) installation. In order to achieve the desired coverage capability of APs, the bio-inspired algorithms are applied for robust competition and optimization. The main objective is to determine the optimal number of APs with the high coverage capability in the concerning area using the genetic and ant colony optimization algorithms. Received signal strength indicator (RSSI) and line-of-sight (LoS) gradient approach are the most important parameters for AP installation depending on the AP signal strength. Practical experiments are tested on the embedded system using Xilinx Kria KR260 and Raspberry Pi Zero 2W boards at the tested room size about 16 m wide and 40 m long inside the building. Xilinx Kria KR260 board is used to calculate the number of AP installation and localization compared to Xcode. Then, Raspberry Pi Zero 2W board is the representation of wireless AP for measuring the signal in the testing area. Experiment results show that maximum received signals strength is equal to -35 dBm at 6 m and there are six APs installation with high coverage area and maximum received signal strength at the area of 16×40 m2