Kamran Sayrafian

Mobile wearable communications [Guest Editorial]

This special issue provides the latest research and development on wireless mobile wearable communications. According to a report by Juniper Research, the market value of connected wearable devices is expected to reach

Uncoordinated strategies for inter-BAN interference mitigation

1.5 billion by 2014, and the shipment of wearable devices may reach 70 million by 2017. Good examples of wearable devices are the prominent Google Glass and Microsoft HoloLens. As wearable technology is rapidly penetrating our daily life, mobile wearable communication is becoming a new communication paradigm. Mobile wearable device communications create new challenges compared to ordinary sensor networks and short-range communication. In mobile wearable communications, devices communicate with each other in a peer-to-peer fashion or client-server fashion and also communicate with aggregation points (e.g., smartphones, tablets, and gateway nodes). Wearable devices are expected to integrate multiple radio technologies for various applications’ needs with small power consumption and low transmission delays. These devices can hence collect, interpret, transmit, and exchange data among supporting components, other wearable devices, and the Internet. Such data are not limited to peoples personal biomedical information but also include human-centric social and contextual data. The success of mobile wearable technology depends on communication and networking architectures that support efficient and secure end-to-end information flows. A key design consideration of future wearable devices is the ability to ubiquitously connect to smartphones or the Internet with very low energy consumption. Radio propagation and, accordingly, channel models are also different from those in other existing wireless technologies. A huge number of connected wearable devices require novel big data processing algorithms, efficient storage solutions, cloud-assisted infrastructures, and spectrum-efficient communications technologies.

Impact of the energy detection threshold on performance of the IEEE 802.15.6 CSMA/CA

A Body Area Network (BAN) is a radio standard for wireless connectivity of wearable and implantable sensor nodes that are located inside or in proximity to the human body. Many applications of BANs (e.g. physiological monitoring) require reliable communication of information between the sensor nodes and their controller. As there are currently no coordinating mechanisms among multiple co-located BANs, interference caused by co-channel transmission in adjacent BANs could impact the reliability and in general quality of the service experienced by a receiver node within an individual BAN. Here, we present a simulation platform that allows for statistical evaluation of interference in multi-BAN scenarios and performance of possible mitigation algorithms. Currently, there are no mechanisms for interfering BANs to explicitly coordinate their transmissions. As our analysis show, this may result in unacceptably high interference; and therefore, high link outage probability by the intended receiver. We propose uncoordinated approaches that could help to ease cross-interference among multiple adjacent BANs. Simulation results in our preliminary studies support the effectiveness of our approach.

A Novel Cyber Physical System for 3-D Imaging of the Small Intestine In Vivo

A Body Area Network (BAN) is a radio interface standard for wireless connectivity of wearable and implantable sensors located inside or in close proximity to the human body. Medical applications requirements impose stringent constraints on the reliability, and quality of service performance in these networks. Interference from other co-located BANs or nearby devices that share the same spectrum could greatly impact the data link reliability in these networks. Specifically, the CSMA/CA MAC protocol as outlined in the IEEE802.15.6 BAN standard involves the use of an energy detection threshold to determine the status of the transmission channel i.e. idle versus busy. In this paper, we would like to show that the use of such static thresholds could negatively impact the performance of the system composed of multiple co-located BANs. It could also lead to starvation or unfair treatment of a node that is experiencing excessive interference due to its physical location relative to all other nodes in the system. A simulation platform is presented to highlight this problem and investigate the performance impact.

A queue-size & channel quality based adaptation of the energy detection threshold in IEEE802.15.6 CSMA/CA

Small intestine is the longest organ in the gastrointestinal tract where much of the digestion and the food absorption take place. Wireless video capsule endoscope (VCE) is the first device taking 2-D pictures from the lesions and the abnormalities in the entire length of the small intestine. Since precise localization and mapping inside the small intestine is a very challenging problem, we cannot measure the distance traveled by the VCE to associate lesions and abnormalities to locations inside the small intestine, and we cannot use the 2-D pictures to reconstruct the 3-D image of interior of the entire small intestine in vivo. This paper presents the architectural concept of a novel cyber physical system (CPS), which can utilize the 2-D pictures of the small intestine taken by the VCE to reconstruct the 3-D image of the small intestine in vivo. Hybrid localization and mapping techniques with millimetric accuracy for inside the small intestine is presented as an enabling technology to facilitate the reconstruction of 3-D images from the 2-D pictures. The proposed CPS architecture provides for large-scale virtual experimentations inside the human body without intruding the body with a sizable equipment using reasonable clinical experiments for validation. The 3-D imaging of the small intestine in vivo allows a lesion to be pinpointed for follow-up diagnosis and/or treatment and the abnormalities may be observed from different angles in 3-D images for more thorough examination.

Autonomous relocation strategies for cells on wheels in public safety networks

IEEE802.15.6 is a radio interface standard for wireless connectivity of wearable and implantable sensors and actuators located inside or in close proximity to the human body i.e., Body Area Network (BAN). Medical applications impose stringent requirements on BAN Quality of Service (QoS), including reliability and on-time availability of data. However, interference from other co-located BANs or other nearby devices sharing the same spectrum, e.g., due to BAN mobility, may cause unacceptable QoS degradation. This paper suggests that the impact of such QoS degradations can be minimized with a queue-size and channel quality based adaptation of the Energy Detection Threshold (EDT) at the transmitting nodes. Guided by known results for Q-CSMA/CA, we propose an adaptive EDT algorithm for use in the IEEE 802.15.6 BAN standard. Our preliminary simulation results demonstrate the performance gain of our algorithm compared to using a fixed EDT, and thus warrant future efforts in the adaptive EDT optimization as a mechanism to maintain QoS in various interference scenarios.

Uncoordinated scheduling strategies for BAN-to-BAN interference mitigation

Lack of network availability or limited access to communication services are among the challenges that public safety officials and first responders could face during disasters. Networking infrastructure can partially (or sometimes fully) breakdown during a catastrophe. At the same time, unusual peaks in traffic load could lead to much higher blocking probability for critical communication. A possible solution for such scenarios is through the use of mobile infrastructures commonly referred to as Cells on Wheels (COW) or Cells on Light Trucks (COLT). These mobile cells can effectively complement the existing undamaged infrastructure or enable a temporary emergency network by themselves. Given the limited capacity of each cell, variable and spatially non-uniform traffic across the disaster area can make a big impact on the network performance. Not only judicious deployment of the cells can help to meet the coverage and capacity demands across the area, but also intelligent relocation strategies can optimally match the network resources to potentially changing traffic demands. Assuming that each cell can autonomously change its location, in this paper, we propose a decentralized relocation algorithm that adapts network coverage in order to increase the supported users traffic.

Regret minimization based adaptation of the energy detection threshold in body area networks

A Body Area Network (BAN) is a radio standard for wireless connectivity of wearable and implantable sensors located inside or in close proximity to the human body. Medical and some other applications impose stringent constraints on battery powered BAN reliability, quality of service, and power consumption. However, lack of coordination among multiple colocated BANs in the current BAN standard may cause unacceptable deterioration of BAN reliability and quality of service due to high levels of inter-BAN interference. Assuming Time Division Multiple Access (TDMA), this paper proposes inter-BAN interference mitigation using several novel uncoordinated transmission scheduling algorithms. These algorithms use patterns of past and current interference for implicit coordination across multiple BAN transmissions. Simulation results demonstrate improvement in the performance and potential benefits of the proposed strategies.

Autonomous relocation strategies for cells on wheels in environments with prohibited areas

IEEE802.15.6 is a radio interface standard for wireless connectivity of wearable and implantable sensors and actuators located inside or in close proximity to the human body i.e., Body Area Network (BAN). Medical applications impose stringent requirements on BAN Quality of Service (QoS), including reliability and on-time availability of the sensors data. However, interference from other co-located BANs or other nearby devices sharing the same spectrum may cause unacceptable QoS degradation. The impact of such degradations can be minimized by using adaptive schemes that intelligently adjust relevant parameters at the transmitting or receiving nodes of a BAN. This paper provides a framework for low complexity regret minimization based algorithms for Energy Detection Threshold (EDT) adaptation in the transmitter node of a BAN. The nodes are assumed to be using the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol according to the IEEE 802.15.6 BAN standard. Our preliminary simulation results demonstrate the performance gain of our algorithm compared to using a fixed EDT, and thus warrant future efforts in the adaptive EDT optimization as a mechanism to maintain QoS in various interference scenarios.

Using RTS/CTS to enhance the performance of IEEE 802.15.6 CSMA/CA

Public safety organizations increasingly rely on wireless technology for their mission critical communication during disaster response operations. In such situations, a communication network could face much higher traffic demands compared to its normal operation. Given the limited capacity of base stations in the network, such peak traffic scenarios could lead to high blocking probability or equivalently service interruptions during critical communications. At the same time, networking infrastructure can breakdown during a disaster. Proper deployment of mobile cells — Cells on Wheels — can help to enhance the network coverage or accommodate excess traffic in areas with high concentration of users. In addition, an intelligent relocation strategy can be used to efficiently adapt the cell locations to match variations in the spatial distribution of the traffic. In practical scenarios, these mobile base stations may not be able to relocate to all positions within the target field. Such prohibited areas introduce additional constraints on designing an intelligent relocation strategy. In this paper, we propose a decentralized relocation algorithm that enables mobile cells to adapt their positions in response to potentially changing traffic patterns in a field with prohibited areas. Extensive simulations show considerable improvement in supporting spatially variable traffic throughout the target field.