Sergio Camorlinga

Remote patient monitoring service using heterogeneous wireless access networks: architecture and optimization

Remote patient monitoring is an eHealth service, which is used to collect and transfer biosignal data from the patients to the eHealth service provider (e.g., healthcare center). A heterogeneous wireless access-based remote patient monitoring system is presented in which multiple wireless technologies are integrated to support continuous biosignal monitoring in presence of patient mobility. A patient-attached monitoring device with a heterogeneous wireless transceiver collects biosignal data from the sensors and transmits the data through the radio access network (RAN) to the eHealth service provider. In this system, the eHealth service provider reserves wireless bandwidth (or connections) from a network service provider in a proactive manner as well as in an on-demand basis. To determine the optimal number of connections to be reserved pro-actively so that the network access cost is minimized, a stochastic programming problem is formulated considering the randomness of service demand due to the mobility of the patients. Since different biosignal data can have different quality-of-service (QoS) requirements, traffic scheduling is used in the patient-attached device which determines whether to transmit and what to transmit over an available wireless connection. To make the optimal scheduling decision, an optimization problem is formulated as a constrained Markov decision process (CMDP). The objective of this formulation is to minimize the connection cost. The proposed system architecture and the optimization formulations will be useful for the eHealth service provider to provide flexible and cost-effective monitoring service to remote/mobile patients.

A cognitive radio system for e-health applications in a hospital environment

Wireless communications technologies are used to support a variety of electronic health applications to transfer medical data and patient information. However, using wireless communications technology in a healthcare environment poses two major challenges. First, the electromagnetic interference caused to bio-medical devices by wireless devices could critically affect their performance. Second, since different types of e-health applications have different priorities, access to the wireless channel by the corresponding devices needs to be prioritized. In this article we introduce a novel cognitive-radio-based approach to address these challenges in wireless communications for e-health applications in a hospital environment. First, the requirements for a wireless communications system to be used in a healthcare environment are identified, and potential applications of cognitive radio technology for e-health applications are discussed. Then a cognitive radio system is proposed for e-health applications in a hospital environment, which protects the medical devices from harmful interference by adapting the transmit power of wireless devices based on EMI constraints. An EMI-aware handshaking protocol is proposed for channel access by two different types of applications with different priorities. The performance of this cognitive radio system for e-health applications is evaluated through simulations.

An EMI-Aware Prioritized Wireless Access Scheme for e-Health Applications in Hospital Environments

Wireless communications technologies can support efficient healthcare services in medical and patient-care environments. However, using wireless communications in a healthcare environment raises two crucial issues. First, the RF transmission can cause electromagnetic interference (EMI) to biomedical devices, which could critically malfunction. Second, the different types of electronic health (e-Health) applications require different quality of service (QoS). In this paper, we introduce an innovative wireless access scheme, called EMI-aware prioritized wireless access, to address these issues. First, the system architecture for the proposed scheme is introduced. Then, an EMI-aware handshaking protocol is proposed for e-Health applications in a hospital environment. This protocol provides safety to the biomedical devices from harmful interference by adapting transmit power of wireless devices based on the EMI constraints. A prioritized wireless access scheme is proposed for channel access by two different types of applications with different priorities. A Markov chain model is presented to study the queuing behavior of the proposed system. Then, this queuing model is used to optimize the performance of the system given the QoS requirements. Finally, the performance of the proposed wireless access scheme is evaluated through extensive simulations.

Characterizing random CSMA wireless networks: A stochastic geometry approach

We charachterize the random CSMA wireless networks by statistically quantifing the intensity of simultaneously active nodes and the aggregate interference experienced by a generic node in the network. First, starting from a Poisson point process to model the spatial distribution of the network nodes, we propose a modified hard core point process (MHCPP) to model the spatial distribution of the simultaneously active users in a random CSMA network. Our motivation to propose the MHCPP is to mitigate the node intensity underestimation problem of the traditional hard core point process (HCPP). Then, we use the shot noise theory to statistically quantify the interference experienced by a generic node in the network. Closed-form expressions for the intensity of the simultaneously active nodes and the Laplace transform of the probability density function (and hence the moment generating function and the characteristic function), mean, and variance of the approximate aggregate interference are obtained. The accuracy of our model is validated by simulations.

An Optimization-Based GTS Allocation Scheme for IEEE 802.15.4 MAC with Application to Wireless Body-Area Sensor Networks

IEEE 802.15.4 standard is widely used in wireless personal area networks (WPANs). This standard supports a limited number of guaranteed time slots (GTSs) for time-critical or delay-sensitive data transmission.We propose a GTS allocation scheme to improve reliability and bandwidth utilization in IEEE 802.15.4-based wireless body area sensor networks (WiBaSe-Nets). A knapsack problem is formulated to obtain optimal GTS allocation such that a minimum bandwidth requirement is satisfied for the sensor devices. Simulation results show that the proposed scheme can achieve better GTS utilization and higher packet delivery ratio than the standard IEEE 802.15.4 scheme does.

Electromagnetic Interference-Aware Transmission Scheduling and Power Control for Dynamic Wireless Access in Hospital Environments

We study the multiple access problem for e-Health applications (referred to as secondary users) coexisting with medical devices (referred to as primary or protected users) in a hospital environment. In particular, we focus on transmission scheduling and power control of secondary users in multiple spatial reuse time-division multiple access (STDMA) networks. The objective is to maximize the spectrum utilization of secondary users and minimize their power consumption subject to the electromagnetic interference (EMI) constraints for active and passive medical de vices and minimum throughput guarantee for secondary users. The multiple access problem is formulated as a dual objective optimization problem which is shown to be NP-complete. We propose a joint scheduling and power control algorithm based on a greedy approach to solve the problem with much lower computational complexity. To this end, an enhanced greedy algorithm is proposed to improve the performance of the greedy algorithm by finding the optimal sequence of secondary users for scheduling. Using extensive simulations, the tradeoff in performance in terms of spectrum utilization, energy consumption, and computational complexity is evaluated for both the algorithms.

IEEE 802.15.4 MAC With GTS Transmission for Heterogeneous Devices With Application to Wheelchair Body-Area Sensor Networks

In wireless personal area networks, such as wireless body-area sensor networks, stations or devices have different bandwidth requirements and, thus, create heterogeneous traffics. For such networks, the IEEE 802.15.4 medium access control (MAC) can be used in the beacon-enabled mode, which supports guaranteed time slot (GTS) allocation for time-critical data transmissions. This paper presents a general discrete-time Markov chain model for the IEEE 802.15.4-based networks taking into account the slotted carrier sense multiple access with collision avoidance and GTS transmission phenomena together in the heterogeneous traffic scenario and under nonsaturated condition. For this purpose, the standard GTS allocation scheme is modified. For each non-identical device, the Markov model is solved and the average service time and the service utilization factor are analyzed in the non-saturated mode. The analysis is validated by simulations using network simulator version 2.33. Also, the model is enhanced with a wireless propagation model and the performance of the MAC is evaluated in a wheelchair body-area sensor network scenario.

Traffic offloading techniques in two-tier femtocell networks

Due to the scarcity of the wireless spectrum along with the ever increasing number of cellular wireless users and the associated drastic increase in the data traffic demand, femtocells are envisioned to provide fast, flexible, cost-efficient, and customer driven solutions to offload users from the congested macro access network and enhance the overall system performance. To control offloading and to achieve the required balance of users and traffic served by each network tier, we quantify offloading and discuss different techniques that can be used to offload users from the macro access network to the femto access network, namely, offloading via power control, offloading via femtocell deployment and offloading via biasing. In this paper, we quantify offloading when users connect to the network entity that provides the strongest instantaneous signal power in a Nakagami-m fading environment. To this end, we discuss the merits and drawbacks of each of the offloading techniques.

A Cost-Effective Web-Based Teaching File System

Teaching files are common in radiology. Although there is an increasing role of digital technology in radiology departments, today’s teaching files have not yet seen the application of this new technology. This may have been due in part to poor or incomplete implementation in many commercial software packages. We have demonstrated that by utilizing free software from the Internet, a web-based teaching file system, which is easy to use, low cost, and secure, can be created.

Robust Scheduling and Power Control for Vertical Spectrum Sharing in STDMA Wireless Networks

We study the robust transmission scheduling and power control problem for spectrum sharing between secondary and primary users in a spatial reuse time-division multiple access (STDMA) network. The objective is to find a robust minimum-length schedule for secondary users (in terms of time slots) subject to the interference constraints for primary users and the traffic demand of secondary users. We consider the fact that power allocation based on average (or estimated) link gains can be improper since actual link gains can be different from the average link gains. Therefore, transmission of the secondary links may fail and require more time slots. We also consider this demand uncertainty arising from channel gain uncertainty. We propose a column generation-based algorithm to solve the scheduling and power control problem for secondary users. The column generation method breaks the problem down to a restricted master problem and a pricing problem. However, the classical column generation method can have convergence problem due to primal degeneracy. We propose an improved column generation algorithm to stabilize and accelerate the column generation procedure by using the perturbation and exact penalty methods. Furthermore, we propose an efficient heuristic algorithm for the pricing problem based on a greedy algorithm. For the simulation scenario considered in this paper, the proposed stabilized column generation algorithm can obtain the optimal schedules with 18.85% reduction of the number of iterations and 0.29% reduction of the number of time slots. Also, the heuristic algorithm can achieve the optimality with 0.39% of cost penalty but 1.67×10-4 times reduction of runtime.