A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Technology Integration for M2M Communications <s> In this paper we consider the interconnection of an IEEE 802.15.4 body area network (BAN) in which nodes sense physiological variables such as electrocardiography (EKG), electroencephalography (EEG), pulse oximeter data, blood pressure and cardiac output, with an IEEE 802.11b room/ward WLAN. We model the operation of this two-tier network assuming that 802.15.4 BAN operates in CSMA-CA mode and that the BAN coordinator acts as the bridge which conveys BAN packets to the 802.11b access point. We analyze the two-hop network delay and discuss the mutual interaction of different data streams as well as impact of the number of bridges on packet delay. <s> BIB001 </s> A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Technology Integration for M2M Communications <s> 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. <s> BIB002 </s> A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Technology Integration for M2M Communications <s> E-Health services comprise a broad range of healthcare services delivered by using information and communication technology. In order to support existing as well as emerging e-Health services over converged next generation network (NGN) architectures, there is a need for network QoS control mechanisms that meet the often stringent requirements of such services. In this paper, we evaluate the QoS support for e-Health services in the context of the Evolved Packet System (EPS), specified by the Third Generation Partnership Project (3GPP) as a multi-access all-IP NGN. We classify heterogeneous e-Health services based on context and network QoS requirements and propose a mapping to existing 3GPP QoS Class Identifiers (QCIs) that serve as a basis for the class-based QoS concept of the EPS. The proposed mapping aims to provide network operators with guidelines for meeting heterogeneous e-Health service requirements. As an example, we present the QoS requirements for a prototype e-Health service supporting tele-consultation between a patient and a doctor and illustrate the use of the proposed mapping to QCIs in standardized QoS control procedures. <s> BIB003 </s> A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Technology Integration for M2M Communications <s> To enable full mechanical automation where each smart device can play multiple roles among sensor, decision maker, and action executor, it is essential to construct scrupulous connections among all devices. Machine-to-machine communications thus emerge to achieve ubiquitous communications among all devices. With the merit of providing higher-layer connections, scenarios of 3GPP have been regarded as the promising solution facilitating M2M communications, which is being standardized as an emphatic application to be supported by LTE-Advanced. However, distinct features in M2M communications create diverse challenges from those in human-to-human communications. To deeply understand M2M communications in 3GPP, in this article, we provide an overview of the network architecture and features of M2M communications in 3GPP, and identify potential issues on the air interface, including physical layer transmissions, the random access procedure, and radio resources allocation supporting the most critical QoS provisioning. An effective solution is further proposed to provide QoS guarantees to facilitate M2M applications with inviolable hard timing constraints. <s> BIB004 </s> A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Technology Integration for M2M Communications <s> This paper describes issues related to one of the most significant challenges that 3GPP faces in supporting M2M communications over LTE: facilitating the support for low cost M2M devices. The paper considers the requirements for low cost M2M devices and the most significant contributors to device cost. System bandwidth is identified as being a significant cost contributor and backwards compatible approaches to reducing system bandwidth are identified. <s> BIB005 </s> A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Technology Integration for M2M Communications <s> It is well known that the evolution of 4G-based mobile multimedia network systems will contribute significantly to future mobile healthcare (m-health) applications that require high bandwidth and fast data rates. Central to the success of such emerging applications is the compatibility of broadband networks, such as mobile Worldwide Interoperability For Microwave Access (WiMAX) and High-Speed Uplink Packet Access (HSUPA), and especially their rate adaption issues combined with the acceptable real-time medical quality of service requirements. In this paper, we address the relevant challenges of cross-layer design requirements for real-time rate adaptation of ultrasound video streaming in mobile WiMAX and HSUPA networks. A comparative performance analysis of such approach is validated in two experimental m-health test bed systems for both mobile WiMAX and HSUPA networks. The experimental results have shown an improved performance of mobile WiMAX compared to the HSUPA using the same cross-layer optimization approach. <s> BIB006
The integration of access communication technologies with WBANs is a challenging but crucial issue. Some works identify the challenges to enable M2M communications over LTE and LTE-A, focusing on the air interface BIB004 , scheduling mechanisms  , and the support of low-cost devices BIB005 . The use of WiMAX-based broadband wireless access technology for mHealth applications, along with potential deployment scenarios and related radio resource management issues has been discussed in  . Apart from these high-level approaches, there are some works in the literature that study more specific M2M mHealth scenarios. For instance,  discusses the suitability of WiFi-based solutions within healthcare facilities such as single hospital units, as long as proper design, installation and validation methods are followed to meet the specific application requirements. In BIB001 , a two-tier network architecture is considered. At the lower tier, multiple sensor devices worn by a single patient form a WBAN, by employing the CSMA/CA access mode of IEEE 802.15.4. At the upper tier, multiple WBAN coordinators (corresponding to multiple patients) located within a specific area (e.g., a hospital ward), communicate with an Access Point through WiFi. End-to-end packet delay and access time has been modeled as a function of the number of coexisting WBANs. An extension of this work, in  , has introduced service differentiation to prioritize high-rate data streams (e.g., EEG data) by providing them contention-free access, whereas CSMA/CA access is given to low-rate streams (e.g., ECG data). In  , the authors discuss the feasibility of employing a hybrid network based on WiFi and WiMAX technologies as the access communication network in an M2M system for mHealth services. The integration of the two technologies poses several challenges, mainly related to QoS provisioning, connection admission control, scheduling, and mobility management through seamless vertical handovers. The envisioned heterogeneous deployment scenario considers nodes with either single (WiFi or WiMAX) or dual radio interface and aims to provide wireless connectivity between different subnetworks, including WBANs, home care networks, mobile patients and networks of healthcare providers (such as intranets of hospitals, clinics, drugstores, etc.). Another remote monitoring scheme that provides ubiquitous connectivity for mobile patients has been presented in BIB002 . In the proposed scheme, shown in Figure 5 , a patient-attached monitoring device collects the WBAN data, classifies them as high-priority (e.g., critical data such as blood pressure, pulse rate and heart rate) or normal priority (e.g., ECG signal) and forwards them towards the healthcare provider through an heterogeneous WiFi/WiMAX access communication network. The access technology is selected depending on the patient's location, considering that WiFi hotspots cover only specific (mainly indoor) locations and WiMAX has a wider (outdoor) coverage. In addition, two types of connections are provided by the network operator: (i) low-cost reserved connections, allocated to patients for given amounts of time (e.g., weeks); and (ii) high-cost on-demand connections, employed when the available bandwidth for reserved connections is not enough to cover the traffic load. The authors approach this mHealth scenario from the service provider's side, who has to buy in advance a certain number of reserved connections from the network operator to serve a given number of patients. Stochastic programming techniques are used to determine the optimal number of reserved connections for each wireless technology in order to minimize the provider's cost. As far as LTE-based solutions for healthcare applications are concerned, the relevant works in the literature are limited. The impact of 4G communication technologies on mHealth and the emerging challenges are discussed in  . In BIB003 , a mapping between the QoS requirements of mHealth services and the existing service classes defined by 3GPP standards is proposed, aiming to provide guidelines for network operators. A cross-layer design for QoS of medical video streaming over mobile WiMAX (IEEE 802.16e) and the 3G High-Speed Packet Access (HSPA) cellular technology is proposed in BIB006 , and a comparison between the performance of the two technologies is given, opening the road to further investigation on LTE-based mHealth applications.