On the Link Layer Performance of Narrowband Body Area Networks Jean-Michel Dricot 1 , Gianluigi Ferrari 2 , Stéphane Van Roy 1 , François Horlin 1 , and Philippe De Doncker 1 1. Université Libre de Bruxelles 2. University of Parma, Italy OPERA – Wireless Communications Group Dept. of Information Engineering E-mail: {jdricot, svroy, fhorlin, pdedonck}@ulb.ac.be E-mail: gianluigi.ferrari@unipr.it Abstract—Personal area networks and, more specifically, body area networks (BANs) are key building blocks of the future generation networks and the Internet of Things as well. In the last years, research has focused on the channel modeling and the definition of efficient medium access control (MAC) mech- anisms. Less attention was paid to network-level performance. Thereby, this paper presents a novel analytical model for network performance analysis with centralized and mesh topologies. This model takes into account the channel statistics (i.e., the large-scale fading) and delivers several insights on the BAN implementation. Index Terms—body area networks, wireless networks, fading, performance analysis. I. I NTRODUCTION Recent advances in ultra-low power sensors have fostered the research in the field of body-centric networks, also referred to as body area networks (BANs). In these networks, a set of nodes (called sensors) is deployed on the human body. They aim at monitoring and reporting several physiological values, such as blood pressure, breath rate, skin temperature, or heart beating rate. A pictoral example of a BAN is shown in Fig. 1, where two illustrative topologies are presented: (i) a centralized topology, where a special node (denoted as “HUB”) acts as a sink for all communications initiated by the sensor and (ii) a mesh topology (or “multi-hop topology”), where several intermediary nodes relay the information from the source node to the destination (e.g., when data fusion or sensor cooperation is required). Mesh Topology Centralized (HUB) Topology Fig. 1: Body Area Network. Most of the time, sensing is performed at low rates but, in case of emergency, the network load may increase in seconds. Therefore, an in-depth analysis of the network outage, throughput, and achievable transmission rate can give insights on the maximum supported reporting rate and the correspond- ing performance. The focus of this paper is on multi-hop communications and the impact of the specificities of the propagation channel. The modeling of the BAN channel has recently been thoroughly investigated [1]–[5]. The main findings on the body radio propagation channel can be summarized as follows. First, the average value of the power decreases as an exponential function of the distance. However, unlike classical propagation models, where the received power P is a decreasing function of the distance of the form d −α , in [6] the authors prove that a law of the form 10 −γd characterizes more accurately body radio propagation. Second, the propagation channel is subject to large-scale fading (that is, shadowing). This variation fol- lows a zero-mean Gaussian distribution in the dB scale or a Log-normal distribution in the linear scale. This paper addresses the evaluation of the throughput for BANs, being this metric a traditional measure of how much traffic can be delivered by the network [7], [8]. Therefore, our analysis is expedient to understand the level of informa- tion which could be collected and processed in body-related applications (e.g., health or fitness monitoring). We consider slotted and asynchronous communications such that, in every time slot, each node transmits independently with a probability p. Indeed, in a generic scenario, the traffic distribution in a sensor network can be considered as spatially and temporally bursty, that is, reporting periods alternate temporally and spatially with periods and areas with little or no traffic (or even with a scheduled sleep of the nodes). It may therefore be impractical to employ reservation-based MAC schemes, such as those based on time/frequency division multiple access (TD- MA/FDMA), that require a substantial amount of coordination traffic and cannot be implemented efficiently in energy- and computation-constrained sensor nodes. The rest of the paper is organized as follows. In Sec- tion II, the models, definitions, and notations are introduced. Then, in Section III, the conditional success probability of a transmission for a node given the transmitter-receiver and interference-receiver distances is derived. Section IV investi- gates the average link throughput and achievable transmission rate for centralized and mesh topologies. Section V concludes the paper. 83 EMERGING 2010 : The Second International Conference on Emerging Network Intelligence Copyright (c) IARIA, 2010 ISBN: 978-1-61208-103-8