Characterization of the Body-to-Body Propagation Channel for Subjects during Sports Activities

Abstract

Body-to-body wireless networks (BBWNs) have great potential to find applications in team sports activities among others. However, successful design of such systems requires great understanding of the communication channel as the movement of the body components causes time-varying shadowing and fading effects. In this study, we present results of the measurement campaign of BBWN during running and cycling activities. Among others, the results indicated the presence of good and bad states with each state following a specific distribution for the considered propagation scenarios. This motivated the development of two-state semi-Markov model, for simulation of the communication channels. The simulation model was validated using the available measurement data in terms of first and second order statistics and have shown good agreement. The first order statistics obtained from the simulation model as well as the measured results were then used to analyze the performance of the BBWNs channels under running and cycling activities in terms of capacity and outage probability. Cycling channels showed better performance than running, having higher channel capacity and lower outage probability, regardless of the speed of the subjects involved in the measurement campaign.

Advanced spatial modulation for efficient MIMO‐based B2B communications in sporting activities

“…It is also noted that running Scenario II gives the worst result for any particular method. There is an oscillatory motion of the arms in case of running scenario, while in case of cycling, leaning and body tilting occurs and the arms are relatively stationary [22]. Due to such movements, the clusters are less distinct for cycling scenarios, whereas running scenario provides more prominent scatterers.…”

“…The analysis of the experiment was performed over an outdoor stretch of 500 m with 25 kg samples being collected for each scenario. The equipment details and procedures of measurement are provided in [22].…”

Channel Characterization and Modeling for Optical Wireless Body-Area Networks

“…Focusing on T c,50 , for instance, we note that it is on the order of hundreds of milliseconds to a few seconds, ranging between 0.78 to 3.27 sec for CN1 and between 0.95 to 2.26 sec for CN2. These relatively long coherence times indicate that optical intra-WBAN links have a slow time-varying nature, compared to their RF counterparts for which the coherence time is on the order of 0.025 to 0.07 sec [60], [61]. As a result, optical WBAN links benefit from larger packet sizes, a lower pilot overhead, and the possibility of using a simpler adaptive transmit power control over successive packets.…”

Moving Towards Body-to-Body Sensor Networks for Ubiquitous Applications: A Survey

“…Few works tackled the body-to-body concept and investigate a single or limited design axes [3,15,16,35,36]. For example, real testbed-based experiments are conducted in [35] to explore the connectivity behavior in body-to-body communications under different network parameters (radio technology, interference conditions, mobility, data dissemination scheme, etc.).…”

“…A body-to-body pointed study is also present in [3], especially a distributed routing protocol is introduced using an adaptive CSMA/CA cross-layer mechanism. Some other studies focused on the body-to-body channel characterization such as [15,16,36]. Even fewer works tackled the inter-WBAN coexistence issue [32,[37][38][39], some of which are discussed in detail in this survey hereafter.…”