Cross-Technology Interference Mitigation in Body Area Networks: An Optimization Approach

In recent years, wearable devices and wireless body area networks have gained momentum as a means to monitor people's behavior and simplify their interaction with the surrounding environment, thus representing a key element of the body-to-body networking (BBN) paradigm. Within this paradigm, several transmission technologies, such as 802.11 and 802.15.4, that share the same unlicensed band (namely, the industrial, scientific, and medical band) coexist, dramatically increasing the level of interference and, in turn, negatively affecting network performance. In this paper, we analyze the cross-technology interference (CTI) caused by the utilization of different transmission technologies that share the same radio spectrum. We formulate an optimization model that considers internal interference, as well as CTI to mitigate the overall level of interference within the system, explicitly taking into account node mobility. We further develop three heuristic approaches to efficiently solve the interference mitigation problem in large-scale network scenarios. Finally, we propose a protocol to compute the solution that minimizes CTI in a distributed fashion. Numerical results show that the proposed heuristics represent efficient and practical alternatives to the optimal solution for solving the CTI mitigation (CTIM) problem in large-scale BBN scenarios.

I. Introduction

The ongoing evolution of wireless technologies has fostered the development of innovative network paradigms such as wireless body area networks (WBANs), where the pervasive deployment of wireless devices endowed with sensing capabilities interweaves the physical and digital worlds, thus enabling the development of enhanced services. WBANs, and, more specifically, body-to-body networks (BBNs), are emerging solutions for the monitoring of people's behavior and their interaction with the surrounding environment. In its most common configuration, a BBN consists of several WBANs, as shown in Fig. 1. Each WBAN is composed of wearable sensor nodes, connected through the 802.15.4 protocol (i.e., ZigBee) to their mobile terminal (MT). The set of wearable sensors may be used to consistently monitor people's vital signs, such as blood pressure, heart rate, skin temperature, or important environmental parameters such as temperature and humidity. Furthermore, wireless headsets can be used to enable communications among BBN users, whereas glasses such as those recently proposed by Google and Microsoft can be wirelessly connected with a smartphone to provide augmented reality [1]. Fig. 1.

Network scenario. Two BBNs corresponding to two different groups of people (i.e., black and gray) are using the same set of unlicensed channels.