Dynamic channel allocation for interference mitigation in relay-assisted wireless body networks

Abstract

Abstract-We focus on interference mitigation and energy conservation within a single wireless body area network (WBAN). We adopt two-hop communication scheme supported by the the IEEE 802.15.6 standard 2012 [14]. In this paper, we propose a dynamic channel allocation scheme, namely DCAIM to mitigate node-level interference amongst the coexisting regions of a WBAN. At the time, the sensors are in the radius communication of a relay, they form a relay region (RG) coordinated by that relay using time division multiple access (TDMA). In the proposed scheme, each RG creates a table consisting of interfering sensors which it broadcasts to its neighboring sensors. This broadcast allows each pair of RGs to create an interference set (IS). Thus, the members of IS are assigned orthogonal sub-channels whereas other sonsors that do not belong to IS can transmit using the same time slots. Experimental results show that our proposal mitigates node-level interference and improves node and WBAN energy savings. These results are then compared to the results of other schemes. As a result, our scheme outperforms in all cases. Node-level signal to interference and noise ratio (SINR) improved by 11dB whilst, the energy consumption decreased significantly. We further present a probabilistic method and analytically show the outage probability can be effectively reduced to the minimal.

A stochastic game for adaptive security in constrained wireless body area networks

“…To reduce the complexity of the computation of the Nash equilibrium (20), we adopt the Pareto efficiency which is defined by the state where it is impossible to make any player better off without making at least one individual worse off.…”

“…We assume a communication model with different link quality, where a bit error rate (BER) is assigned to indicate excellent (PRR: 0.99) and bad (PRR: 0.5) link quality. The channel model involves the node transmission power (-10dBm), receiver sensitivity (-84.7dBm), noise floor (-102dBm), an additive white Gaussian noise (AWGN) of mean zero and σ=6.81dBm as well as the path loss exponent (3.6) [20]. The path loss model is defined by a path loss at reference distance PL (dref) =23.49dB, an average deviation σdB=2.93 and reference distance dref=0.5cm [21].…”