Link Scheduling Algorithm with Interference Prediction for Multiple Mobile WBANs

Abstract

As wireless body area networks (WBANs) become a key element in electronic healthcare (e-healthcare) systems, the coexistence of multiple mobile WBANs is becoming an issue. The network performance is negatively affected by the unpredictable movement of the human body. In such an environment, inter-WBAN interference can be caused by the overlapping transmission range of nearby WBANs. We propose a link scheduling algorithm with interference prediction (LSIP) for multiple mobile WBANs, which allows multiple mobile WBANs to transmit at the same time without causing inter-WBAN interference. In the LSIP, a superframe includes the contention access phase using carrier sense multiple access with collision avoidance (CSMA/CA) and the scheduled phase using time division multiple access (TDMA) for non-interfering nodes and interfering nodes, respectively. For interference prediction, we define a parameter called interference duration as the duration during which disparate WBANs interfere with each other. The Bayesian model is used to estimate and classify the interference using a signal to interference plus noise ratio (SINR) and the number of neighboring WBANs. The simulation results show that the proposed LSIP algorithm improves the packet delivery ratio and throughput significantly with acceptable delay.

Identification key scheme to enhance network performance in wireless body area network

“…In addition, vibrations at 402-405 MHz have propagation characteristics that lead to the transmission of radio signals within the human body and do not pose a significant risk of interference in other radio processes in this range and miniaturization and low-power consumption. MICS band is located at an optimum frequency range that promises high-level of integration with the advanced radio frequency IC (RFIC) technology [20][21][22][23], while higher frequency causes higher penetration loss, high-level integration becomes difficult at low frequencies. In addition, there exist relatively insignificant penetration loss at these frequencies (10 dB with 10 mm tissue penetration).…”

Interference and Priority Aware Coexistence (IPC) Algorithm for Link Scheduling in IEEE 802.15.6 Based WBANs

“…Dynamic, Reliable and Energy Efficient Scheduling (DREES), presents two new TDMA based techniques to improve reliability and energy efficiency for WBANs [27]. In Link Scheduling Algorithm with Interference Prediction (LSIP), the interference prediction was carried out through the Bayesian model that estimates interference duration and the number of interfering nodes [31]. Dynamic Coexistence Management (DCM) provides distributed coexistence mitigation without exchanging information between the WBANs [25].…”

Smart Link Adaptation and Scheduling for IIoT

“…However, existing LA and scheduling approaches do not account for quasi-periodicity of traffic in IIoT environments [4], rendering it partially predictable [5], [6]. Incorporating interference prediction within the scheduling process can naturally improve the spectral efficiency (SE) [7].…”

“…In earlier works [7], centralized interference prediction and scheduling was proposed with coordination achieved at the cost of increased communication overhead. Alternatively, in the present work, traffic patterns are learned using distributed interference prediction using long short-term memory (LSTM) neural networks.…”