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Wireless body area networks (WBANs) incorporate multiple battery-operated nodes positioned either inside, on, or vicinity of the human body, providing remote monitoring of patients with comfort and ease thus, allowing them to retain their health record while reducing hospital visits (“Wireless Body Area Networks,” 2012). The technology is not solely confined to medical purposes but extends to sports, entertainment, disaster management, consumer electronics, smart clothing, and beyond.
Gartner Inc. forecasted that $42 billion would be spent on wearable devices by end-users in 2019 with a shipment of 225 million units worldwide, an increase of 25.8% from 2018 (“Forecast: Wearable Electronic Devices, Worldwide, 2018.”) According to Forbes, the wearable market will be doubled by 2022 creating a market worth of $27 billion (Lamkin, 2018). CCS Insights, a global technology research firm, predicts the sale of wearables to reach 142 million units in 2019 leading to 260 million units in 2023, generating revenue of almost $30 billion (“Optimistic Outlook for Wearables.” 2019).
In IEEE 802.15.6, i.e. the specified WBAN standard, channel models (CM) are segregated based on node location and classified as CM1 – CM4. A CM1 model is specified for the communication of invasive nodes whereas; the communication among in body and on body nodes is specified by CM2. A CM3 model is associated with the nodes deployed on the body, and CM4 is used for off-body communication. Considering above, designing an energy efficient strategy is challenging as the link conditions vary significantly due to posture variations and a complex body structure. The dynamic channel conditions and limited energy resources compromise the operation of WBAN. One of the substantial challenges is to model a communication technique between the nodes in such a way that network lifetime is enhanced and energy is utilized efficiently, as replacing the sensors frequently is undesirable (Park, Kim, & Choi, 2010). Also, in order to avoid unwanted interference among co-located WBANs, given the short range of communication, the nodes are inclined to function at ultra-low power. On the contrary, very low transmission power give rise to high packet error rate (PER) resulting in re-transmissions and low packet delivery ratios (PDR) (Alam & Hamida, 2014; Alam, Arbia, & Hamida, 2016). Moreover, under time-varying realistic channel conditions, i.e. body shadowing, channel fading, and propagation path loss, the transmission capability further deteriorate. Consequently, it is essential to have an equitable balance between PDR performance and transmission power.
In order to cater for the above-mentioned challenges in WBAN, a number of techniques are presented. Various cooperative communication scenarios are considered to improve the network capacity and provide energy efficient transmission (Movassaghi, Shirvanimoghaddam, & Abolhasan, 2013; Wang, Cano, & Giannakis, 2005), as cooperative communication is better compared to direct communication in terms of energy efficiency (EE) (Movassaghi, Shirvanimoghaddamy, Abolhasan, & Smith, 2013).
Cooperative communication for a single relay scenario discussed for an ultra-wideband (UWB) based WBAN shows that a cooperative mechanism between in-body and on-body sensors can decrease outages and increase energy efficiency (Ding, Dutkiewicz, & Huang, 2013). An incremental relay scheme depicts an improved PER and EE when measured against the distance between source and destination while deriving analytical expressions (Deepak & Babu, 2015; Yousaf et al., 2015; Yousaf at el., 2016). The energy consumption for direct and coded transmission links is also discussed based on various modulation schemes (Deepak & Babu, 2016). In non-invasive WBANs, network coding is being used for improved transmission reliability of healthcare units, considering bit error rate (BER) versus signal strength while neglecting in-body transmissions and link length (Taparugssanagorn, Ono, & Kohno, 2010). Two-way relay cooperation is considered in terms of EE, effective performance range, and optimal packet size (Waheed, Ahmad, Ahmed, Drieberg, & Alam, 2018). A hybrid scheme and joint network-channel coding are also discussed.