# A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments
## 1 Introduction
### Residential Environment eHealthcare System Architecture  
A typical architecture of a residential environment eHealthcare system [25] consists of four layers as shown in Figure 1. Each layer of this architecture is further explained in more detail as follows. The BAN layer (layer 1) incorporates a number of sensor nodes operating within a wireless network. Sensor nodes in this layer are designed such that they can be placed on the human body as very small patches (on-body sensors), sewed into fabric (wearable sensors), or implanted under the skin (in-body sensors). Figure 1: The four-layer typical architecture of an eHealthcare system. Such sensors continuously capture and relay vital parameters. However, depending on the functionalities and computation capabilities of nodes, data may require low-level on-tag processing prior to transmission. The collected data then may either initially be relayed to a central coordinator on the body or may be transmitted directly to the upper layers for further processing. The required transmission power by a sensor node in an off-body communication is mainly dependent on a number of factors such as Body Path Loss (BPL), Receive Noise Figure (RNF) and Signal to Noise Ratio (SNR) [26]. BPL greatly depends on the radiation patterns of the antennas used [27; 28]. RNF is also a device-dependent factor. Each device has its own RNF and is indicated in its datasheet. SNR however is influenced by the quality of the overall communication link. The performance of SNR can be improved by a number of techniques such as Error Control Coding (ECC) techniques and Single-Input and Multiple-Output (SIMO) methods [29; 30]. Layer 2 contains user interaction devices. Depending on the selected wireless communication protocol, different devices may be required to be used. For instance, Bluetooth-based sensor nodes require Bluetooth-based monitoring devices such as smartphones or PDAs. Layer 2 acts as an Access Point (AP). APs for residential monitoring are usually located within a room environment. Each room is equipped with an AP, where wireless devices are connected to a wired network, Wi-Fi or other relevant standards [31]. Collected data from this layer is required to be transferred to an upper layer (layer 3) in order to be prepared for the final destination. From room (layer 2) to black box (layer 3), there are a number of home networking possibilities that need to be considered [32]. There are three \"room-to-box\" scenarios which are explained in more detail as follows. First scenario provides an approach based on dedicated cabling. In this scenario, either both data and power are transferred over a cable (e.g., Power over Ethernet (POE)) [33] or data and power are transferred over separate cables (e.g., power over mains and data over Ethernet) [34]. The main disadvantage of this scenario is the requirement for cable installation which adds repetition complexity and cost to the system [35]. Table 1 lists some of the existing wired home networking technologies that can potentially be used to transfer the data over the cables [35; 36]. The second scenario relies on Power Line Communication (PLC) technology, where data and power are transferred over the mains [37]. The main advantage of this scenario is the use of existing electrical wiring infrastructure and electrical outlets [38]. PLC is a reliable technology and in terms of cost, it is less expensive than a dedicated cabling scenario [38]. However, embedded based standards for PLC are limited in bandwidth. Another important disadvantage of PLC technology is that data may be lost due to an unexpected power outage [38]. The final scenario is based on existing wireless communication protocols such as Wi-Fi or ZigBee in order to transfer the collected data from rooms to black box [35]. However, this communication method is considered less reliable when it is compared to dedicated cabling and PLC technology [38]. The third layer of the proposed system architecture as depicted in Figure 1 consists of a Decision Measuring Unit (DMU).