Resolve wireless sensor network issues –

January 7, 2014

While both low-power sensors and wireless networking are now ever-present, there are still relatively minimal examples on the market of low-power wireless sensor networks. This is not for lack of interest – wireless sensors promise to cut installation costs dramatically, and provide access to data previously impossible or prohibitively expensive to obtain. While sensors have become smaller, less expensive, and lower power, installation costs have not kept pace: labour for wiring in new construction dwarfs the cost of a switch. When retrofitted into an existing building, or in an industrial process control environment, per-sensor installation costs can be hundreds or thousands of dollars.

With such strong cost motivation, why have wireless sensor networks (WSNs) not come to dominate the market? Two factors—radio power and network reliability—have kept WSNs largely “niche” products.

Technology choices
Customers want a technology that is low cost, allows unrestricted sensor placement, reliable and quick data reporting, and runs for years with no battery changes. Recent advances in low-power radios and communications protocols have enabled us to deliver those features in many markets.

Data collection applications typically involve large numbers of sense points forwarding data to a central host that may respond with a process set-point or other configuration changes. There are several technologies competing to fill this role, including satellite, cellular, Wi-Fi, and IEEE 802.15.4-based solutions.

Satellite and cellular have the highest energy cost per packet, and are generally unsuitable for battery powered applications. These solutions make sense only for applications sending at a very low data rate (e.g., one data packet per day) with known good connectivity.

Wi-Fi (IEEE 802.11b, g) sensors are now widely available. The energy cost for a Wi-Fi packet is much lower than cellular, but still high for battery powered operation. Connectivity and coverage remain important concerns, as the density of access points necessary for reliable communication with a fixed sensor is typically high.

The IEEE 802.15.4 standard defines a physical layer (PHY) and Medium Access Control (MAC) layer for short-range, low-power operation, ideal for WSNs. IEEE 802.15.4 forms the basis of several proprietary and standards-based protocols including ZigBee unsynchronised single-channel networks, and WirelessHART1 time-synchronised multi-channel networks. Using Linear Technology’s LTC5800-IPM802.15.4 Mote-on-Chip, sending a few bytes of sensor data, with routing, cryptography, and other headers uses under 30µC of charge, including receiving a secure link-layer acknowledgement (figure 1).

Figure 1: Energy to transmit a short 802.15.4 packet and receive an acknowledgement.

Mesh networks
Reliability is a concern when transitioning to wireless systems. The wireless channel is unreliable in nature, and a number of phenomena can prevent a transmitted packet from reaching a receiver – these can be exacerbated as radio power decreases.

Interference occurs when multiple transmitters send at the same time and frequency. This is particularly problematic if they cannot hear each other (the “hidden terminal problem”). Backoff, retransmission, and acknowledgement mechanisms are required to resolve collisions. Interference can come from within the network, another similar network operating in the same radio space, or from a different radio technology operating in-band—a common occurrence in the band shared by Wi-Fi, Bluetooth, and 802.15.4.

A second highly varying phenomenon called multi-path fadingcan prevent successful transmission even when the line-of-sight link margin is expected to be sufficient. This occurs when multiple copies of the transmission bounce off objects in the environment (ceilings, doors, people, etc.) all traveling different distances. When interfering destructively, fades of 20-30dB are common. Multipath fading depends on the transmission frequency, device position, and on every nearby object – predicting it is practically impossible.

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Originally posted 2013-04-12 08:22:27.

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