Cooperative Diversity Techniques for Energy Efficient Wireless Sensor Networks

Introduction

Wireless Sensor Networks (WSN) have been attracting great attention recently. They are relatively low cost to be deployed and to be used in many promising applications, such as biomedical sensor monitoring (e.g., cardiac patient monitoring), habitat monitoring (e.g., animal tracking), weather monitoring (temperature, humidity, etc.), seismic sensing, environment preservation and natural disaster detection/monitoring (e.g., flooding and fire) (Lewis, 2004; Tubaishat & Madria, 2003; Stankovic, Abdelzaher, Sha & Hou, 2003; Akyildiz, Sankarasubramaniam & Cayirci, 2002; Rashid-Farrokhi, Tassiulas & Liu, 1998).

An important design feature of WSN is the low energy consumption of each individual transmitting node and thereby also of the total sensor network energy consumption. The ‘bottleneck’ in the WSN, from an energy point of view, is when the nodes need to communicate with a distant base station to forward the collected data. Since the distance to the base station usually is several magnitudes greater than the distance between the individual nodes within the network, each node would need a much more powerful transmitter than necessary considering the distances within the WSN (Singh & Prasanna, 2003). One technique for achieving this is to use cooperative space-time processing to combine the transmitting power of all the nodes into a distributed non-uniform antenna array. For example in (Cui, Goldsmith, & Bahai, 2004) the energy efficiency using cooperative multiple-input multiple-output (MIMO) system was investigated and compared with the results obtained by the reference single-input single-output (SISO) system.

The WSN applications analyzed in this chapter have a topology where a large number of wireless sensor nodes are spread out over a large or small geographic area (e.g., disaster regions, indoor factory, large sports event areas, etc.). In this topology, an inefficient use of bandwidth and transmitter power resources is resulted if each wireless sensor is transmitting its measurement data to the base station (processing central). In this case, each sensor node would have to be assigned its own frequency channel and, if the base station is located a long distance from the sensor nodes, it would also demand a higher than average sensor node transmitter power. By using a coordinating cluster head, for each cluster of wireless sensor nodes, we can instead use the combined transmitter power of the node cluster through the use of beamforming to increase the transmitter-receiver separation and/or to improve the signal-to-noise ratio (SNR) of the communication link. Another advantage of using this cooperative transmission is that we can exert power control to minimize the power consumption of each individual sensor node, and thus maximizing network lifetime. In addition, in a cooperative network the measurement data could be sent by using time division multiplexing (TDM) instead of frequency division multiplexing (FDM) which improves the overall bandwidth efficiency of the system.