For randomly deployed systems, although, the antenna element is sealed inside the node, the surrounding objects that may cover the nodes could distort the antenna radiation pattern. Conducting objects create the most severe pattern distortion. Those objects with dimensions near the length of the antenna behave as parasitic elements of an uncontrolled array, producing random nulls in the antenna radiation pattern. Nonconducting objects can also distort the radiation pattern. Therefore, different nodes might exhibit different radiation patterns, and the antenna gains of a link of a source-destination pair of nodes may vary from one hop to another within the system. Consequently, the coverage area will be impacted by the antenna radiation pattern. Characterization of the radiation pattern of a randomly deployed system, would be very useful for developing and deploying efficient and cost-effective sensor systems.

In a wireless sensor system, RF transmissions encounter two classes of interference: intrasystem interference (interference from node to node) and intersystem interference (interference from other systems which operate at the same frequencies as the nodes). The accumulated interference level at the victim node reduces the signal-to-interference plus noise ratio (SINR), which desensitizes the receiver of the victim node and degrades the system throughput. The SINR can be estimated by:

where:

P_r = the desired received signal power,
I_i = the signal power from the ith interfering node,
I_k = signal power from the kth external interfering source, and
N_o = the receiver's thermal noise power.

The SINR depends on the distance between the victim node and the interfering sources, the strength of the desired signal, and the strength of the interfering signals. In the case where a system is based on collision-avoidance design, all nodes do not transmit at the same time. and intrasystem interference would not be as critical as intersystem interference. Because of the low transmit power of the nodes, intersystem interference could be a concern in sensor systems. Low SINR degrades the system's BER, as well as the capacity of the system, which is expressed as:

where:

C = the system capacity (b/s) and
B = the system bandwidth (Hz).

For WSNs, capacity is not a major issue since each node operates at low data rates. Characterization and modeling of RF interference in a WSN would be essential for ensuring the coexistence of the systems with other wireless technologies. Such technologies include IEEE 802.11 b/g wireless local-area networks (WLANs), WiMAX, Bluetooth, cordless phones, and ultrawideband (UWB).

Designing transmitters for sensor systems requires careful consideration for choosing the modulation scheme. There are many important criteria for choosing the most suitable modulation scheme, including power consumption,^{11, 12} transmit power, and cost. The limited power supply in sensor systems mandates that the transmitter operates under nonlinear conditions.

Since power consumption is a design constraint, power-efficient modulation such as binary frequency-shift keying (BFSK) could be a good candidate for a WSN. BFSK is a form of constant-envelope modulation, which allows the transmit power amplifier (PA) to operate in a nonlinear condition.

Besides the choice of the modulation scheme, the choice of transmitter architecture can also contribute to power savings. This can be achieved by using RF blocks that draw low current. Transmitters based on multiple frequency upconversion and filtering stages do not comply with low-cost and low-power requirements. Efficient generation of the transmit signal can be achieved by using a single in-phase/quadrature (I/Q) upconversion topology (Fig. 5). The PA is the most power-hungry block in the transmitter. However, the choice of modulation scheme affects the requirements for peak-to-average power ratio, and can contribute to a power savings in the transmitter.

In summary, designing an effective WSN involves extensive knowledge of the propagation environment, where performance can be compromised by hidden sensor nodes or sensors covered by vegetation. An accurate propagation model is essential for developing a cost-effective WSN. In addition, the choice of frequency has a significant effect on system performance. Lower frequencies suffer less path loss and better range than higher frequencies, although higher frequencies result in smaller sensor nodes. For very small size nodes and very high-density deployment, millimeter-wave frequencies of 70 GHz and higher offer miniature antennas and the chance for frequency reuse. But, at these high frequencies, routing issues may be a problem.

In WSNs, low node transmit power makes the system susceptible to radio interference.

Thus, an interference assessment is essential for efficient system design and deployment. In some WSN applications, nodes are deployed randomly and may be hidden or blocked by other objects, in which case the radiation characteristics of the node antennas may be affected. Therefore, measurements of the radiation pattern of the nodes in different environments would help in predicting the system performance.

ACKNOWLEDGMENTS
The authors would like to acknowledge the Defence Research and Development Canada-Valcartier for sponsoring this and other research activities in the area of wireless sensor networks. Special thanks to Mr. Luc Boucher of the Communications Research Centre Canada for good suggestions and discussions, as well as for his support for this work.

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