## 1 Introduction  
Piezoelectric sensor networks that are embedded in large civil structures, such as pipes, offshore platforms, bridges and railways, are considered as the future of structural health monitoring (SHM) systems [1]. Active acoustic sensors or actuators in the network can be excited to generate elastic waves that could propagate a long distance and interrogate structures for possible defects, thus providing _in situ_ monitoring of the integrity and operating conditions of the structures. One of the important aspects of sensor networks for SHM applications is its ability for data communication between sensors. This is because the operating status and conditions of the structure under monitoring must be sent through the network to a central processing unit, so that human operators can take necessary actions when defects are detected. Data communication within a sensor network could occur between two or multiple sensor nodes or between sensor nodes and a central processing unit. In the classic communication theory, information-bearing signals are modulated and excited from a transmitter; the excitation signals propagate through physical medium as propagation waves, such as electromagnetic waved and acoustical waved, and are received by a receiver. The received signals are demodulated to recover the transmitted information bits. In many existing SHM sensor network applications, conventional schemes, such as wireless radio communication and acoustical communication, are employed for data communication. However, the underlying wave propagation physics reveals that conventional communication schemes are often inapplicable or inadequate in many real-life situations. For example, for pipes that are buried underground or for hollow sub-sea structures in offshore platforms, radio communication is difficult to realize, because electromagnetic wave signals suffer severe decay in soil or water, which results in very short transmission range. Ultrasonic waves, _i.e._, waves that travel along a rod, tube, pipe or plate-like structure, form guided waves as a result of the interaction between ultrasonic excitation signals propagating in a medium and the medium's boundaries [2; 3; 4]. The excitation of guided ultrasonic waves has become a popular tool for nondestructive inspection of pipes and other physical infrastructures, due to their potential to travel great distances [5; 6; 7; 8]. However, there are three fundamental difficulties when guided waves are utilized for pipe inspection and data communication, _i.e._, signal dispersion, multimode and ambient noise. First, the elastic guided wave signals are highly dispersive. Signal dispersion stems from the underlying elastic wave propagation physics, which signal transmission speed varies with frequencies. Acoustic signal dispersion causes signal time spreading, as well as phase and frequency shift. In communication theory, this phenomenon is called multipath propagation. The delayed arrivals of propagating signals may overlap, destructively causing severe signal attenuation or signal fading, which results in poor system performance in many stages of the communication flow, including synchronization, signal detection and demodulation, _etc._ Second, pipe waves are characterized by an infinite number of dispersive longitudinal and torsional modes and a doubly infinite number of flexural modes [9]. The longitudinal and torsionalmodes are both axisymmetric, while each flexural mode exhibits an infinite number of non-axisymmetric circumferential mode orders [10, 11]. Thus, a proper selection of wave modes for signal transmission would be a critical, but difficult, task. Third, ambient noise exists in the received signals. Ambient noise refers to the addition of a random signal of specific mean value and variance. A high noise level reduces the signal-to-noise power ratio at the receiver, which yields poor performance for signal detection. Adaptive filtering methods should be employed to reduce the level of ambient noise.