CIF: Small: Theory and Codes for Intermittent and Sparse Communication

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Growing interest in sensor networks and other wireless communication network infrastructure for a host of applications presents important engineering challenges. In particular, there is a need to deliver data quickly and reliably in harsh environments, using often very scarce energy and bandwidth resources. Compared with traditional networks, a distinguishing feature of communication in many emerging applications is the inherent sparseness of communication---that is,communication between participating nodes is highly intermittent. For example, a sensor node may send a few hundred bits of information every few days. In such cases, there is not only uncertainty due to noise to contend with, but timing uncertainty as well. Such transmission profiles create unique challenges, due to the requirement to synchronize with the receiver each time. As a result, for short transmissions, traditional synchronization approaches can consume a disproportionate share of the available resources.This research develops and analyzes models for asynchronous communication suitable for such applications, starting with basic single-user channels and proceeding to broader multiuser and network scenarios. The investigation studies fundamental limits and trade-offs associated with such models, and pursues architectures,protocols, and practical codes for resource-efficient communication in such settings. Because such models explicitly incorporate the lack of prior synchronization in the communication, the associated coding schemes of interest ensure reliable communication in the presence of such timing uncertainty. The research uses such models to assess the relative value of different candidate sparse communication architectures, including quantifying the inefficiency of traditional architectures in which synchronization and communication subsystems are separate, over an approach in which synchronization and communication are combined.