'Distributed' signal processing: new opportunities and challenges

摘要

Summary form only given. We are at a novel crossroads in technology where we are witnessing the confluence of computing, communicating and networking. A number of exciting applications are both driving and being driven by this confluence, including low-power sensor networks, large-scale ad hoc wireless networks, and wireless multimedia transmission. Many of these applications demand a move away from classical centralized architectures and algorithms towards more decentralized and distributed ones. Signal processing plays a key role in this revolution- not in isolation but rather as a pivotal interdisciplinary systems component, intimately integrated with communications, information theory, coding theory, and networking protocols. Sensor networks represent a particularly rich applications base. We would provide a snapshot of the sensor network related activities in a number of research groups at Berkeley. Motivated by the communications and computational constraints imposed by large-scale low-power sensor networks, we would describe some of our signal processing centric research including: (i) distributed sampling; (ii) distributed source coding; (iii) distributed estimation; and (iv) robust transmission. We would highlight the key foundational role played by multi-user information theory, particularly the so-called area of side-information coding for both source coding (compression) and channel coding (transmission). A deeper look reveals a beautiful functional duality between source and channel coding with side-information. This unexpectedly unifies a host of seemingly unrelated problem areas like distributed compression, digital watermarking, multimedia transmission over packet-error networks, and seamless digital upgrade of analog TV. Finally, as a microcosm of the expressive power of interdisciplinary thinking, we would describe a novel video compression paradigm dubbed PRISM (power-efficient, robust, hlh-compression, syndrome-based multimedia coding). PRISM's architecture, in stark contrast to that driving current video codecs like MPEG, allows for a novel shifting of the computational complexity from the encoder to the decoder, making it ideally suited for "uplink" transmission scenarios in wireless multimedia and surveillance applications.