Adaptive link layer strategies for energy efficient wireless networking

Low power consumption is a key design metric for portable wireless network devices where battery energy is a limited resource. The resultant energy ef ficient design problem can be addressed at various levels of system design, and indeed much research has been done for hardware power optimization and power management within a wireless device. However, with the increasing tr end towards thin client type wireless devices that rely more and more on ne twork based services, a high fraction of power consumption is being account ed for by the transport of packet data over wireless links [28]. This offer s an opportunity to optimize for low power in higher layer network protocol s responsible for data communication among multiple wireless devices. Consi der the data link protocols that transport bits across the wireless link. W hile traditionally designed around the conventional metrics of throughput a nd latency, a proper design offers many opportunities for optimizing the me tric most relevant to battery operated devices: the amount of battery energ y consumed per useful user level bit transmitted across the wireless link. This includes energy spent in the physical radio transmission process, as w ell as in computation such as signal processing and error coding. This pape r describes how energy efficiency in the wireless data link can be enhanced via adaptive frame length control in concert with adaptive error control b ased on hybrid FEC (forward error correction) and ARQ (automatic repeat req uest). Key to this approach is a high degree of adaptivity. The length and error coding of the atomic data unit (frame) going over the air, and the re transmission protocol are (a) selected for each application stream (ATM vir tual circuit or IP/RSVP flow) based on quality of service (QoS) requirement s, and (b) continually adapted as a function of varying radio channel condi tions due to fading and other impairments. We present analysis and simulati on results on the battery energy efficiency achieved for user traffic of di fferent QoS requirements, and describe hardware and software implementation s.