Intermittent Communication

Abstract: We formulate a model for intermittent communication that can capture bursty transmissions or a sporadically available channel, where in either case the receiver does not know a priori when the transmissions will occur. Focusing on the point-to-point case, we develop a decoding structure, decoding from pattern detection, and its achievable rate for such communication scenarios. Decoding from pattern detection first detects the locations of codeword symbols and then uses them to decode. We introduce the concept of partial divergence and study some of its properties in order to obtain stronger achievability results. As the system becomes more intermittent, the achievable rates decrease due to the additional uncertainty about the positions of the codeword symbols at the decoder. Additionally, we provide upper bounds on the capacity of binary noiseless intermittent communication with the help of a genie-aided encoder and decoder. The upper bounds imply a tradeoff between the capacity and the intermittency rate of the communication system, even if the receive window scales linearly with the codeword length.