Energy and Sampling Constrained Asynchronous Communication

TL;DR

This paper demonstrates that in bursty asynchronous communication, sparse sampling at the receiver does not increase energy cost or delay if adaptive sampling strategies are used, maintaining capacity per unit cost.

Contribution

It shows that adaptive sparse sampling does not incur capacity or delay penalties, unlike non-adaptive methods, in energy-efficient asynchronous communication.

Findings

Sparse sampling does not reduce asynchronous capacity per unit cost.

Adaptive sampling maintains delay performance even with sparse observations.

Non-adaptive sampling increases decoding delay proportionally to 1/f.

Abstract

The minimum energy, and, more generally, the minimum cost, to transmit one bit of information has been recently derived for bursty communication when information is available infrequently at random times at the transmitter. This result assumes that the receiver is always in the listening mode and samples all channel outputs until it makes a decision. If the receiver is constrained to sample only a fraction f>0 of the channel outputs, what is the cost penalty due to sparse output sampling? Remarkably, there is no penalty: regardless of f>0 the asynchronous capacity per unit cost is the same as under full sampling, ie, when f=1. There is not even a penalty in terms of decoding delay---the elapsed time between when information is available until when it is decoded. This latter result relies on the possibility to sample adaptively; the next sample can be chosen as a function of past samples. Under non-adaptive sampling, it is possible to achieve the full sampling asynchronous capacity per unit cost, but the decoding delay gets multiplied by 1/f. Therefore adaptive sampling strategies are of particular interest in the very sparse sampling regime.