Abstract:
An additive white Gaussian noise energy-harvesting channel with an infinite-sized battery is considered. The energy arrival process is modeled as a sequence of independen...Show MoreMetadata
Abstract:
An additive white Gaussian noise energy-harvesting channel with an infinite-sized battery is considered. The energy arrival process is modeled as a sequence of independent and identically distributed random variables. The channel capacity 1/2 log(1 + P) is achievable by the so-called best-effort and save-and-transmit schemes where P denotes the battery recharge rate. This paper analyzes the save-and-transmit scheme whose transmit power is strictly less than P and the best-effort scheme as a special case of save-and-transmit without a saving phase. In the finite blocklength regime, we obtain new nonasymptotic achievable rates for these schemes that approach the capacity with gaps vanishing at rates proportional to 1/√n and ((log n)/n)1/2 respectively where n denotes the blocklength. The proof technique involves analyzing the escape probability of a Markov process. When P is sufficiently large, we show that allowing the transmit power to back off from P can improve the performance for save-and-transmit. The results are extended to a block energy arrival model where the length of each energy block L grows sublinearly in n. We show that the save-and-transmit and best-effort schemes achieve coding rates that approach the capacity with gaps vanishing at rates proportional to √(L/n) and (max{log n, L}/n)1/2, respectively.
Published in: IEEE Transactions on Information Theory ( Volume: 65, Issue: 11, November 2019)