2017/01/09 by Silas L. Fong, Vincent Y. F. Tan, Fong, Silas L. +3
Engineering · #Advanced MIMO Systems Optimization #Energy Harvesting in Wireless Networks #FOS: Computer and information sciences #Information Theory (cs.IT) #Wireless Communication Security Techniques
paper · pdf · doi:10.48550/arxiv.1701.02088
openalex publication_date 2017/01/09 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
This paper investigates the achievable rates of an additive white Gaussian\nnoise (AWGN) energy-harvesting (EH) channel with an infinite battery. The EH\nprocess is characterized by a sequence of blocks of harvested energy, which is\nknown causally at the source. The harvested energy remains constant within a\nblock while the harvested energy across different blocks is characterized by a\nsequence of independent and identically distributed (i.i.d.) random variables.\nThe blocks have length L, which can be interpreted as the coherence time of\nthe energy arrival process. If L is a constant or grows sublinearly in the\nblocklength n, we fully characterize the first-order term in the asymptotic\nexpansion of the maximum transmission rate subject to a fixed tolerable error\nprobability \ε. The first-order term is known as the\n\ε-capacity. In addition, we obtain lower and upper bounds on the\nsecond-order term in the asymptotic expansion, which reveal that the second\norder term scales as \√(\(L)/(n)) for any \ε less than\n1/2. The lower bound is obtained through analyzing the save-and-transmit\nstrategy. If L grows linearly in n, we obtain lower and upper bounds on the\n\ε-capacity, which coincide whenever the cumulative distribution\nfunction (cdf) of the EH random variable is continuous and strictly increasing.\nIn order to achieve the lower bound, we have proposed a novel adaptive\nsave-and-transmit strategy, which chooses different save-and-transmit codes\nacross different blocks according to the energy variation across the blocks.\n