Capacity of Gaussian Channels With Energy Harvesting and Processing Cost

Rajesh, R.; Sharma, Vinod; Viswanath, Pramod

doi:10.1109/tit.2014.2311822

Cited by 69 publications

(59 citation statements)

References 37 publications

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“…Our goal in this section is to formalize the results in (7) and (8). Before presenting the first main result, we define the second-order achievable rate as follows.…”

Section: Resultsmentioning

confidence: 99%

“…The qualitative interpretation of V + ε will be given in Remark 4 in Section III-C. Note that (7) and (8) together reveal that the back-off from C(P ) for the optimal length-n code with error probability less than ε is of the order L n . Therefore, the impact of correlation in the EH process can be interpreted as effectively decreasing the blocklength by a factor of L. In other words, to achieve the same reliability, one needs to increase the blocklength by a factor equal to the coherence time of the EH process.…”

Section: A Main Contributionmentioning

confidence: 91%

“…EH process in [3] and with a stationary ergodic EH process in [8]. The aforementioned studies showed that with an unlimited battery, the capacity of the AWGN channel with stochastic energy constraints is equal to the capacity of the same channel under an average power constraint as long as the average power equals the average recharge rate of the battery.…”

Section: B Related Workmentioning

confidence: 99%

See 2 more Smart Citations

On achievable rates of AWGN energy-harvesting channels with block energy arrival and non-vanishing error probabilities

Pong

Tan

Özgür

2017

2017 IEEE International Symposium on Information Theory (ISIT)

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This paper investigates the achievable rates of an additive white Gaussian noise (AWGN) energy-harvesting (EH) channel with an infinite battery. The EH process is characterized by a sequence of blocks of harvested energy, which is known causally at the source. The harvested energy remains constant within a block while the harvested energy across different blocks is characterized by a sequence of independent and identically distributed (i.i.d.) random variables. The blocks have length L, which can be interpreted as the coherence time of the energy arrival process. If L is a constant or grows sublinearly in the blocklength n, we fully characterize the first-order term in the asymptotic expansion of the maximum transmission rate subject to a fixed tolerable error probability ε. The first-order term is known as the ε-capacity. In addition, we obtain lower and upper bounds on the second-order term in the asymptotic expansion, which reveal that the second order term scales as L n for any ε less than 1/2. The lower bound is obtained through analyzing the save-and-transmit strategy. If L grows linearly in n, we obtain lower and upper bounds on the ε-capacity, which coincide whenever the cumulative distribution function (cdf) of the EH random variable is continuous and strictly increasing. In order to achieve the lower bound, we have proposed a novel adaptive save-and-transmit strategy, which chooses different save-and-transmit codes across different blocks according to the energy variation across the blocks.

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“…Our goal in this section is to formalize the results in (7) and (8). Before presenting the first main result, we define the second-order achievable rate as follows.…”

Section: Resultsmentioning

confidence: 99%

Section: A Main Contributionmentioning

confidence: 91%

Section: B Related Workmentioning

confidence: 99%

See 1 more Smart Citation

On achievable rates of AWGN energy-harvesting channels with block energy arrival and non-vanishing error probabilities

Pong

Tan

Özgür

2017

2017 IEEE International Symposium on Information Theory (ISIT)

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“…Authors in [8] studied the ergodic capacity under the assumption that the circuit energy cost other than the transmission power is independent of the power allocation strategy.…”

Section: Proposition 32mentioning

confidence: 99%

“…Instead, here we propose an efficient heuristic power allocation given by P s t = min P * t , B t − P (c) + , where P * t is the optimal solution obtained under conventional power grid model by letting P = μ. We obtain the power allocation P s t by following Theorem 3 in [8], which states that without circuit power overhead at the transmitter, the modified waterfilling solution, by counting the hard energy constraint at each time slot, is capacity achieving. Here our circuit power is slightly different; so we adopt P s t as a near-optimal heuristic solution.…”

Section: Proposition 32mentioning

confidence: 99%

Performance Analysis for Energy Harvesting Communication Systems: From Throughput to Energy Diversity

Huang

Alsaadi

et al. 2015

2015 IEEE Global Communications Conference (GLOBECOM)

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Energy harvesting (EH) based communication has raised great research interests due to its wide applications and the feasibility of commercialization. In this paper, we consider wireless communications with EH constraints at the transmitter. First, for delay-tolerant traffic, we investigate the long-term average throughput maximization problem and analytically compare the throughput performance against that of a system supported by conventional power supplies. Second, for delay-sensitive traffic, we analyze the outage probability by studying its asymptotic behavior in the high energy arrival rate regime, where the new concept of energy diversity is formally introduced. Moreover, we show that the speed of outage probability approaching zero, termed energy diversity gain, varies under different power supply models.

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Energy HarvestingAd HocNetworks

Huang¹,

Zhou²,

et al. 2018

Energy Harvesting Wireless Communications

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Capacity of Gaussian Channels With Energy Harvesting and Processing Cost

Cited by 69 publications

References 37 publications

On achievable rates of AWGN energy-harvesting channels with block energy arrival and non-vanishing error probabilities

On achievable rates of AWGN energy-harvesting channels with block energy arrival and non-vanishing error probabilities

Performance Analysis for Energy Harvesting Communication Systems: From Throughput to Energy Diversity

Energy HarvestingAd HocNetworks

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