Has green energy arrived? Delay analysis for energy harvesting communication systems

Abstract

Energy harvesting communication systems provide a "green" solution by obtaining energy from ambient sources, such as sunlight or vibrations. This energy is stored for transmission of data packets which arrive at the link layer of an energy harvesting transmitter. Since the data and energy arrival processes are independent and random, the data packets wait in a queue for the accumulation of sufficient amount of energy and for service completion of previously arrived packets. Thus, the energy arrival process and the data service process jointly impact the data queue dynamics. This makes the queueing analysis of an energy harvesting communication system challenging. In this paper, we formulate a two stage virtual queueing system which decouples the wait stages for the energy arrival process and the service process. This virtual queueing system leads to closed-form expressions for the average packet delay and the probability of data packet loss due to buffer overflow. We assume that the data and energy arrivals are independent Poisson processes and the service time for data packets may have any general distribution. The expressions for the average packet delay and the probability of buffer overflow are shown to be exact when the service time becomes negligible, and the packet delay gets dominated by data packets waiting for arrival of sufficient energy. These expressions are compared with Monte Carlo simulations and are shown to be robust even when the service time is increased up to sixty percent of the average packet delay.

A Cross-Layer Approach to Reducing Packet Delay in Polling-Based Multiuser Systems

“…As mentioned in [12], the upper bound in (39) can be extended to a random binary linear code to obtain (42). In the following, we provide a sketch of the steps required to derive (42) from (39).…”

“…Another advantage of fixing the energy per coded bit is that when hard-decision decoding is employed on Gaussian channels, the crossover probability of the equivalent BSC does not change upon changing the coding rate. An interesting extension will be to analyze the packet delay in an energy harvesting communication system [42] when FEC is employed to reduce the PEP when transmitting over an error prone channel.…”

Performance Analysis of Buffer-Aided Relaying System Based on Data and Energy Coupling Queuing Model for Cooperative Communication Networks

“…The queue theory [17] is introduced into the cooperative wireless communication scenario to investigate the relaying system performance for jointly considering the data arrival and energy arrival. The authors in [18,19] investigate the throughput, delay, and so forth of system performance parameters by applying queue theory in wireless communication field. Reference [18] focuses on the system performance of Device-to-Device (D2D) communications with variable data arrival and interference.…”

“…By formulating the queuing model as a Discrete Time Markov Chain (DTMC), the authors adopt model decomposition scheme to iterate out the steady state distribution. A system performance analysis problem is discussed in [19] which considers the data arrival and energy arrival jointly. For the purpose of analyzing the coupling queuing system, the authors present a twostage virtual queuing model which decouples the wait states for the data transmission process depending on the energy arrival process.…”

“…For the purpose of analyzing the coupling queuing system, the authors present a twostage virtual queuing model which decouples the wait states for the data transmission process depending on the energy arrival process. However, [19] does not consider the influence of channel condition on the coupling relationship of data arrival and energy arrival. In other words, energy exhaust should modify self-adapting with the time varying channel environment.…”