Energy-efficient packet transmission over a wireless link

By Elif Uysal-Biyikoglu, Balaji Prabhakar, Abbas A. El Gamal. TNET, 2002

536 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4162d75f71b7c66edf6518d00b23851f35af361a

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Opportunistic Flooding in Low-Duty-Cycle Wireless Sensor Networks with Unreliable Links (2009, background): “Typically, the energy used in communication can be optimized through (i) physical-layer transmission rate scaling [39]; (ii) linklayer optimization for better connectivity, reliability, and stability [3,31,40]; (iii) network-layer enhancement for better forwarders and routes [5, 12, 43]; and (iv) ap”
Drift rate control of a Brownian processing system (2005, background): “Uysal-Biyikoglu, Prabhakar and El Gamal [15] have emphasized the trade-off between energy consumption and transmission speed in wireless communication: lower transmission power leads to lower energy consumption but also to slower transmission and hence longer delays.”
Broadcasting with an Energy Harvesting Rechargeable Transmitter (2010, background): “101813 traditional battery powered (un-rechargeable) systems [3]–[8], energy-efficient scheduling in energy harvesting networks with nodes that have rechargeable batteries has only recently been considered [1], [2].”
Cross-layer optimization for energy-efficient wireless communications: a survey (2009, methodology): “With knowledge of arrival time of each packet, it is shown in [53] that optimal schedule is to have equal transmission times for each packet under feasibility”
Optimum Transmission Policies for Battery Limited Energy Harvesting Nodes (2010, result): “Numerical results are presented to confirm the analytical findings.”
Throughput Optimal Policies for Energy Harvesting Wireless Transmitters with Non-Ideal Circuit Power (2012, background): “Among others, how to maximize the bits-per-Joule energy efficiency (EE) for the point-to-point wireless link has received a great deal of interest recently [6], [7], [8].”
Energy-Optimal Mobile Cloud Computing under Stochastic Wireless Channel (2013, background): “Since the energy cost per time slot is a convex function of bits transmitted, it is ideal to transmit as few bits as possible [25].”
Great expectations: the value of spatial diversity in wireless networks (2004, background): “One can tradeoff delay with energy consumption, as done in [95], [259], and references therein.”
A Tutorial on Ultrareliable and Low-Latency Communications in 6G: Integrating Domain Knowledge Into Deep Learning (2021, methodology): “Depending on the delay metrics, the existing queuing theory research papers can be classiﬁed into three categories, that is, average delay [142]–[145], hard deadline [15], [146]–[149], and statistical QoS [16], [150]–[156].”
TDMA scheduling algorithms for wireless sensor networks (2010, background): “We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.”
Optimal Packet Scheduling in an Energy Harvesting Communication System (2010, methodology): “This is similar to the energy minimization problem in [1], wh ere the objective is to minimize the energy consumption with a given deadlineconstraint.”