Effective capacity: a wireless link model for support of quality of service

By Dapeng Oliver Wu, Rohit Negi. IEEE Transactions on Wireless Communications, 2003

1,512 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/91c3e53c160e3532d43f7b4901b9d54fa4dbe99f

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Toward Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions (2018, methodology): “Another approach is to use an intuition from [103] and to obtain the QoS exponent θ ( λ ) in the following way where Q ( t ) is the length of a queue at time t and τ s denotes the the average remaining service time of a packet being served.”
A Tutorial on Ultrareliable and Low-Latency Communications in 6G: Integrating Domain Knowledge Into Deep Learning (2021, methodology): “Based on Mellin transforms in network calculus, we can derive the effective bandwidth of arrival processes and effective bandwidth of service processes with the G ¨ artner-Ellis theory [150], [151], [164].”
Ultra-Reliable and Low-Latency Vehicular Transmission: An Extreme Value Theory Approach (2018, background): “From [9], we know that given a constant service rate Rc, the complementary cumulative distribution function (CCDF) of the queue length can be approximately written as F̄Q(q) ≈ Pr(Q > 0) ·e−θq, where exponent θ can be found by equating the effective bandwidth function β(θ) [9] to the constant service”
Quality-of-Service Driven Power and Rate Adaptation over Wireless Links (2007, background): “We also assume that the datalink-layer buffer size is infinite.”
An energy efficient and spectrum efficient wireless heterogeneous network framework for 5G systems (2014, background): “Effective capacity was proposed as a metric to measure the wireless fading channel performance in the presence of statistical QoS needs [13].”
Martingales-Based Energy-Efficient D-ALOHA Algorithms for MTC Networks With Delay-Insensitive/URLLC Terminals Co-Existence (2018, background): “Based on the effective capacity theory [11], the resource allocation algorithms with statistical delay-QoS guarantees have been explored in cellular systems [12]–[15].”