Channel Coding Rate in the Finite Blocklength Regime

By Yury Polyanskiy, H. V. Poor, Sergio Verdú. IEEE Transactions on Information Theory, 2010

3,769 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/9d4e83db13ea001165d8968a3e869e8716c78377

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Citations in the corpus

Fundamental Limits of Communication With Low Probability of Detection (2015, methodology): “However, by slightly varying the methods in [15], [16], or using the one-shot achievability bounds as in [17], [18], we can obtain that the sequence { K n } is achievable provided where P - lim inf denotes the limit inferior in probability , namely, the largest number such that the probability that…”
Ultra-reliable communication in 5G wireless systems (2014, methodology): “The following relation is given in [5]:”
A Comprehensive Overview on 5G-and-Beyond Networks With UAVs: From Communications to Sensing and Intelligence (2020, background): “given finite blocklength can be accurately approximated as follows [174]:”
Ultra-Reliable Low Latency Cellular Networks: Use Cases, Challenges and Approaches (2017, background): “A recent Polyansky-Poor-Verdu (PPV) analysis of channel capacity with finite block lengths [10] has provided the tradeoffs between delays, throughput, and reliability on Gaussian channels and fixed rate block codes, by introducing a new fundamental parameter called “channel dispersion;” this analysi”
Minimax Estimation of Functionals of Discrete Distributions (2014, background): “In information theory, the random variable ı(X) = ln 1 P (X) is known as the information density, and plays important roles in characterizing higher order fundamental limits of coding problems [65], [66].”
Ultra-Reliable and Low-Latency Vehicular Transmission: An Extreme Value Theory Approach (2018, positive): “transmission rate Rf = log2(1+γ)− √ 2γ(γ+2)erfc−1(2 ) √ L(1+γ) ln 2 which incorporates the blocklength L ∞ and a block error probability > 0 with the inverse error function erfc−1(·) [10].”
Ultra-Reliable and Low-Latency Communications in 5G Downlink: Physical Layer Aspects (2017, background): “However, when the packet size is small, ultra reliability can be achieved at the expense of the achievable rate reduction [4].”
Towards Massive, Ultra-Reliable, and Low-Latency Wireless Communication with Short Packets (2015, methodology): “The work by Polyanskiy, Poor, and Verd´u [12] has triggered a renewed interest in the problem of ﬁnite-blocklength information theory.”
Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Toward 6G (2021, background): “still suffer gaps to finite block length bounds, such as the normal approximation bound [163], when practical decoders with bounded complexity are being used [149].”
Differential Privacy as a Mutual Information Constraint (2016, background): “Also, the notion of ( ǫ, δ )-closeness goes by the name of E γ distance in some of the information theory literature, such as [22] and [19].”
Deep Joint Source-channel Coding for Wireless Image Transmission (2018, background): “It is known that the achievable rates guaranteeing a low block error probability for the blocklengths considered here are below the capacity [34] for the entire range of compression ratio values.”
Short Block-length Codes for Ultra-Reliable Low-Latency Communications (2018, methodology): “TB-CC, m = 8 [6] 12 TB-CC, m = 11 [6] 14 TB-CC, m = 14 [6] 16 eBCH (64,128) [9] 22 RM (64,128) [9] 16 Polar Code [9] 8 Polar Code + CRC-7 Normal Approximation (PPV) [1] d min”
An Adaptive Successive Cancellation List Decoder for Polar Codes with Cyclic Redundancy Check (2012, methodology): “To compare this performance to the Shannon limit at the same block length, we use a result from [4].”
Ultrareliable and Low-Latency Wireless Communication: Tail, Risk, and Scale (2018, background): “Progress has been made in URLLC in terms of short-packet transmission [9], [24] and other concepts such as shorter transmission time interval, network slicing, caching, multiconnectivity, and so forth.”